@prefix vivo: . @prefix edm: . @prefix ns0: . @prefix dcterms: . @prefix dc: . @prefix skos: . vivo:departmentOrSchool "Education, Faculty of"@en, "Educational Studies (EDST), Department of"@en ; edm:dataProvider "DSpace"@en ; ns0:degreeCampus "UBCV"@en ; dcterms:creator "Andres, Lesley"@en ; dcterms:issued "2009-01-09T21:51:47Z"@en, "1992"@en ; vivo:relatedDegree "Doctor of Education - EdD"@en ; ns0:degreeGrantor "University of British Columbia"@en ; dcterms:description """This study investigated how and why individuals chose various post-high school destinations. Theoretical frameworks based on Härnqvists (1978) conceptualization of the determinants of educational choice, rational choice theory as depicted by Elster (1986, 1989a, 1989b), and Bourdieu’s Theory of Practice (1977c, 1979, 1986, 1990b) were used to examine 1) the complex of individual and institutional influences of educational choice, 2) the processes underlying the decisions people made in choosing whether or not to pursue a post-secondary education, and 3) how students in the midst of the transition from high school to various post-high school destinations perceived these processes. Central to these analyses are the concepts of cultural capital, primary and secondary social capital, beliefs about and dispositions toward post-secondary education, academic capital, and enabling capital in relation to post-high school status. This research, conducted in British Columbia, has undertaken two kinds of examination: 1) the exploration of choices made by a large sample of recent high school graduates (n5345), as reported on a survey questionnaire and enriched by corresponding Ministry of Education linked data and 2) two sets of intensive, focused interviews conducted with a sample of Grade 12 students (n51) who were in the process of making choices about post-high school destinations. Three different types of analyses were conducted to explore the choice process. First, discrirninant function analyses were carried out to determine which individual and institutional determinants of educational choice, as depicted by Härnqvist, best predicted post-high school group membership (non-participant, non-university participant, university participant). Second, structural equation modelling using LISREL VI was employed to unravel the processes, as depicted in a model of Post-high School Status, that led to differential group membership. Finally, interviews with Grade 12 students were carried out to explore students perceptions of these processes. In the first discrirninant analysis, non-participants and participants in postsecondary education comprised the dichotomous grouping variable. Employing the variables included in Härnqvists framework, 74% of the non-participants and 79% of the participants could be correctly classified into their respective groups. The most powerful predictor was curricular differentiation, followed by level of education expected, total number of awards received, and primary social capital (parental influence variables). In a second discriminant analysis with non- university and university participants as the grouping variable, and based on the same set of predictors, the type of post-secondary institution attended was correctly predicted for 81% of university participants and 75% of non-university participants. High school grade point average most strongly predicted group membership, followed by curricular differentiation and level of education expected. Primary social capital (parental influence variables) or secondary social capital (influence of school personnel and peers) were not useful predictors in this analysis. In a three group discriminant analysis (non-participant, non-university participant, and university participant), the first function distinguished among these three groups on academic capital variables, disposition variables, and parents as sources of cultural capital, and the second discriminant function distinguished among the groups on primary and secondary social capital variables and number of academic awards received. Based on Härnqvist’s schema, 81% of university participants, 50% of non-university participants, and 67% of non-participants were correctly classified. Analyses by gender were also reported for each discriminant analysis. In the second type of analysis, a theoretical model of Post-high School Status was tested using LISREL VI. Strong positive relationships were demonstrated to exist between academic capital and post-high school status, and between dispositions toward post-secondary education and academic capital, for both males and females. The effect of parents as sources of cultural capital on dispositions toward post-secondary education was moderate, for both males and females. The total effects of parental transmission of cultural and social capital on post-high school destinations was significant. In these analyses, 58% of the variance in post- high school destination for the male sample and 54% of the variance for the female sample was explained. In the third analysis, the processes of educational choice were further explored through interviews with Grade 12 students. Of particular theoretical interest were differences in students’ long term dispositions toward post-secondary education, beliefs about post-secondary education, and how parents as sources of primary social capital enabled their children to pursue higher education. It was concluded that the treatment of two disparate strands of thinking (rational choice theory and Bourdieu’s Theory of Practice) as complementary rather than competing provide a coherent account of how students made choices about post-high school destinations. The theoretical frameworks developed for this study hold potential as a first step in revitalizing the investigation of equality of educational opportunity. Implications for further research, theory development, and policy directions are offered."""@en ; edm:aggregatedCHO "https://circle.library.ubc.ca/rest/handle/2429/3489?expand=metadata"@en ; dcterms:extent "6385961 bytes"@en ; dc:format "application/pdf"@en ; skos:note "PATHS ON LIFE’S WAY: DESTINATIONS, DETERMINANTS, ANDDECISIONS IN THE TRANSITION FROM HIGH SCHOOLbyLESLEY ANDRES BELLAMYB.Sc.N. Lakehead University, 1976B.Ed. Lakehead University, 1984M.Ed. Lakehead University, 1985A THESIS SUBMITTED IN PARTIAL FULFILMENT OFTHE REQUIREMENTS FOR THE DEGREE OFDOCTOR OF EDUCATIONinTHE FACULTY OF GRADUATE STUDIESDepartment of Administrative, Adult, and Higher EducationWe accept this thesis as conformingTHE UNIVERSI OF BRITISH COLUMBIAMarch 1992required standard© Lesley Andres Bellamy, 1992In presenting this thesis in partial fulfilment of the requirements for an advanceddegree at the University of British Columbia, I agree that the Library shall make itfreely available for reference and study. I further agree that permission for extensivecopying of this thesis for scholarly purposes may be granted by the head of mydepartment or by his or her representatives. It is understood that copying orpublication of this thesis for financial gain shall not be allowed without my writtenpermission./ — — / 1 114 /jDepartment ofThe University of British ColumbiaVancouver, Canada/ , / ttDate 1/DE-6 (2/88)ABSTRACTThis study investigated how and why individuals chose various post-highschool destinations. Theoretical frameworks based on Härnqvists (1978)conceptualization of the determinants of educational choice, rational choice theoryas depicted by Elster (1986, 1989a, 1989b), and Bourdieu’s Theory of Practice (1977c,1979, 1986, 1990b) were used to examine 1) the complex of individual andinstitutional influences of educational choice, 2) the processes underlying thedecisions people made in choosing whether or not to pursue a post-secondaryeducation, and 3) how students in the midst of the transition from high school tovarious post-high school destinations perceived these processes. Central to theseanalyses are the concepts of cultural capital, primary and secondary social capital,beliefs about and dispositions toward post-secondary education, academic capital,and enabling capital in relation to post-high school status.This research, conducted in British Columbia, has undertaken two kinds ofexamination: 1) the exploration of choices made by a large sample of recent highschool graduates (n5345), as reported on a survey questionnaire and enriched bycorresponding Ministry of Education linked data and 2) two sets of intensive,focused interviews conducted with a sample of Grade 12 students (n51) who werein the process of making choices about post-high school destinations.Three different types of analyses were conducted to explore the choiceprocess. First, discrirninant function analyses were carried out to determine whichindividual and institutional determinants of educational choice, as depicted byHärnqvist, best predicted post-high school group membership (non-participant,non-university participant, university participant). Second, structural equationmodelling using LISREL VI was employed to unravel the processes, as depicted ina model of Post-high School Status, that led to differential group membership.11111Finally, interviews with Grade 12 students were carried out to explore studentsperceptions of these processes.In the first discrirninant analysis, non-participants and participants in post-secondary education comprised the dichotomous grouping variable. Employing thevariables included in Härnqvists framework, 74% of the non-participants and 79%of the participants could be correctly classified into their respective groups. Themost powerful predictor was curricular differentiation, followed by level ofeducation expected, total number of awards received, and primary social capital(parental influence variables). In a second discriminant analysis with non-university and university participants as the grouping variable, and based on thesame set of predictors, the type of post-secondary institution attended was correctlypredicted for 81% of university participants and 75% of non-university participants.High school grade point average most strongly predicted group membership,followed by curricular differentiation and level of education expected. Primarysocial capital (parental influence variables) or secondary social capital (influence ofschool personnel and peers) were not useful predictors in this analysis. In a threegroup discriminant analysis (non-participant, non-university participant, anduniversity participant), the first function distinguished among these three groupson academic capital variables, disposition variables, and parents as sources ofcultural capital, and the second discriminant function distinguished among thegroups on primary and secondary social capital variables and number of academicawards received. Based on Härnqvist’s schema, 81% of university participants, 50%of non-university participants, and 67% of non-participants were correctlyclassified. Analyses by gender were also reported for each discriminant analysis.In the second type of analysis, a theoretical model of Post-high School Statuswas tested using LISREL VI. Strong positive relationships were demonstrated toexist between academic capital and post-high school status, and betweenivdispositions toward post-secondary education and academic capital, for both malesand females. The effect of parents as sources of cultural capital on dispositionstoward post-secondary education was moderate, for both males and females. Thetotal effects of parental transmission of cultural and social capital on post-highschool destinations was significant. In these analyses, 58% of the variance in post-high school destination for the male sample and 54% of the variance for the femalesample was explained.In the third analysis, the processes of educational choice were furtherexplored through interviews with Grade 12 students. Of particular theoreticalinterest were differences in students’ long term dispositions toward post-secondaryeducation, beliefs about post-secondary education, and how parents as sources ofprimary social capital enabled their children to pursue higher education.It was concluded that the treatment of two disparate strands of thinking(rational choice theory and Bourdieu’s Theory of Practice) as complementary ratherthan competing provide a coherent account of how students made choices aboutpost-high school destinations. The theoretical frameworks developed for this studyhold potential as a first step in revitalizing the investigation of equality ofeducational opportunity. Implications for further research, theory development,and policy directions are offered.Table of ContentsChapter PageAbstract iiTable of Contents vList of Tables xiList of Figures xvAcknowledgements xviiDedication xviiiINTRODUCTION 1Research Problem 3Purpose 4Significance of the Study 6Overview of the Dissertation 92. POST-HIGH SCHOOL DESTINATIONS AND THE DECISIONMAKING CONTEXT 11The Canadian Educational System 12The Transition Points 12Junctures During Secondary School 13Decisions Regarding Post- high School Destination 14The Canadian Post-secondary System 15Why Go On? The Choice of A Post-secondary Education 17The Market Effects of Education 18The Non-Market Effects of Education 21Broad Effects of Higher Education 22Transition from high school to work 23Changing Labour Market Requirements 28Education and Credentialism 31Post-secondary Education and Equality of Opportunity 34Non-participants in Post-secondary Education 35Participants and Institutions 38The Pluralistic Nature of Canadian Post-secondaryEducation - Reality or Myth? 39Transfer from College to University 42Summary 463. REVIEW OF THE LITERATURE AND THEORETICALPERSPECTIVES 47Factors Affecting Participation 47Social Stratification Perspective 48Status Attainment Research 50VviChapter PageDeterminants of Educational Choice.56Individual determinants of educational choice 58Institutional determinants of educational choice 58Post-high School Destination and Educational Choice 62Individuals as Rational Actors 66Practical Rationality 69Technical Rationality 69Bourdieu’s Theory of Practice 75Cultural Capital 75Social Capital 78Obligations and Expectations 79Information Channels 79Norms and Effective Sanctions 80Habitus 81Field 85A Theory of Practice and Post-high School Destination 87Self-elimination 88Overselection 89Relegation 90Reproduction and Agency 93Destinations, Determinants, and Decisions 94Summary 954. RESEARCH QUESTIONS, CONCEPTUAL FRAMEWORKS,AND HYPOTHESES 96Question 1 97Question 2 99Hypotheses 106Hypothesis One 106Hypothesis Two 106Hypothesis Three 106Hypothesis Four 106Hypothesis Five 107Hypothesis Six 107Question 3 1075. RESEARCH DESIGN 109Link File Data Base 109Grade 12 Graduate Follow-Up Survey Data 110The Sample 111Sampling Strategy 112Post-secondary status 112Geographic region 113Eligibility for university admission 113viiChapter PageSample Selection.115Questionnaire Development and Data Collection 116Response Rate 117Representativeness of the Sample 118Overall Return Rate 119Frame Population and Survey Respondents 120Respondents versus Non-respondents 123Preparation of the Data Set 129Summary 129Interviews with Grade 12 Students 131The Sample 132Selection of Schools 132Metropolitan School (MSS) 132Remote Secondary School (RSS) 133Urban/Rural Secondary School (URSS) 133Student Selection 134MSS 134RSS 134URSS 134Interview Procedure 135Representativeness of the Interview Sample 137Preparation of the Interview Data 138Reliability and Validity of the Interview Data 138Summary 139Delimitations and Limitations 140Delimitations 140Limitations 1406. OBSERVED MEASURES, LATENT CONSTRUCTS, ANDTHEORETICAL MEANING 142Individual Determinants of Educational Choice 144Characteristics of the Individual 145Sex 145Educational Achievement 146Curricular Differentiation 147Interests and Expectations 149Beliefs 150Characteristics of the Personal Environment 152Family Background 153School Environment 156Institutional Determinants of Educational Choice 157Conditions Antecedent to the Choice Situation 157Guidance Organization 157Influence of Teachers and Counsellors 158viiiChapter PageConditions Anticipated in the Choice Situation 160Geographic Availability 161Study Finance 161Dependent Variables 162Participant status 162Post-secondary Institution Status 163Post-secondary Status 163Summary 1647. POST-HIGH SCHOOL DESTINATIONS AND OPPORTUNITYSETS 165Participation or Non-participation in Post-secondary Education 166Evaluation of Assumptions 167Missing data 167Unequal Sample Sizes 167Multivariate Normality 168Homogeneity of Variance-Covariance Matrices 169Direct Analysis 170Interpretation 170Classification 178Cross-validation 180Stepwise Discriminant Function Analysis 181Gender Differences 185Summary 189University or Non-university Participation 190Direct Analysis 191Classification 196Cross-validation 197Stepwise Discrirninant Function Analysis 197Gender Differences 202Summary 205Non-participation, Non-university Participation, orUniversity Participation 206Direct Analysis 207Classification 214Cross-validation 216Stepwise Discrirninant Function Analysis 216Gender Differences 220Summary 225Destinations and Opportunity Sets - A Summary 226ixChapter Page8. A MODEL OF POST-HIGH SCHOOL STATUS.227The LISREL Model of Post-high School Status 228Tests of Model Fit 234Male Sample 235Female Sample 238Adequacy of the Measurement Model 241Analysis of the Structural Model 242Beliefs about Post-secondary Education 242Academic Capital 245Sources of Secondary Social Capital 246Dispositions 246Enabling Capital 247Post-high School Status 247Direct, Indirect, and Total Effects 248Female Sample 249Male Sample 252Discussion 2539. GRADE 12 STUDENTS AND THEIR PERCEPTIONS OF THETRANSITION PROCESS 258Destinations 260Dispositions Toward Post-secondary Education 265Academic Capital 274Beliefs about Post-secondary Education 278Primary and Secondary Sources of Social Capital 289Enabling and Constraining Forces and Post-highSchool Destinations 297Rational Choice and Post-high School Destinations 307Discussion 311Summary 31310. CONCLUSIONS AND DISCUSSION 314Central Findings of the Study 315Hypothesis One 318Hypothesis Two 318Hypothesis Three 319Hypothesis Four 319Hypothesis Five 319Hypothesis Six 320Significance of the Research 327Implications for Future Research 329Implications for Theory 332Implications for Policy Development 334xChapter PageREFERENCE LIST.340APPENDICESA. Survey Questionnaire 363B. Rates of Response and Non-Response 371C. Interview Data Collection 390D. Comparison of Males and Females. Means andStandard Deviations 400E. Summary of LISREL Parameter Estimates 402List of TablesTable Page1. Distribution of Individuals by Average Income, Educationand Sex, Canada and British Columbia, 1988 202. Unemployment Rates of Population 15 Years and Over byEducation and Sex, Canada and British Columbia,Annual Average 1989 243. Groups Identified as Under-represented in CanadianPost-secondary Education 374. Forms of Exclusion in Relation to Capital and Habitus 915. Frame Population of the 1988 Grade 12 Graduates 1146. Sample Size and Sampling Fractions by Stratum 1167. The Survey Respondents (Response Rate) 1188. Frame Population (A), Sampling Fractions (B), Response Rate (C),Survey Respondents (D), Percent Difference between Frame andSurvey Respondents (E) 1219. Respondents and Non-respondents - Significant Differences byGeographic Region and Eligibility for University Admission 12510. Comparison of Mean Values - Respondents and Non-respondentsby Geographic Region and Eligibility for University Admission.Participants 12711. Comparison of Mean Values - Respondents and Non-respondentsby Geographic Region and Eligibility for University Admission.Non-participants 12812. Interviewees by Sex and Geographic Region 13613. Interviewees by Sex and Post-high School Destination 13714. Determinants of Educational Choice and their Sources 143xixiiTable Page15. Means and Standard Deviations. Non-participants andParticipants 17116. Discriminant Function Analysis Summary Table. Non-participantsand Participants 17217. Pooled Within-Groups Correlations between DiscriminatingVariables and the Canonical Discriminant Functions.Non-participants and Participants 17518. Classification Matrix. Non-participants and Participants 17919. Stepwise Discriminant Function Analysis. Non-participants andParticipants 18220. Stepwise Analysis Classification Matrix. Non-participantsand Participants 18321. Discriminant Function Analysis Summary Table. Non-participantsand Participants - Females and Males 18722. Pooled Within-Groups Correlations between DiscriminatingVariables and the Canonical Discriminant Functions.Non-participants and Participants. Females and Males 18823. Classification Matrix. Non-participants and Participants.Females and Males 18924. Means and Standard Deviations. Non-university and UniversityParticipants 19225. Discriminant Function Analysis Summary Table. Non-university andUniversity Participants 19326. Pooled Within-Groups Correlations between DiscriminatingVariables and the Canonical Discriminant Functions.Non-university and University Participants 19427. Classification Matrix. Non-university and University Participants 19628. Stepwise Discriminant Function Analysis. Non-university andUniversity Participants 199xli’Table Page29. Stepwise Analysis Classification Matrix. Non-university andUniversity Participants 20030. Discrirninant Function Analysis Summary Table. Non-universityand University Participants. Females and Males 20331. Pooled Within-Groups Correlations between Discriminating Variablesand the Canonical Discrirninant Functions. Non-university andUniversity Participants. Females and Males 20432. Classification Matrix. Non-university and UniversityParticipants. Females and Males 20533. Means and Standard Deviations. Non-participants, Non-universityParticipants, and University Participants 20834. Discriminant Function Analysis Summary Table. Non-participants,Non-university Participants, and University Participants 20935. Canonical Discriminant Functions Evaluated at GroupMeans (Centroids) 21036. Pooled Within-Groups Correlations between Discriminating Variablesand the Canonical Discriminant Functions. Non-participants,Non-university Participants, and University Participants 21237. Classification Matrix. Non-participants, Non-participants,Non-university Participants, and University Participants 21538. Stepwise Discrirninant Function Analysis. Non-participants,Non-university Participants, and University Participants 21739. Stepwise Classification Matrix. Non-participants, Non-universityParticipants, and University Participants 21840. Discriminant Function Analysis Summary Table. Non-participants,Non-university Participants, and University Participants.Females and Males 221xivTable Page41. Pooled Within-Groups Correlations between Discriminating Variablesand the Canonical Discriminant Functions. Non-participants,Non-university Participants, and University Participants.Females and Males 22242. Classification Matrix. Non-participants, Non-university Participants,and University Participants. Females and Males 22443. Means, Standard Deviations, Product Moment Correlations, andFactor Loadings of the Indicator Variables - Males and Females 23344. Stages in the Modification of the LISREL Model of Post-high SchoolStatus - Males 23645. Stages in the Modification of the LISREL Model of Post-high SchoolStatus - Females 23946. Path Coefficients in a Model of Post-high School Status. Males andFemales 24447. Direct, Indirect, and Total Effects of Antecedent Variables onPost-high School Status. (Standardized Coefficients) 24948. Post-high School Destination by GPA, Curricular Differentiation,and Geographic Location 275List of FiguresFigure Page1. Post-high School Destinations.22. Decisions during high school 133. Unemployment Rates of Population 15-24 Years and Over,by Education, Canada Annual Averages 1980-1989 254. Unemployment Rates of Population 25-44 Years and Over,by Education, Canada Annual Averages 1980-1989 255. Härnqvist’s Determinants of Educational Choice 576. Adaptation of Elsters Schema of Rational Choice 707. Determinants of Educational Choice 988. Rational Choice Theory and Post-high School Status 999. Cultural Capital and Post-high School Status 10110. Social Capital and Post-high School Status 10311. A Model of Post-high School Status 10512. Populations and Samples Relevant to the Grade 12 GraduateFollow-up Survey 13013. Data Sources 14114. Academic Capital 14815. Dispositions toward Post-secondary Education 15016. Beliefs about Post-secondary Education 15217. Sources of Cultural Capital 15418. Sources of Primary Social Capital 15519. Sources of Secondary Social Capital 159xvxviFigure Page20. Enabling Capital.16221. Post-high School Status 16322. Plot of Group Centroids 21123. Path Diagram for an Hypothesized Model ofPost-high School Status 22924. Parameter Estimates in a Model of Post-highSchool Status 24325. Stated Post-high School Destination (October 1989 and May 1990)and Actual Post-high School Destination (October 1990) 26226. Ameliorated Model of Post-high School Status 330ACKNOWLEDGEMENTSI am grateful to the members of my thesis committee for their individualand collective contributions to the improvement of my research. My researchsupervisor, Dr. Neil Guppy, has provided me with solid direction, incisivecomments, and ceaseless encouragement. I extend my thanks also to Dr. JohnDennison for his constant vigilance and guidance, to Dr. Donald Fisher for sharinghis knowledge of both theory and methodology, and to Dr. Robert Schutz forguiding me gently through the statistical analyses.I wish to thank Dr. Grant Fisher at the B.C. Council of Admissions andTransfer, Scott Mclnnis at the Ministry of Advanced Education, Training, andTechnology, and Glen Forrester and David Shea at the British Columbia ResearchCorporation for assisting me to gain access to the data sets employed in this study.Also, I extend my appreciation to the students who enriched my study by sharingtheir experiences of the transition process.I would also like to acknowledge the financial assistance provided by theSocial Sciences and Humanities Research Council of Canada.I thank my friends and the faculty in the Department of Administrative,Adult, and Higher Education for their genuine interest in me and my work. Inparticular, I thank Shauna Bufterwick, Trisha Wilcox, Jay Handel, Graham Kelsey,Jean Hills, Ian and Billie Housego, and Kjell Rubenson.Finally, to my husband, John Bellamy, my sincere thanks and appreciationfor the many years of encouragement, assistance, and patience. His support, alongwith the constant companionship of Aururn and Ali (the cats), has made my life asa graduate student most pleasant.xviixviiiTo the Memory of Sheldon ChumirChapter 1INTRODUCTIONFor every Canadian student, their last year of high school is, by definition,a year of transition. This transition typically involves a separation from theprevious world of high school and family and incorporation into a new world ofadult life. This particular transition point is rather unique, for its occurrence ispredictable but involuntary’. Despite its predictable and inevitable nature, thetransition from high school is far from straightforward. Inherent in thistransition is the decision of whether or not to continue in the educationalsystem. This decision is a major life decision (Sloan, 1987), whether or not it isrecognized as such, for its consequences impact on almost every aspect of anindividuals future. However, the choice is not simply one of selecting onealternative over another. Even at its simplest level, several decisions areinvolved in this transition (see Figure 1).1 These terms are borrowed from Van Gennep (1960) who distinguished three major phases oftransition or rites de passage: separation, transition, and incorporation, and Adams, Hayes, andHopson (1976) who have categorized the forms of transition.12Decisions regarding post-high school destinations are made within thesocial, cultural, historical, and interpersonal contexts of the deciding individual.Constraints and opportunities due to socioeconomic circumstances, geographiclocation, cognitive and non-cognitive personality traits affect the decisionmaking process. Societal conditions of inequality, of cultural and economicresources, and the prevailing employment climate also impinge on decisionmaking.An informed decision requires a long-term planning perspective,crystallized preferences, and recognition of constraints and opportunities.Ironically, such a complex life decision occurs during adolescence, the verystage of human development that tends to be characterized by unstablepreferences, limited past experience, and opaque career goals. As Sloan (1987)suggests, the ability to reach a decision under circumstances such as these is9qure 1: ost-fi.tqfi sclwotclestiiuztions3difficult. Yet, we continue to presume that individuals make optimal decisionsregarding life beyond the confines of high school.Despite a substantial body of evidence to support the claim that educationdoes enhance ones life chances, Canadian national statistics reveal that nearly50% of Grade 12 graduates do not continue directly to some form of post-secondary education (Report of the Standing Senate Committee on NationalFinance, 1987). Given what is known about the benefits of post-secondaryparticipation and the observation that numerous high school graduates do notgo on, some interesting questions arise: Why do some students not continue onto post-secondary education? Why do others decide to pursue it, and what is itthat makes those who do continue choose one type of post-secondary institutionover another? How do students actually make this decision?Research ProblemThe relationship between participation in post-secondary education andthe factors affecting participation is well documented in studies of post-secondary education in Canada. These factors are traditionally cited under thefollowing headings: socio-economic (social class, parents occupation, parentseducation, sex, ethnicity), geographic (urban/rural/remote differences),institutional (admission standards, availability and content of programs),cognitive personality traits (IQ, aptitude), noncognitive personality traits(motivation, aspiration), and financial (costs to the student, financial aid).Various investigations have identified and measured the factors affectingparticipation. These studies include explorations of aspirations and expectationsof high school students (Anisef, 1975; Crysdale, 1975; Gilbert & McRoberts,41977; O’Neill, 1981; Porter, Porter, & Blishen et al., 1982) the characteristics ofthe Canadian post-secondary population (Dennison, Forrester, & Jones, 1982;Pike, 1970; Porter, Porter, & Blishen et a!., 1982); the impact of social origin,present school experience, and relationships with the future on vocationalindecision, educational intentions, and the level of occupational preferences(Breton, 1972); trends over time in Canadian post-secondary enrollment(Guppy, 1988; Harvey, 1977); characteristics of community college students(Dennison, Tunner, Jones, & Forrester, 1975); and experiences of going fromschool to work (Anisef, 1980).Such studies, however, provide little insight into the dynamics of howindividuals actually make decisions about post-high school destinations.Although a considerable body of literature on accessibility to and participationin post-secondary education in Canada exists, very little research effort has beenexpended on elucidating the processes behind the decisions people make inchoosing whether or not to pursue post-secondary education. It is clear thatcertain factors affect the choice to participate in post-secondary education.However, little empirically derived evidence can be found in the literature toexplain how and why individuals make the decisions they do regarding posthigh school destinations. As Hossler, Braxton, and Coopersmith (1989) suggest,a set of theoretical concepts is needed to explain the interrelationships amongthe salient factors of the post-secondary choice process.PurposeThe purpose of my study is to investigate how and why individualschoose various post-high school destinations. Three major research questions5are advanced to explore this problem. First: Given a sample of recent highschool graduates, what factors influence whether and where one participates inpost-secondary education? The second major question is: What processesunderlie the decisions individuals make in choosing whether or not to pursue apost-secondary education? Finally, to further unravel these processes, a thirdquestion is posed: How do students perceive the processes which underlie theirdecisions?The complicated nature of destinations, determinants, and decisions meritsboth theoretical and methodological complexity. Hence, in order to provideanswers to these questions, the research strategy of theoretical andmethodological triangulation is employed. First, in relation to the first question,the macro-processes of post-secondary participation are examined byemploying an analytical framework based on Härnqvist’s (1978)conceptualization of the determinants of educational choice. This framework isused to assess the individual and institutional factors that contribute to orcurtail post-secondary participation in a large sample of the 1988 cohort ofBritish Columbia high school graduates. To answer the second question, this setof macro-level or aggregate data is used to analyse micro-level concepts specificto rational choice theory as explicated primarily by Elster (1986, 1989a, 1989b)and Bourdieu’s Theory of Practice (1977c, 1979, 1986, 1990b). A conceptualmodel of Post-high School Status is developed from the research questions andis used to determine the relationship between the concepts advanced by thesetwo theoretical perspectives. Finally, to further detail the intricacies of decisionmaking in relation to post-high school destinations, this model of Post-highSchool Status is used as a guiding theoretical framework on which to base ananalysis of data collected from two sets of interviews conducted with Grade 12students in 1989 and 1990.6Thus, by examining the choices made by a cohort of recent high schoolgraduates (along with linked secondary and post-secondary institutional database files) and a sample of students who were currently in Grade 12, a range ofparticipants, non-participants and potential participants in the post-secondarysystem was included in this study. The study was conducted within the contextof the British Columbia educational system.Significance of the StudyThere is a paucity of research on the processes behind the decisions peoplemake in choosing whether or not to pursue post-secondary education. TheReport of the Committee to Examine Participation Trends in Alberta concludedthat while the results of their study provided a clear picture of who attendspost-secondary education, it did not provide any information about how thesechoices were made (Alberta Advanced Education, 1984). Härnqvist (1978)commented that because educational choice has very rarely been used as adependent variable in studies of institutional and structural determinants,knowledge in this area is “incomplete and scattered” (p.8O) This study extendsthe current knowledge base by considering the determinants of educationalchoice, the processes behind these actions, and how individuals perceive theseprocesses.In much of the current theoretical debate in the social sciences, a reexamination of two disparate views of action have been called for (Coleman,1986, 1990; Gambetta, 1987; Hindess, 1988). In the first of these two streams ofthought, the actor is treated as a “creative subject, pursuing its interests to thebest of its ability and constituting actions and social relations in the process” and7in the second stream as ‘the picture of the human subject as literally subjected tothe system of social relations in which it internalizes its part and subsequentlyacts out” (Hindess, 1988, p.38) One feature of the theoretical promise of thisstudy is that it treats these two disparate intellectual streams as complementaryrather than competing. Guided by rational choice theory and Bourdieu’s Theoryof Practice, a theoretical model which incorporates the first stream within aframework of the second stream is developed. Insights into the choices thatindividuals make about post-high school destinations, and the processesunderlying these choices are gained by addressing this theoretical debate.Through the use of multiple data sources and a variety of data analyses, thisstudy extends the empirical work of Gambetta (1987) and Rehberg andRosenthal (1978).The significance of this study can also be justified in more general terms. Alimited amount of Canadian research has been conducted on access issues inregard to non-university participation, the use of multivariate and multi-site! multirnethod approaches to data analysis, and studies whichsimultaneously consider the non-participants and participants of post-secondary education (Anisef, 1985). Of the Canadian studies that do exist, mosthave been conducted using data limited to participation in “binary systems” ofpost-secondary education (Campbell, 1975, p.55) in which the university andnon-university sectors do not overlap, but exist independently of each other. Forexample, in Ontario post-secondary education has been classified as a “binarysystem” and university-equivalent courses are not available at the Colleges ofApplied Arts and Technology (CAAT); thus, formal transfer with creditbetween the two types of institutions does not exist. The CAAT’s werespecifically designed to provide training for students who were not eligible foruniversity entrance.8In contrast, the post-secondary system in British Columbia has beendescribed as a “ternary system” (Campbell, 1975, p.57’) or “combineddevelopmental model” (Worth, 1972, p.82). After completion of one or two yearsof university-equivalent courses at one of the fifteen community colleges,students with appropriate prerequisites are able to transfer to one of the threeprovincial universities to complete a bachelor’s degree. Differences in provincialpost-secondary systems, and resulting participation patterns, may enhance ourunderstanding of the effects of the structure of the system on choices regardingpost-secondary participation.The issue of participation in post-secondary education continues to be amajor concern in the development of educational policy. The question of theneed for wider accessibility to the post-secondary system recurred throughoutthe National Forum on Post-Secondary education held in Saskatoon in 1987, andimprovement of accessibility was identified as one of four priorities requiringimmediate federal-provincial cooperation (Department of the Secretary of State,1988). The Report of the British Columbia Provincial Access Committee (1988)states that “increasing accessibility to advanced education and job training hasemerged as a major concern of citizens, educators and government” (p.1) and:the need our province faces, therefore, is not to just improve equality of access for allour citizens, but also to improve the overall rate of transition of students from highschool into advanced education and job training institutions of all kinds .Opportunities for our young people need to be expanded so that they can competewith highly trained and educated people coming from elsewhere. (p.5)This view continues to be reiterated in recent policy documents (Ministry ofAdvanced Education, Training, and Technology, 1991). As well, in a currenthuman resource development initiative in British Columbia, the transition from9school has been identified as one of the nine key policy areas requiring indepthexamination (British Columbia Human Resource Development Project, 1991).An investigation of all aspects of participation in post-secondary educationwould require studies that go beyond the transition from high school to post-secondary education and would include retention, transfer, graduation, andtransition to the work force. Although this study is limited to the transition ofBritish Columbia Grade 12 enrollees and graduates to various post-high schooldestinations, it contributes to an understanding of the decisions made by non-participants, as well as participants at universities, community colleges andother post-secondary institutions. This study reframes current approaches toparticipation, accessibility, and decision making extant in the literature. Suchreframing may contribute to a greater understanding of decision makingprocesses and may help explain existing disparities between the characteristicsof participants and non-participants in post-secondary education.Overview of the DissertationThis chapter has provided the background to this study, an introduction tothe research problem, the purpose, and the significance. Chapter 2 endeavoursto cast the topic of choice regarding post-high school destination into a broadeducational, societal, and cultural context. Literature related to the structure ofthe system, benefits of a post-secondary education, youth and unemployment,and post-secondary education and equality of opportunity are reviewed. InChapter 3 the literature relevant to participation, rational decision making andBourdieu’s Theory of Practice is reviewed. In Chapter 4 the research questionsare developed, and corresponding conceptual frameworks to address these10questions are presented. Specifically, a model of Post-high School Status isadvanced which treats the tenets of rational choice theory and concepts of socialcapital, cultural capital, and dispositions or habitus espoused by Bourdieu ascomplementary constructs. Chapter 5 is concerned with the research design. Inthis chapter, a description of the data sources, instruments and methods of datacollection, and details of the samples is provided. Chapter 6 provides adescription of the manifest variables from survey sample data, formation of thelatent constructs, and the theoretical meaning attributed to these variables. InChapter 7, discriminant function analysis is employed to further delineate theopportunity sets of non-participants, non-university participants, and universityparticipants. In Chapter 8, the model of Post-high School Status is tested usingLISREL VI. Chapter 9 uses interview data to provide an indepth description ofhow students perceive the constructs identified in the model of Post-high SchoolStatus. In Chapter 10 a summary of the findings, conclusions, and implicationsis presented. Directions for research, theory, and policy development aresuggested.Chapter 2POST-HIGH SCHOOL DESTINATIONS AND THE DECISION MAKINGCONTEXTAs indicated in Chapter 1, decisions about post-high school destinations arenot made in isolation. Rather, these decisions are influenced by three interrelatedcontexts: the interpersonal context of the deciding individual, the context of theexisting educational system, and the broad context defined by our society andculture. These interrelationships result in what Saussure refers to assimultaneous complications in many direction&’ (cited in Bourdieu, 1984, p.126).Buchmann (1989) advises that when an analysis focuses on a singletransition period or life stage, it is critical that the life stage be located within thebroader context of that society. Hence, the purpose of this chapter is to reviewthe two larger contexts of the transition under consideration in this study; that is,educational and societal contexts within which decisions regarding post-highschool destinations occur. First, the structures of the elementary, secondary, andpost-secondary systems in British Columbia, and the transition points that occurwithin these structures are reviewed. Second, issues surrounding low transitionrates are discussed under two headings: 1) the benefits of a post-secondaryeducation, and 2) the transition from school to work. Finally, equality ofopportunity in relation to post-secondary education is considered.1112The Canadian Educational SystemGambetta (1987) indicates that a given educational system creates anexternal constraint on individual decision behaviour. It does so by providing theorganization for a given type of education, seffing the rules and procedureswhich regulate admission, selection, promotion, and certification. Individualswithin the system, when making a decision, are required to adjust to and choosefrom the prescribed set of alternatives offered by the system. The possibleeducational trajectories are dependent on the structure of the system and thestreaming and selecting mechanisms within it.In this section, a review of the structures of the elementary, secondary, andpost-secondary systems in British Columbia is outlined, and the transition pointsthat occur within this structure are identified.The Transition PointsDuring the pre-tertiary years, Canadian students face two key decisionsregarding their life trajectories: first, once the age of compulsory attendance hasbeen reached, whether to withdraw from school or continue until graduation;and second, upon high school graduation, whether to continue to postsecondary education or enter the labour force.13Junctures During Secondary SchoolThe first point in which a participation choice may be exercised arises forthe Canadian student only after she or he reaches minimum school leaving age.The choice, depicted in Figure 2, is whether to continue beyond the compulsoryattendance age or to leave the educational system. Until that point, childrenwithin a defined age range are “legal captives of the school system” (Fischer,1987, p.43) and are obligated by law to attend school. The ages of compulsoryattendance vary from province to province between a lower limit of 5 years andan upper limit of 16 years. In British Columbia, Section 3(1) of the the School Actrequires that each child between the fifth and sixteenth birthdays attend schooldaily (School Act, 1989).ageJ tt1ufrawfrom tile1 eucatioim1systemfFWure 2. fDecLcion.c éuthzg fiigfi scfiooLIn Canada, education is also a right. That is, individuals within a specifiedschool age range, which is usually broader than the compulsory age ofattendance, have the right to attend school (Bezeau, 1989). In British Columbia, itis the obligation of the Ministry of Education to ensure that an educationalprogram is provided for every child of school age. School age is specified asbetween 5 and 19 years (School Act, 1989). This right of attendance isaccompanied by an implicit expectation that students will stay in school until14they graduate from high school. In fact, a credential is awarded only uponcompletion of the requirements for high school graduation.The majority of students do remain in school and complete therequirements for Grade 12 graduation. The British Columbia Ministry ofEducation (1990b)2 reports that in September 1989, approximately 87% of thosewho entered Grade 8 in 1985 enrolled in Grade 12 in 1989, even thoughattendance was compulsory only from ages 7 through 14g. Of this cohort, 63%met the requirements for high school graduation4.Decisions Regarding Post- high School DestinationWhile the choice regarding participation in high school is limited towhether or not to stay in the educational system until graduation, optionsregarding post-high school destinations are more diverse. Historically, themajority of high school graduates have not pursued post-secondary studies, andeven as late as the 1950s, attendance at post-secondary institutions wasrestricted to a select few (Harris, 1976). However, changes to the post-secondarysystem over the past thirty years has ensured that access to some form of post-secondary education is open to all high school leavers. These changes and theresulting available options warrant further comment and are discussed in thenext section.2 Throughout this chapter, 1988 and 1989 statistics are cited to complement data sets used in theanalysis chapters of this study.Students who attended school during the 1987/88 year were subject to compulsory attendancerules as stipulated by Section 113(1) of the School Act (1979). Since that time, compulsoryattendance has been redefined in the new School Act (1989).The present study is delimited to an examination of decisions made by grade 12 enrollees andgraduates and does not address the decisions of either dropouts or the 24% of Grade 12 studentswho fail to meet graduation requirements (Ministry of Education, 1990). Early withdrawal andnon-completion of graduation requirements warrant separate consideration; it is beyond thescope of this study.15The Canadian Post-secondary SystemExpansion of the Canadian system of post-secondary education since the1960s has been described as extraordinary (OECD, 1976). In terms of quantitativedevelopment, Canada is considered to be among the educational leaders.Contributing to this expansion were the increase in the number of placesavailable in existing universities, the establishment of new universities, and thedevelopment of a community college system in each province. Canada nowboasts 65 universities, 123 public community colleges, 53 public post-secondaryinstitutions, and an assortment of private post-secondary institutions (Dennison& Gallagher, 1986; Department of the Secretary of State of Canada, 1990). As aresult, over the last three decades significant improvement has occurred in mostforms of post-secondary participation, including the transition from high schoolto post-secondary education. Full-time enrolment in post-secondary institutionshas increased from 91,000 in 1951-52 to 817,000 in 1988-89 (Department of theSecretary of State of Canada, 1990). Transition rates from Grade 12 directly topost-secondary education have increased from 44.5% in 1979/80 to 53.2% in1985/86 (Report of the Standing Senate Committee on National Finance, 1987).Full-time post-secondary enrolment among the 18 to 24 age group in 1986/87totalled 25.5% (Statistics Canada, 1989).The post-secondary system in British Columbia is described as a‘diversified and well-developed structure for advanced education and jobtraining” (Report of the Provincial Access Committee, 1988, p.3). The postsecondary system has expanded over the past three decades to include threepublic universities, one private university, fifteen community colleges, fourpublic institutes, an Open Learning University and an Open Learning College, aswell as many private colleges and trade schools. University degree program16availability has been enhanced recently by the creation of four universitycolleges within the existing community college system. As well, a degreegranting institution for northern British Columbia is currently underconstruction. It is reported that 116,500 full-time and part-time studentsparticipate annually in non-vocational education and over 12,000 students areenrolled in full-time vocational programs (Department of the Secretary of Stateof Canada, 1990; Ministry of Advanced Education and Job Training, 1988). Thetransition rate6 for British Columbia students moving directly from high schoolto college or university, has increased to 45% in 1985-86 from 35% in 1978-79(Report of the Standing Senate Committee on National Finance, 1987).This macroscopic way of viewing participation in post-secondary educationhas been referred to as Type II accessibility (Skolnik, 1984, cited in Anisef, 1985)which pertains to the average probability of participation in post-secondaryeducation by all individuals in a relevantly defined population. The higher theaverage probability, the greater the Type II accessibility. Using Type IIaccessibility as a measure, the number of students making the transition fromhigh school to post-secondary education appears to compare favourably withpast transition figures. A transition rate of 45% is not necessarily problematic if,as Radwanski (1987) points out, the objective is merely to ensure that everyyoung person has the opportunity to obtain as much education as she or hedesires. However, there are several reasons for concern regarding the transitionof British Columbia Grade 12 graduates to post-secondary education.5 This figure includes university transfer, career/technical, general studies, and collegepreparatory programs. Of the full-time students in British Columbia 1988/89, 38,580 attenduniversity and 25,488 are at community colleges. Part-time participants include 17,997 atuniversity and 34,658 at community colleges (Department of the Secretary of State of Canada,1990).6 Transition rate is defined as the percentage of high school graduates proceeding directly toeither college or university following high school graduation (Report of the Standing SenateCommittee on National Finance, 1987).17When transition rates are compared with other provinces, British Columbiaranks sixth (above Saskatchewan, Manitoba, New Brunswick and Prince EdwardIsland). Although 63% of Grade 12 enrollees in British Columbia have graduatedfrom high school each year since 1985 (Ministry of Education, 1990), each yearapproximately 45% continue directly on to some form of post-secondaryeducation (Report of the Standing Senate Committee on National Finance, 1987).Whereas the overall transition rate in Canada is 53%, it is 45% in BritishColumbia (Report of the Standing Senate Committee on National Finance, 1987;Report of the Provincial Access Committee, 1988). In other words, for 55% ofGrade 12 graduates, the immediate post-high school destination is not post-secondary education. The issues surrounding low transition rates will bediscussed under the following headings: 1) The choice of a post-secondaryeducation, and 2) The transition from school to work.Why Go On? The Choice of A Post-secondary EducationA basic assumption made in this study is that participation in post-secondary education enhances one’s life chances. According to Dahrendorf(1979), life chances are the “moulds of human life in society; their shapedetermines how and how far people can unfold” (p.ll). Dahrendorf claims thatlife chances are not attributes of individuals, but rather individuals have lifechances in society, and their life chances may “make or break them”. Life chancesare described as “opportunities for individual growth, for the realization oftalents, wishes and hopes, and these opportunities are provided by socialconditions” (p.30). One such opportunity is participation in education, and in18particular post-secondary education; it is an avenue that allows individuals toextend their life chances and to grow in response to them.There is a substantial body of evidence to support the claim that educationdoes enhance one’s life chances. It can be demonstrated that participation in post-secondary education makes a difference in terms of future labour marketexperience, employability, and quality of life. That is, individuals who achievehigher levels of education are more likely to earn higher salaries, hold moreprestigious positions in the work force, are less likely to be unemployed, and aremore likely to both benefit from and contribute to the robustness of society ingeneral (see references below).The benefits of a post-secondary education will be considered under thefollowing headings: the market and non-market effects of education, and thebroad effects of higher education.The Market Effects of EducationOne way of determining the benefits of a post-secondary education is toexamine the private and social payoff of additional education. Over the years,numerous studies have been conducted on the economic returns to investmentsin education and the role of education in national economic growth (Mincer,1989; Murphy & Welch, 1989; Schultz, 1961; Stager, 1972; Vaizey andDebeauvais, 1961; West, 1988). These studies dealing with individual rates ofreturn usually show that there is a positive correlation between economicproductivity and the number of years of formal education.Economists generally agree that, from a market perspective, highereducation is a good investment that on the average produces returns that amplyjustify the cost (Bowen, 1982; Douglass, 1977). For example, Vaillancourt and19Henriques (1986) report that private rates of return for Canadian men in 1981ranged from 10 to 14% for three years of university education, and 8 to 12% forfour years of university education (p.454). They conclude that:the real after-tax private rate of return to a university education is significantly higherthan rates of return associated with other types of investment such as long-termgovernment bonds that usually yield between 3 and 5 percent in real terms (p.454).In other words, compared to other forms of investment, three to four years ofuniversity education will generally yield higher private rates of return. Byinvesting in themselves, Schultz (1961) explains, individuals are able to augmentthe range of choices available to them and thus, enhance their welfare (p.2). Thepositive association between post-secondary education and earnings isdemonstrated in Table 1:20Table 1.Distribution of Individuals by Average Income,Education and Sex, Canada and British Columbia,1988.CANADA BRITISH COLUMBIATotal Male Female Total Male Female$ $ $ $ $ $0-8 years 14,867 19,239 9,970 15,390 20,538 9,691Some high schooland no postsecondary 18,708 24,087 13,128 -Some post-secondary 19,013 23,452 14,297 20,175 25,595 14,689Post-secondarydiploma/certificate 23,765 30,272 17,920 - -University degree 35,237 42,035 26,301 31,727 38,508 22,807(Income Distributions by Size in Canada, 1989. Catalogue 13-207)Murphy and Welch (1989) comment that the evidence demonstrating thepositive association between schooling and earnings is so strong that it is“impossible to ignore the role of education in systematic studies of individualearnings”7 (p.l7) West (1988) also concludes that the higher the level ofeducation, the better the labour market experience.It must be noted, however, that while women attain higher educationallevels than men (Bellamy & Guppy, 1991), the return to their investments ineducation is not as lucrative. Gaskell (1983) comments that an individual womanmay be able to increase her income level relative to other women by furthering7Wh.ile a decline in returns to higher education was reported in the 1970’s (Freeman, 1976), it hasbeen described as a temporary, short-lived cyclical condition rather than the beginning of a longterm trend. Increased returns to schooling in the 1980’s have been described as dramatic (Stager,1989; Murphy and Welch, 1989). Stager (1989) reports that in 1985, the estimated returns havealmost returned to the levels that prevailed in 1960.21her education, but large disparities in earnings continue to exist between menand women with equal educational levels.The Non-Market Effects of EducationEconomists did not deny the existence of nonmonetary values and in factacknowledged that changes in observed earnings and output did not capture allof the relevant economic effects of education. Few, however, concernedthemselves with the wide range of nonmarket impacts of education (Haveman &Wolfe, 1984), but chose to concentrate their attention on human attributes whichyielded outputs measurable in dollars. Douglass (1977) posits:in human capital, economists have fashioned a concept that leaves no room for thetraits of individuals that produce such ineffable outcomes as happiness, love,friendliness, humanitarian impulses, spirituality, knowledge for its own sake, and soon. These are simply left out of any assessment of the value of human capital except tothe extent that they significantly influence the earning capacity of individuals or theproductive capacity of the economy. (p.363)Studies of the nonmarket effects of education have demonstrated thatincreased levels of education are positively related with one’s own health andfamily health status (Fuchs, 1980; Taubman & Rosen, 1980), efficiency ofconsumption choices (Hettich, 1972; Schultz, 1975), attainment of desired familysize (Michael, 1973), lower mortality rates (Grossman & Jacobowitz, 1981),efficiency in labour and marriage market decisions (Haveman & Wolfe, 1984),better matching of jobs with skill requirements and migration decisions(Schwartz, 1984), increased savings (Solomon, 1975), greater levels of charitablegiving (Dye, 1980), and decreased criminal activity (Ehlrich, 1975). Haveman andWolfe (1984) conclude that “one is left with the strong impression thatincremental schooling yields aggregate economic well-being benefits that are22considerably larger than those captured in estimates of the differences in labourmarket earnings associated with differences in the average level of schooling”(p.390).Broad Effects of Higher EducationEconomists have long been preoccupied with measuring the market effectsand, more recently, the non-market effects of education. They also identify theexistence of one type of broad effect of education on society, referred to as anexternality-generating or spillover effect (Havernan & Wolfe, 1984; West, 1988).An externality is said to exist when the self-interested action of an individual orgroup indirectly affects or spills over to another person or group. Examples ofsuch positive external benefits include income gains of individuals other thanthose who have received additional education and also of subsequentgenerations resulting from a better educated work force.Trow (1989) notes that some of the larger effects of higher education are notwell recognized or easily quantified. He suggests that some of the broaderoutcomes (as opposed to intended effects) of higher education of those exposedto it include: 1) attitudinal changes with resulting increased appreciation of andtolerance to cultural differences and weakening of racial prejudices; 2)lengthened temporal perspectives towards public issues, thus allowing andenhancing long-term planning and program development; and 3) cultivation of alife-long learning perspective, and hence, the continued progress toward alearning society. In a longitudinal study of the factors affecting recurrent adulteducation in Sweden, Tuijnman (1990) concluded that higher levels of formalyouth education were positively related to participation in recurrent adult23education and these effects could be demonstrated over three successive ageperiods.While the benefits of continuing on to post-secondary education can beeasily gleaned from the literature, arguments supporting the choice to enter thework force directly from high school are not as readily apparent. In the followingsection, the transition from high school to work is considered.Transition from high school to workThe journey from school to the world of work is one of the importantcomponents of the transition of youth to adulthood. This transition, however, isidentified by many as especially difficult for high school leavers (Coleman &Husén, 1985; Economic Council of Canada, 1990; OECD, 1983). According to theMinister of State [Youth] (1984), while all youth groups face job uncertainty anda high prospect of at least some unemployment, the problem of joblessness isparticularly grave for youth in the 17-22 year age range who leave schoolwithout participating in post-secondary education.Young persons are clearly over-represented in the ranks of theunemployed. The Canadian annual average unemployment rate for 15 to 24year-olds8in1989 was 11.3%, compared with a rate of 6.6% for those aged 25 andover (Statistics Canada, 1989a; 1989d).When educational attainment is introduced as a variable, a more detailedillustration of this association emerges, as depicted in Table 2:8 The unemployment rate is defined by Statistics Canada as the number of unemployed as apercentage of the entire labour force (employed plus unemployed).24Table 2.Unemployment Rates of Population 15 Years and Over byEducation and Sex, Canada and British Columbia,Annual Average 1989.CANADA BRITISH COLUMBIA9Male Female Total 15-24 25-44 Totalyears yearsTOTAL 7.3 7.9 7.5 11.3 7.2 9.10-8 years 10.9 11.4 11.1 23.2 13.1 16.99-13 years 8.6 9.2 8.9 12.7 8.6 10.3Some post-secondary 6.8 7.8 7.3 8.6 7.0 8.5Post-secondarydiploma/certificate 4.7 5.7 5.2 6.6 5.3 6.2University degree 3.4 4.2 3.7 5.9 3.8 4.9he Labour Force Annual Averages, 1989)Myles, Picot, and Wannell (1988) explain that the labour market for youngpeople has always been volatile. Adjustment processes in the labour marketamong industries or occupations, decreases in aggregate demand, anddemographic changes often disproportionately affect young people. Whileunemployment rates have declined considerably from 1981-89 period, Figure 3and Figure 4 demonstrate that those with the least education are most likely tochronically suffer the effects of unemployment.A breakdown by sex is not available for British Columbia.2535302512050YearFigure 3.Unemployment Rates of Population 15-24 Years and Over by Education, Canada AnnualAverages 1980-1989.3530251201050YearFigure 4.Unemployment Rates of Population 25-44 Years and Over by Education, Canada AnnualAverages 1980-1989.—.------— 0-8 years—D-———— 9-13 years—•— Some post-secondary—0-——--— P.S. cert./diplomaUniversity degreeS— O Occ cc cc cc cc cc cc cc cc cc—— 0-8 years—0---—-—— 9-13 years—.— Some post-secondary—0———— P.S. cert/diploma—A— University degreecc - cc O\\cc cc cc cc cc cc cc cc cc cc(The Labour Force Annual Averages, 1980-1989)26Pallas (1984) suggests that if educational attainment is considered as acontinuum, the most disadvantaged are those with the least education. Studentswho fail to complete high school are less employable than high school graduates,who in turn fare worse than those entering and completing university. Lack ofeducation has been shown to be a predictor of welfare recipiency, persistentpoverty, and chronic unemployment (Krein & Belier, 1988). When youth do findemployment at all, entry level jobs often prove to be dead ends, providing onlylimited work experience, little in the way of satisfaction or pay, and are seldomthe critical first rung on a career ladder (Akyeampong, 1989; Coleman & Husén1985; Gaskell & Lazerson, 1981; Watchel, 1987).Even within the ranks of the employed, Myles, Picot, and Wannell (1988)report a downward shift in wages in jobs held by younger workers. They state:in jobs held by 16-24 year olds, there was a net shift from higher to lower wage levelsof 21% in jobs held by workers with less than secondary school, 22.1% in the groupwith secondary school completed, and 17.2% in jobs held by post-secondarygraduates. (p.30)Educational credentials may not provide protection against the downward shiftin wages in jobs held by younger workers, but the experience of those with moreeducation is generally less severe.Higher economic returns to education were also more evident in the olderage groups. Myles, Picot, and Wannell report that in jobs held by 35-49 year olds,virtually all of the gains in wages were in jobs held by post-secondary graduates.They state that “in this group, the share of jobs in the top four wage levelsincreased by 7.1% and there was little net shift of any sort in jobs held by thosewith less than a post-secondary degree” (p.30). Employment difficultiesencountered by young school leavers can be profitably juxtaposed to the newlyemerging skill shortages. Cohen (1989) suggests that high unemployment rates27experienced by out-of-school youth could reflect a mismatch between laboursupply and demand. This mismatch is a result of available jobs that requirequalifications not possessed by those seeking employment. Unemploymentresulting from the mismatches of available persons and jobs is commonlyreferred to as “structural unemployment” (Gower, 1989, p.l5) One way ofassessing the prevalence of this type of unemployment is to examine statisticsprovided by the National Job Bank. Employers experiencing difficulties inrecruiting qualified workers may seek assistance from the federal governmentthrough the National Job Bank, an agency which registers the recruitment needsacross the country. In 1988, National Job Bank listings for British Columbiatotalled 2862 - an increase of 64% since 1983 (Jothen, 1989). Structuralunemployment, according to Gera and McMullen (1991) tends to be “relativelypermanent” (p.9).In British Columbia, growing skill shortages have become a major concern.Jothen (1989) reports that 34% of British Columbia members of the CanadianFederation of Independent Business identified skill shortages as a major concernat the end of 1988. Serious shortages are predicted in science and engineering-related occupations, nursing and other health care workers, air traffic controllers,computer specialists, specialized service workers, teachers and highly skilledtrades. Those individuals with the least education are precisely the group leastable to fill these positions.The problem of youth unemployment is not likely to disappear. Accordingto Watchel (1987), there has been a sense over the past few years that high levelsof youth unemployment are not a transient aberration, but a deep, enduringproblem. Coleman and Husén (1985) warn that most of the recent changes inwork institutions imply a increasingly arduous role for youth attempting toenter the full-time labour market, especially young unskilled or semi-skilled28workers, for ‘it is these jobs which, for a variety of reasons, are declining indeveloped countries, and these jobs which are unlikely to be revived” (p.5)There is mounting evidence to support the prediction that changing labourmarket requirements, as outlined in the next section, will further exacerbate analready problematic youth employment situation.Changing Labour Market RequirementsColeman and Husén (1985) indicate that the inevitable changes due to thechanging nature of the labour market will have grim consequences for poorlyprepared youth in developed countries. In the past, virtually anyone who waswilling to work, even those with low levels of education or limited skills, wereable to obtain steady, reasonably well-paid employment. At one time it waspossible for bright, highly motivated people with little in the way of educationalcredentials to be upwardly mobile in their chosen occupation. Today, however,as educational attainment surpasses a willingness to work as the principal jobentry level credential, the “career ladder has been truncated” (Radwanski, 1987,p.15) and those with limited education and few skills are likely to be severelylimited in their choices of employment and advancement.The Economic Council of Canada (1990) summarized the impact of thesefactors on today’s labour force:29The growth of services, along with the information explosion and theinternationalization of business activity, is fuelling the demand for an increasinglywell-educated and skilled work force. Canada’s future economic welfare will bedictated in no small measure by its capacity to develop human resources. The‘education and training’ imperative will also be compelling for individuals, sinceemployment experiences will be less and less favourable for those who have skilldeficiencies. In fact, our analysis suggests that the segmentation into the labourmarket into ‘good-job’ and ‘bad-job’ sectors is likely to raise considerable challengesfor policymakers. (p.18)The Economic Council of Canada (1990) predicts that as global competitionaccelerates, high cost countries such as Canada will be increasingly compelled torely on the excellence of their work force to provide a comparative advantage inthe global marketplace. As the volume of international trade increases, demandfor domestic low-skilled, entry-level labour will continue to decline in developedcountries. Goods and services requiring less skilled labour will be produced incountries with the lowest production costs and then be readily transported tomarkets located anywhere in the world. Youth will find themselves competingnot only with adult workers in their own society, but also with workers fromother countries who are paid at much lower levels (Coleman & Husén, 1985).Effective competition in an internationalized economy requires knowledge-intensive service and manufacturing activities employing an expert and flexiblework force. According to the Economic Council of Canada, all recentemployment growth has occurred in one of two quite distinct ‘growth poles’ -either highly skilled, well-compensated, and secure jobs, or nonstandard,unstable and relatively poorly paid jobs. While it is acknowledged that ‘skill’ is adifficult concept to measure, the Economic Council of Canada asserts that thenature and the level of skills required in the labour market are being transformedby a combination of three factors: growth of the service sector, technologicalinnovation, and changes in the way work is organized. Because of thistransformation, today’s employers are seeking individuals with qualities that30include ‘basic academic competence, creativity and initiative, analytical andproblem-solving abilities, adaptability, and communication and interpersonalskills” (p.13).Psacharopoulos (1986) points out that the pace of technological change maymove at an even more accelerated pace in the future, a pace that will ridicule anyattempts to either predict it or to adapt a school system to it. This would suggestthat rather than the acquisition of qualffications such as job-specific skill trainingand specialization in high technology which carry with them a “built-inobsolescence” (Watts, 1987, p.9), education in the general sense is required,resulting in the development of individuals who are adaptable to changingopportunities, motivated to continually seek new knowledge, and capable ofcritical thinking and decision making (Bowen, 1982; Department of the Secretaryof State of Canada, 1988; Province of British Columbia, 1988; Report of theProvincial Access Committee, 1988; Science Council of Canada, 1988; Watts,1987). Coleman and Husén (1985) refer to those who leave school with the“mandatory minimum” but without the requisite abilities and skills necessary tocope with the demands of the modern work place, as a “new underclass”. Forthis group, there is little chance of becoming meaningfully employed.It is widely acknowledged that Canada, along with other advancedindustrial countries, is undergoing a radical transformation from an industrialsociety to to a society characterized by economic globalization, a labour forceshifting from the goods-producing sector to the service sector, and the rapiddiffusion of technology into the work place. These interrelated factors, accordingto many, account for the transformation of the labour market as fundamental asthe earlier shift from the agrarian to the industrial eras (Economic Council ofCanada, 1990; Radwanski, 1987).31Others, as discussed in the next section, question the relationship amongeducation, skills, and work.Education and CredentialismThe view that increasing levels of education are necessary to contend withan increasingly complex society has generated substantial criticism. Collins(1979) asserts that there is little evidence to support the view that 1) the majorityof jobs in modern society require more sophisticated knowledge and skills thanin previous years and 2) that there is a relationship between formal educationand productivity. He alleges that schools are extremely ineffective institutionsfor the development of cognitive skills and that schooling “has more to do withteaching conventional standards of sociability and propriety than withinstrumental and cognitive skills” (Collins, 1979, p.19). Collins also maintainsthat the “myth of technocracy” is perpetuated by employers and educationalinstitutions who have vested interests in raising levels of educationalqualifications.According to Collins (1979), education has become a form of “culturalcurrency” (p.6O-62), which is used to purchase desirable occupations. Post-secondary education is perceived by students as a means to enter the powersystem, and it is the attainment of a credential rather than the acquisition ofknowledge that is desired (Aronowitz & Giroux, 1985; Collins, 1979). Dore (1976)argues that credentials become inflated with rapid educational expansion; thus,competition for desirable occupations then exerts pressure to increase thequantity of credentials required by employers. The resulting “credentialingsociety”, according to Collins, is irrational and wasteful, and is detrimental tominority groups in their struggle for dominance and prestige.32But as Aronowitz and Giroux (1985) point out, ‘credentials are the onlygame in town” (p.166). Credentials have become a rite of passage, an indicationthat a process of educational socialization has occurred. Arrow (1973) suggeststhat higher education acts as a ‘double filter” for the purchasers of labour, firstby selecting entrants, and second by passing or failing them. In this way, highereducation serves as a screening device by sorting individuals of differingabilities. Dore suggests that employers appear to be “unquestioning victims ofthe widespread myth that education improves people” (p.5) and by hiringsomeone with qualifications beyond the requirements of the position, employersbelieve that they are geffing more for their money. Credentials are recognized byemployers and by the larger society as constituting adequate preparation foroccupational status; therefore, credentials rather than knowledge ensure marketsurvival (Aronowitz & Giroux, 1985).Whether one favours a credentialist account or one of changing labourmarket requirements, it would appear that there is an inextricable relationshipbetween what one learns and what one is certified to have learned (Bidwell &Friedkin, 1988). Several recent studies demonstrate this relationship. Bills (1988)found that while approximately 80% of managers making hiring decisionsconsidered credentials to be an important determinant to their ultimate hiringdecision, they were deemed less important than indicators of job performance(e.g. recent work experience). He concludes that overall, credentials do serve toget people “through organizational gates and on organizational ladders” (p.58),but once in, managers use other more direct measures of performance. Shockey(1989), in a study on “mismatched”10 or overeducated workers, found thatworkers who were mismatched for their occupational positions were more10 Shockey defines workers as mismatched or overeducated “if their educational aftainment isgreater than one standard deviation above the mean education among workers in similaroccupations” (p.858).33successful at competing for better jobs and received greater returns to their post-secondary education than those who were correctly matched to their jobs.Hunter (1988) examined the changes in skill requirements of entry level jobs inCanada between 1930 and 1980, and demonstrated that at least for entry-leveljobs, variation in skill requirements across occupations does exist, and thateducation is clearly related to the skill requirements of those jobs. Given thefindings of these studies, it may be more prudent, as Bidwell and Friedkin (1988)suggest, “to regard learning and gaining credentials as tightly linkedmechanisms through which schooling affects employability” (p.454).Whether considered from the viewpoint of the market and nonmarketeffects of education, youth unemployment, changing market requirements, orcredentialism, it can be justifiably concluded that the transition from high schoolto post-high school destinations is indeed a critical juncture. Decisions made bystudents during this period in their lives will have an impact not only on theirown life chances, but also, as some continue to argue, the economic future ofCanada (Economic Council of Canada, 1990; Radwanski, 1987).There is, however, an intimate relationship between social equity and thedevelopment of human resources. As Watts (1988) concludes:policies ensuring wide accessibility to higher education, including its extension togroups not yet served, may be justified not only on grounds of social equity but alsoon the grounds that no nation can afford to lose the human talent that otherwisewould remain undeveloped. (p.5)This sentiment is reflected in the comments of Porter (1965), that “no society inthe modern period can afford to ignore the ability which lies in the lower socialstrata” (p.197) and Bowen (1982), that “the number of persons of all ages in oursociety who are educable and who would be benefited from higher education34vastly exceeds any past or present enrollment” (p.9). Equality of opportunity inrelation to post-secondary education is discussed in the next section.Post-secondary Education and Equality of OpportunityThe principle of equality of opportunity of access to post-secondaryeducation has been described as a major driving force behind the dramaticexpansion of education throughout the western world (Report of the StandingSenate Committee on National Finance, 1987). Growth of and accessibility to thepost-secondary system were based on social and economic changes and on thetheories of human capital and social justice. An equality of opportunityperspective was, and continues to be, founded on the notion that educationalbarriers not rooted in academic considerations, that is, those based on ascriptivecharacteristics or ‘accidents of birth’, are “wasteful of human talent and contraryto the broad social goals of improving educational opportunity” (Alexander,Holupka, & Pallas, 1987a, p.59). The existing objective espoused by the federaland provincial governments is to ensure that higher education is available on anequitable basis to all Canadians who are qualified and want to study(Department of the Secretary of State, 1988; Report of the Provincial AccessCommittee, 1988; Report of the Standing Senate Committee on National Finance,1987).The relationship between education and equality of opportunity isconsidered under the following headings: 1) non-participants in post-secondaryeducation and 2) participants and institutions.35Non-participants in Post-secondary EducationSeveral recent studies indicate that, despite the expansion and ostensibledemocratization of the Canadian post-secondary system, the existing objective ofequality of educational opportunity for all Canadians who are qualified and whowant to study is not being met (Alberta Advanced Education, 1984; Anisef, 1985;Fortin, 1987; Guppy, 1984). In 1982, the Honourable Bette Stephenson stated“while we have dramatically increased the number of students attending post-secondary institutions, access to post-secondary education remains far fromequal across all social and economic groups in Canada in many areas” (Councilof Ministers of Education, Canada, 1982, p.25O). The Report of the RoyalCommission on the Economic Union and Development Prospects of Canada(1983) found that the likelihood of university attendance of children whoseparents hold bachelors degrees is three times greater than children of parentswithout degrees, and that participation in post-secondary education of youngpeople from high-income families has always been greater than from low-income families. The Report of the British Columbia Provincial AccessCommittee (1988) acknowledges that opportunities for advanced education arenot equal for all people in all parts of the province. Although services to underrepresented groups have vastly improved over the past twenty-five years, thereport indicates that “it is unacceptable that significant groups should remainunder-represented for long in higher learning activities, unless by free choicerather than by lack of opportunity” (p.18).Skolnik’s definition of Type I accessibility provides a second way oflooking at participation:36Type I accessibility pertains to variation among individuals or groups with respect totheir chances of getting into post-secondary education. If the probability of gettinginto post-secondary education is the same for all individuals, then Type I accessibilityis maximized, whether that probability is high or low. (Skolnik (1984) cited in Anisef,1985, p.4)Table 3 highlights groups that have been identified in major (federal and BritishColumbia) reports on post-secondary participation over the past decade asunder-represented in the Canadian post-secondary system. Native Indians, thedisabled, and women are most frequently identified as under-represented in theCanadian post-secondary system. The four most recent reports, however, do notidentify the economically or socially disadvantaged as under-represented inpost-secondary education.Fortin (1987) comments that specified groups of non-participants “havenothing in common except that they do not fit into the segment of the populationthat has traditionally gone on to post-secondary education” (p.12). Is thisstatement tenable? If the answer is yes, what are the differences in thecharacteristics among the groups? Why do some individuals become nonparticipants in post-secondary education? If the way in which members of thevarious groups of non-participants make decisions regarding post-secondaryeducation remains unknown, how effective will policies be which are aimed at 1)increasing the overall transition rate and/or 2) reducing inequities by targetingspecific groups?Table3.GroupsIdentifiedasUnder-representedinCanadianPost-secondaryEducation.EconomicMinorityUnemployand/orOfficialmentNativeRemoteSociallyVisibleMaturePart-LanguageInsuranceIndiansCommunitiesDisabledDisadvantagedWomenMinoritiesImmigrantsStudentstimeGroupRecipientsMinistryofAdvancedEducation,JobTraining, andTechnologyfor theOpenCollegePlanningCouncil (Jothen,•1-a1989)Report oftheProvincialAccessCommittee(1988)ortin(1987)Sa4:TheCommissionontheFutureDevelopment ofUniversitiesofOntario(1984)•aatephenson1982)•tDefinedasunderemployedwomenorwomenre-enteringtheworkforce.4:Fortindescribeswomenasbothwinnersand‘losersinpost-secondaryparticipationoftheStandingSenateCommitteeonNationalFinance(1987)38Participants and InstitutionsLess apparent are the disparities in characteristics among those who doparticipate in the various institutions of post-secondary education. AlthoughGuppys (1984) study revealed reduced socioeconomic disparities amongparticipants in post-secondary education, he concluded that this reduction waslargely due to the expansion of the non-university sector of higher education. Arecent joint study by Statistics Canada and the Department of the Secretary ofState (1987) demonstrates that 1) undergraduate levels of education continue tobe dominated by children of parents who fall in upper-middle and upper classcategories, 2) the rate of over-representation is not rapidly decreasing, and 3)parents of community college students tend to have lower levels of education(cited in Fortin, 1987). Guppy and Pendakur (1989) found that the elimination ofone ascriptive characteristic - gender - which in the past has been related to post-secondary participation, resulted in the exacerbation of another form ofascription - family origin. That is, women participating in post-secondaryeducation in 1983/84 were more likely than males to have beller educatedparents. It appears, as Alexander, Pallas and Holupka (198Th) note, that‘traditional patterns of educational stratification are highly resilient” (p.181).It seems reasonable, at this point, to question whether, in terms of lifechances, access to a community college is equal to access to university.Viewpoints related to this question are discussed under the headings 1) thepluralistic nature of Canadian post-secondary education, and 2) transfer fromcollege to university.39The Pluralistic Nature of Canadian Post-secondary Education - Reality or Myth?In the Report of the Committee to Examine Participation Trends of AlbertaPost-Secondary Students (Alberta Advanced Education, 1984), it is asserted thatwithin a differentiated system of post-secondary education, equality ofopportunity of access should mean that different opportunities are available todifferent students; that is, the post-secondary system should offer different typesand levels of education with varying starting points and outcomes. The reportstates:this orientation presupposes that Canadian society is pluralistic and heterogeneousand that its citizens have a diversity of learning needs. A pluralistic society is wellserved by a pluralistic education system. There appears to be no intrinsic merit inseeking a singular pattern - namely that of university attendance. In fact, this patternof thought could prove detrimental to both potential students and the country’seconomic development. (Alberta Advanced Education, 1984, p.20)The development of the community college system in British Columbia wasdesigned to reflect the needs of a pluralistic and heterogeneous population, for,as Macdonald (1962) emphasized, “to insist that each [institution] .. . train youngmen and women in the same way is to confuse the aims and methods ofeducation” (p.5z1). The introduction of the community college system into thehigher education system in Canada was intended as a democratizing strategy,designed to reflect the needs of a pluralistic and heterogeneous population byproviding alternate types and levels of education for those without the requisiteability to attend university. Community colleges have also enabled those fromless privileged backgrounds to pursue post-secondary studies by offeringuniversity-equivalent courses (as well as vocational, technical, career, academicupgrading and continuing education courses), lower tuition fees, flexibleadmission requirements, and programs located within commuting distance40(Alberta Advanced Education, 1984; Dennison & Gallagher, 1986; Fortin, 1987).Beinder (1983) argues that the community college system in British Columbiawas “a social invention, whole and legitimate in its own right, designed to solvea particular kind of problem created by a highly complex society’ (p.1).Advocates of the community college system claim that these colleges contributeto society by providing the technical skills needed by an increasingly complexeconomy. Community colleges were virtually nonexistent in 196011; by 1988/89these institutions enrolled 317,000 full-time students.In terms of life chances, however, critics allege that attendance at acommunity college is far from democratizing (Karabel, 1986; Pincus, 1986).Scholars who subscribe to the class-reproduction school describe communitycolleges not “as new avenues of opportunity for the previously disenfranchised”(Dennison & Gallagher, 1986, p.162), but largely as dumping grounds forminority and disadvantaged youngsters where aspirations are “cooled out”(Clark, 1960) and dead-end degrees with little economic or social value are doledout. In this way, it is argued that community colleges contribute to thereproduction of the existing structure of inequality by training and socializingindividuals for work in capitalist enterprises (Bowles & Gintes, 1976; Karabel,1986). Karabel (1986) indicates that studies confirming the location of communitycolleges on the lowest track in the interinstitutional stratification system of post-secondary education have “now been replicated so many times that it is nolonger controversial” (p.l6) He observes:In 1960, Lethbridge Community College was the only public community college in existencein Canada (Dennison et al.,1975).41far from embodying the democratization of higher education and a redistribution ofopportunity in the wider society, the expansion of the community college insteadheralded the arrival in higher education of a form of class-linked tracking that servedto reproduce existing social relations. To be sure, some individuals who wouldotherwise have been excluded from higher education have used the communitycollege as a platform for upward mobility; yet, . the overall impact of thecommunity college has been to accentuate rather than reduce prevailing patterns ofsocial and class inequality (Karabel, 1986, p.18)Anisef (1985) argues that what has been referred to in Canada as a ‘pluralisticeducation system’ camouflages the hierarchical relationships that exist amongpost-secondary institutions and serves to obscure and mystify the reality of thechoice situation for students when they are choosing a particular post-secondaryinstitution. Coleman and Husén (1985) detect a trend in OECD countries, that ofan emergence of a new stratification in an era of educational egalitarianism.Has a dual higher educational system evolved in Canada, as Guppy (1984)suggests, where community colleges have become a major post-secondaryalternative for lower socioeconomic groups? Anisef (1985) poses the followingquestions: “What sorts of students enrol in universities? In colleges or technicalinstitutes? What is the impact on students’ ‘life chances’ (e.g. career choices andsatisfaction) of attending university in contrast to other forms of post-secondaryeducation?” (p.l65) Karabel (1986) asks: “What are the effects of attending acommunity college on individual life chances in the labor market, as comparedto not attending a community college at all?” (p.25).Havernan and Wolfe (1984) note that, from an economic perspective,estimations of the contribution of education to economic well-being must reflectthe heterogeneity of the educational system because various incrementalprovisions of educational services yield different impacts. In an analysis usingdata from the National Longitudinal Study of 1972 high school graduates,Breneman and Nelson (1981) found that although attendance at a communitycollege increased former students’ likelihood of subsequent employment relative42to those who had achieved only high school graduation, it did not increase theiroccupational status or their wages. Employment and income differentials ofcommunity college and university graduates are demonstrated earlier in thischapter in Tables 1 and 2, and Figures 3 and 4. Breneman and Nelson concluded:“Since occupational status is generally considered to be highly correlated withadult earnings, the positive relationship between attending university andoccupational status bodes ill for future earnings for students choosing acommunity college instead of a university” (p.72).Transfer from College to UniversityNumerous studies reveal that transfer rates from community colleges touniversities are low and that the probability of degree completion is generallysuperior when post-secondary education is commenced in a degree-grantinginstitution (Alba & Lavin, 1981; Anderson, 1984; Astin, 1982; Medsker & Tillery,1971; Velez, 1985). Karabel (1986) indicates that students who are similar interms of socioeconomic background, academic ability, educational aspirations,and other relevant individual characteristics are more likely to earn a bachelor’sdegree if they initially commence their studies in four-year institutions. In astudy on the distributive effects of public two-year college availability, Tinto(1975b) found that the presence of a public two-year college in a communityacted as a redistributive mechanism and did less to increase rates of collegeattendance than to alter the type of post-secondary institution attended. Hefound that the degree to which the substitution of a public two-year college for afour-year college occurred tended to be inversely related to socioeconomic statusand not measured ability. He concludes that “for persons of the two highestability quarters, in particular, the lower the social-status background the lower43the likelihood that individuals living in a community with a local public two-year college would attend nonlocal public four-year institutions” (p.271).Commenting on Tinto’s findings, Karabel (1986) states that:to the extent that this substitution effect diverts individuals from nonprivilegedbackgrounds away from four-year institutions, the expansion of community collegesmay paradoxically lead to an increase in inequality of educational opportunityattendance at a two-year rather than four-year institution has a negative independenteffect on the likelihood of completing a bachelor’s degree. (p.16)Brint and Karabel (1989) maintain that this ‘diversion effect’ that accompaniedthe ‘democratization effect’ of community colleges was an intended outcome,“for part of the junior colleges’ raison d’être was to channel students away frommore selective and expensive four-year colleges and universities” (p.9l)Dougherty (1987) offers a model to explain how community collegeentrance hinders the educational attainment of baccalaureate aspirants. Hedescribes three key processes which act as a funnel-like structure to militateagainst transfer to degree-granting institutions and subsequent degreecompletion: attrition before transfer, difficulty in the transfer process, andattrition after transfer. First, attrition during the first two years of communitycolleges is associated with lack of residential facilities, low academic selectivityand prestige, and lower expectations of instructors. Second, difficulty in thetransfer process is related to the vocational orientation of community colleges,the need to move to a new institution, and difficulty in gaining admission to andobtaining financial aid at four-year institutions. Third, attrition after transfer isassociated with credit loss suffered in the transfer process, drastic declines ingrades, lack of financial aid, and problems becoming socially integrated into thenew institution. Together, Dougherty concludes, these institutional effects44prevent large numbers of students who begin in community colleges fromsuccessfully attaining the goal of completing a baccalaureate.Anderson (1981) maintains that where one commences post-secondarystudies may lead to differences in future occupational status. In her longitudinalstudy of persistence in higher education, she concluded that students enteringtwo-year institutions, despite higher academic performance, were less likely topersist in higher education than their peers who commenced at four-yearinstitutions, and that the attrition rate was particularly high between the secondand third year.Of the Grade 12 graduates12 in British Columbia who entered the post-secondary system in the 1985/86 year, 64% entered community colleges and 36%directly entered universities13 (Report of the Standing Senate Committee onNational Finance, 1987). In 1985, the estimated total transfer rates from BritishColumbia community colleges to universities ranged from 14 to 51% with amedian rate of 29% (Ministry of Advanced Education and Job Training, 1987). Itis estimated that the degree completion rates of students transferring fromcollege to university range from 8 to 32% compared with a degree completionrate of 29 to 56% for those students directly entering university (p.lO). The B.C.Council on Admissions and Transfer (1989) reports that second year enrolmentin the college and institute sector as a percentage of first year decreased to 20%in 1987, a decrease which has affected both university transfer and career12 Of this total cohort, 28.5% continued on to a community college, and 16.7% entered auniversity.13 The Report of the Standing Committee on National Finance (1987) reports that all of theprovinces, British Columbia has the lowest percentage of students entering directly intouniversity. It could be argued that because of the nature of post-secondary education in BritishColumbia, many students have chosen to complete one or two years of university-equivalentcourses at community colleges, thus lowering the numbers entering university. Alberta,however, with a similar post-secondary structure, reports a transition rate of 26.9% for studentsentering directly into university. While Alberta has the second lowest transition rate touniversity, it is much closer than British Columbia to the national average of 29.3%.45programs. Between 1981 and 1987 the percentage had been stable at 22% (p.l).The Ministry of Advanced Education and Job Training (1987) concludes thaton average less than one in four full-time students who begin college academicprograms can expect to end up with a first degree. Looking at it another way, thosewho begin studies at university have twice the chance of completion as those whobegin college. (p.11)The Report of the British Columbia Provincial Access Committee (1988) indicatesthat quotas are being placed on both the number of students admitted touniversities and the number of transfer students accepted from colleges. Thus,those who are currently over-represented in the community college system inBritish Columbia are the most likely to be affected by these policies. Karabel(1986) laments:from the perspective of equality of opportunity, the implications of this pattern ofoverrepresentation- one in which individuals from working-class and minoritybackgrounds tend to be concentrated in the very institutions that offer them the leastchance of obtaining a bachelor’s degree - are sobering. (p.17)Coleman and Husén (1985) comment on the paradoxical nature of educationalopportunity today. They note that there are more available places in post-secondary education than any other time in history; yet, as participation ratesclimb there is a concomitant escalation of competition for these places, and inparticular, university places.Alexander, Holupka, and Pallas (1987b) suggest that it is reasonable toconclude, in terms of life chances, that the type of post-secondary institution oneattends may rival in importance with whether one attends at all. Therefore, itshould be of critical importance whether one’s point of entry to higher educationis a community college or a university.46SummaryThis chapter has examined the educational and societal context withinwhich decisions regarding post-high school destinations occur. The structure ofthe educational system was described, the problem of transition from highschool to post-high school destinations was discussed from an economic andequality of opportunity perspective, and the need for an exploration of thosedecisions made during the period of transition from high school has beenhighlighted. In particular, I have strived to illustrate that: 1) participation in post-secondary education does make a difference in terms of future labour marketexperience and quality of life, and 2) the type of post-secondary institutioninitially attended may affect one’s future ‘life chances’. The significance ofwhether and where an individual attends post-secondary education can bejustified from the viewpoint of unemployment and education, the marketed andnonmarketed effects of education, changing market requirements, orcredentialism.Given what is known about the benefits of participating in post-secondaryeducation, the observation that numerous high school graduates do not go on topost-secondary education, and existence of persistent disparities between groupsof participants and non-participants, further investigation is warranted. That is, itis worth investigating why one “would not want a visa to the bridge-head zone, whenthe alternative is so starkly different?” (Dore, 1976).Chapter 3REVIEW OF THE LITERATURE AND THEORETICAL PERSPECTIVESThe purpose of this chapter is to examine the literature on participation inhigher education as it relates to educational choice. The chapter begins with areview of two dominant bodies of literature on educational attainment andparticipation: the social stratification perspective, and research on statusattainment. Following a critical review of the contributions provided by thesebodies of literature to the research questions of this study, the foundation for analternate model, based primarily on Härnqvists (1978) conceptualization of thedeterminants of educational choice is proposed.In the second section of this chapter, the literature on decision makingprocesses is considered. This section draws primarily on rational choice theoryas developed by Elster (1986, 1989a, 1989b), and a Theory of Practice as depictedby Bourdieu (1977c, 1979, 1986, 1990b).Factors Affecting ParticipationAs indicated in Chapter 1, there are many studies on the factors affectingparticipation in post-secondary education. Of particular interest in this study aretwo approaches, as distinguished by Bidwell and Friedkin (1988) to theparticipation question - the social stratification perspective and statusattainment research.4748Social Stratification PerspectiveOne predominant approach to the analysis of participation in highereducation in the Canadian literature is the adoption of a social stratificationperspective. This approach seeks to explore ‘the degree to which individualseducational attainment is independent of ascriptive characteristics” (Bidwell &Friedkin, 1988, p.453). These ascriptive characteristics, or structural inequalities,are identified as socioeconomic status (most commonly parents’ education,occupation, and income), gender, ethnicity, and geographic location. Studieshave focussed on a single characteristic as the independent variable, for examplethe relationship between gender and participation (Gilbert & Guppy, 1988;Guppy, Vellutini, & Balson, 1987) or socioeconomic status (Guppy, Mikicich, &Pendakur, 1984) or a combination of ascriptive characteristics, such as therelationship of gender and parental education on choice of institution and fieldof study (Guppy & Pendakur, 1989), participation trends among groups basedon gender, socioeconomic background, and rural/urban residency (AlbertaAdvanced Education, 1984; Anisef, Okihiro, and James, 1982), and therelationship between city size and region, family background, and ethnoreligous background on educational transition (Pineo & Goyder, 1988).Several important findings have been revealed in these studies. First,those who enter the post-secondary system historically have and continue tocome from higher socioeconomic origins (Anisef et al., 1982; Pineo & Goyder,1988). Second, women are both “winners” and “losers” in the battle againstascription. That is, enrolment of women in undergraduate programs is nowequal with that of men (Bellamy & Guppy, 1991; Gilbert & Guppy, 1988; Selleck& Breslauer, 1989), but they continue to be underrepresented in certaindisciplines (e.g. engineering) and in graduate studies, and women with lower49socioeconomic backgrounds are overrepresented in the community colleges andunderrepresented in universities (Fortin, 1987; Gaskell, 1981).While studies such as these have greatly contributed to theunderstanding of participation in higher education of various groups inCanadian society by highlighting the existence, persistence, or diminishment ofcertain structural inequalities, they provide little insight into lww individualsmake decisions about participation in post-secondary education and theprocesses behind these decisions.This approach is limited in the following ways. First, as Bidwell andFriedkin (1988) explain, because this perspective only considers factorsexogenous to schooling, characteristics of the individual, institutional aspects ofeducational status allocation, and internal organization and processes ofeducational institutions are not accounted for. Second, this perspective does notallow for a discussion of the processes behind these disparities (Boyd et al.,1981). In their study on the relationship of socioeconomic status on participationin higher education, Guppy, Mikicich, and Pendakur (1984) concluded:we have provided an overall portrait of disparities but we have not endeavoured topinpoint the effects of social origin on each of the many transitions embedded in theeducational system. That is, we have noted that large socioeconomic disparities existat the post-secondary level but we have not examined exactly how this has comeabout. For example, students from blue-collar backgrounds may beunderrepresented at university as a consequence of their failure to complete highschool, their enrolment in high school programs which prevent immediate transitionto university, their decision not to pursue a university education even thougheligible, or some combination of these and other factors. (p.329)Several authors have commented that observed phenomena, such as thecorrelation between socioeconomic status and participation in post-secondaryeducation, are not wholly consistent and do not constitute an explanation (Lane,1972; Giddens, 1984; Porter, Porter, and Blishen, 1982). While it is not unusual to50conclude that a measure such as socioeconomic status is related to theprobability that an individual will continue on to post-secondary education, theusefulness of this type of a measure is incomplete. It remains unclear as to howthese correlations come about. As Lane (1972) observes:even if the correlation were perfect, which it is not, we would still need to seek outand specify the mechanism or mechanisms whereby... [factors operate] to constrainthe educational decisions of its offspring. (p.255)Härnqvist (1978) asserts that research efforts of this type have likely providedmore knowledge about stable and fairly resistant factors behind educationalchoice than about factors that influence change.A second approach to participation, status attainment research, addressessome of the limitations encountered by a social stratification approach.Status Attainment ResearchThe seminal work of Duncan and Hodge (1963) and Blau and Duncan(1967) generated a series of studies which now fall under the rubric of statusattainment models. The original path model of the occupational statusattainment presented by Blau and Duncan (1967) was developed to address twoquestions: How and to what degree do the circumstances of birth conditionsubsequent status? and how does status attained (whether by ascription or byachievement) at one stage of the life cycle affect the prospects for a subsequentstage” (Blau & Duncan, 1967, p.l64) Using an analytical framework whichconsisted of two antecedent structural variables (father’s education and father’soccupation), two intervening behavioural variables (respondents education and51respondent’s first job), and one dependent variable (respondent’s occupationallevel), they attempted to model social mobility. As one part of this work, theydemonstrated the existence of a strong correlation between father’s occupationalstanding and son’s completed years of schooling.The model was subsequently modified by the addition of psychologicaland social-psychological variables which included mental ability, academicperformance, the influence of significant others, and educational andoccupational aspirations (Sewell, Hailer, & Ohlendorf, 1970; Sewell, Hailer, &Portes, 1969). This ameliorated version, known as the ‘Wisconsin’ model ofstatus transmission and status attainment, demonstrated that the effects offamily social status on educational and occupational attainment were mediatedsubstantially by social-psychological variables such as significant others’influence and one’s own educational and occupational aspirations (Jencks,Crouse, & Mueser, 1983; Looker & Pineo, 1983; Sewell, Hailer, & Ohlendorf,1970; Sewell, Hailer, & Portes, 1969; Sewell & Hauser, 1975).Since educational attainment was demonstrated to be a powerfulpredictor of subsequent occupational attainment Gencks, Crouse, & Mueser,1983; Kerckhoff, 1976; Sewell, Hailer, & Ohlendorf, 1970), one group ofresearchers have focused on educational attainment as the dependent variable(Alexander & Cook, 1982; Alexander, Cook, & McDill, 1978; Alexander &McDill, 1976; Sewell & Hauser, 1975). This model was further modified bytreating level of educational aspirations, level of occupational aspirations,and/or educational expectations as the dependent variable(s) (Gilbert, 1977;Gilbert and McRoberts, 1977; Porter, Porter, and Blishen, et al. 1982). Bidwelland Friedkin (1988) provide a concise summary of the range of variables used inthese studies:52Criterion variables include intended or completed years of schooling, achievement testscores, or such measures of educational aspirations as plans for college attendance.Exogenous variables are those of status origins and variously include parents’occupation, education, and income; material and cultural aspects of the home; raceand ethnicity; and gender. The intervening variables variously include academicability and achievement, the students academic and occupational goals, significantothers influence, and school organizational variables. (p.456)Like the findings of studies which use occupational attainment as the dependentvariable, studies of educational attainment have demonstrated that whilesignificant coefficients have been obtained in regressions of educationalattainment on the status origins of students, these effects are mediated by theintervening variables contained in the model. These variables, in diminishingimportance, include academic ability, prior academic performance, educationalaspirations, parental and peer social support, and track placement (Bidwell &Friedkin, 1988).The ‘Wisconsin’ model of status attainment has been described as one ofthe most significant and influential advances in recent sociological research(Kerckhoff, 1976; Marjoribanks, Secombe, & Srnolicz, 1987). Coser (1975)explains that because of the complexity of these models, it is possible to assessthe contributions of social inheritance and individual effort in the statusattainment process.Yet, one major criticism of status attainment models persists. While therange of variables which have been included in various models is extensive,they are comprised almost exclusively of measures of individual characteristics,and thus are interpreted as “individual resources or liabilities” which contributeto the individual attainment process (Campbell, 1983; Coser, 1975; Kerckhoff,1976; Horan, 1978). Extraindividual or structural constraints, such as classbarriers or between-group differences in opportunity structures, have beengiven minimal attention. Coser (1975) remarks that “there is no concern here53with the ways in which differential class power and social advantage operate inpredictable and routine ways, through specifiable social interactions betweenclasses or interest groups, to give shape to determine social structures and tocreate differential life chances11 (p.694).Kerckhoff (1976) explains that the theoretical approach used in theinterpretation of social attainment models is that of social interactionism.According to this perspective, the socialization process is used to elucidate theconnection between status origin and attainment. He continues:significant others are seen as having an influence on the goals of the young person,and these goals are viewed as instrumental in the attainment process. The theoryanticipates that the encouragement by significant others will vary according to thesocial position and demonstrated ability of the child, and that this encouragementwill affect the level to which he aspires. The family and school are seen as theinstitutional settings of this socialization process, and the significant others includeparents, teachers, and peers. (p.368)In an attempt to explain educational and occupational attainment, the focus of asocialization model is on the individual and her or his evolving characteristics. Itis assumed that the agent travels unconstrained through the social system; thus,a persons attainments are determined by what he or she chooses to do and howwell he or she does it (Kerckhoff, 1976). This perspective, Coser (1975) adds, isrooted in the prevailing American ideology of individual achievement.Kerckhoff suggests that an alternate view, which he calls the ‘allocationmodel” of status attainment, can be used to interpret the findings generated bystatus attainment models. In contrast to the socialization model, the locus ofanalysis in an allocation model shifts to an examination of the “mechanisms andcriteria of control of the individual by social agencies” (p.369). The individual, inan allocation model, is viewed as relatively constrained by the social structure,54and her or his attainments are determined by “what he is permitted to do”(Kerckhoff, 1976, p.369). Kerckhoff elaborates:[An allocation model] emphasizes the salience of societal forces which identify,select, process, classify, and assign individuals according to externally imposedcriteria. Rather than differential attainment as being seen as due to variations inlearned motives and skills, as in the socialization model, an allocation model viewsattainment as due to the application of structural limitations and selection criteria.(p.369)Kerckhoff asserts that constraints and limitations exist throughout theattainment process, and are imposed, in the form of providing or withholdingopportunities, by agents in institutional settings.While structural constraints and selection criteria are absent from moststatus attainment models, they have not escaped investigation. Theseinvestigations include the relationship between socioeconomic origins andenrollment in educational tracks (Gaskell, 1985, 1991; Heyns, 1974; Rosenbaum,1976; Vanfossen, Jones, & Spade, 1987), access to school personnel and resources(Anyon, 1981; Orfield & Paul, 1987), and formal and informal track placement(Lee & Eckstrorn, 1987; Page & Valli, 1990). Other studies demonstrate therelationship between track placement and self-direction (Miller, Kohn, &Schooler, 1986), cognitive development (Alexander & Pallas, 1984; Rosenbaum,1976), and educational and occupational aspirations, academic achievement, andpost-secondary participation (Vanfossen, Jones, & Spade, 1987). In general, thesestudies reveal how various components of school life, such as the socialorganization of education and the hidden curriculum, contribute to socialreproduction.Bidwell and Friedkin (1988) conclude that despite the consistent findingsof the status attainment literature that reinforce the notion that individualcharacteristics of students, rather than differential access to educational55resources, are primarily responsible for individual differences in educational lifechances, “it is hard to accept the conclusion that school resources or socialorganization have only minor effects on academic attainment (p.4S6)” Kerckhoff(1976) suggests that the inclusion of measures of the allocation process to currentmodels of status attainment, based on a socialization perspective, wouldincrease the overall power of the models by explaining the relationship betweenorigin and attainment left unexplained in these models. He asserts:the kinds of variables needed can be devised only if we keep before us the idea thatschool as an institution is more than a fixed obstacle course through which studentswith varying levels of skill and motivation are permitted to run. If we recognize theinstitutional necessity for teachers and other officials to differentiate among studentsand to attempt to provide the most suitable kinds of educational experiences todifferent kinds of students, we immediately face the problem of defining the bases ofdifferentiation and the characteristics of the varying kinds of educationalexperiences. (Kerckhoff, 1976, p.377)He maintains that it is impossible to fully differentiate a socialization model andan allocation model, since each perspective provides its own account of how thesocial environment influences the individual actor by highlighting differentkinds of phenomena. Thus, each contributes a unique theoretical interpretationof the same observations.Various models of educational choice have been proposed which claim toaddress both the process (Litten, 1982) and the outcomes of post-secondaryselection (Chapman, 1981). However, these models tend to focus primarily onthe “college oriented” student; that is, those students already committed to postsecondary participation (see Jackson, 1982). Although most of these modelsidentify three stages in the choice process -- predisposition, search, and choice(Hossler, Braxton, & Coopersmith, 1989) it is often assumed in college choicemodels that all students of the traditional college-age group are potential clientsof the post-secondary system. That is, although the predisposition stage is56acknowledged by these models, the emphasis tends to be on which institution astudent chooses, rather than whether one attends and, if so, which type ofinstitution within the hierarchy of post-secondary institutions is chosen.Härnqvist (1978) offers an approach that provides a foundation for theanalysis of educational choice by integrating notions of both socialization andallocation. As such, he concentrates primarily on the predisposition stage of theeducational choice process.Determinants of Educational ChoiceThe work of Härnqvist (1978) provides a comprehensive approach forexploring the relationship between the factors affecting participation andindividual responses to these factors. Grounding his analytical framework in thefindings of a myriad of empirical studies, Härnqvist identifies educationalchoice as the dependent variable, then recasts the factors which are commonlyidentified as influencing participation into ‘determinants of educational choice”.He adopts a distinction originally formulated by Blau, Gustad, Jessor, Parnesand Wilcock (1956), and proposes that entry into the post-compulsory system ofeducation is dependent on both the individual and institutional determinants. Inthe next section, each of these types of determinants, as outlined in Figure 5, isconsidered. -57Individual Determinants of Educational Choice1. Student Characteristics- sex- intellectual abilities- educational achievement- interests- aspirations2. Personal Environment- family background- peer group- school environmentInstitutional Determinants of Educational Choice1. Educational Systema) conditions antecedent to choice- curriculum emphasis- terminal vs. transfer programs- differentiation system- guidance organizationb) conditions anticipated in the choice situation- admission and selection rules- geographic availability- study financec) predicted structural changes in education2. Society Outside the Educational Systema) Demographic Factorsb) Occupation and the Economyc) Social and Cultural ConditionsFigiLre 5: 5[ämqvLct& etenninants ofEt1ucatioiwfC1wice58Individual determinants of educational choiceAccording to Härnqvist, “the process leading up to choice is a dynamicrelationship between the individual and his environment where cause and effectare hard to isolate from the network of continuous interaction” (p.32). He assertsthat the majority of work on educational choice has been done by trait factortheorists (Holland, 1966, 1973; Super, 1957; Super & Crites, 1962) who viewchoices as related to stable characteristics of the individual. They do not,however, provide an explanation of the intermediate processes, that is, thevariables that intervene between the attributes of the individual and the finalchoice. Härnqvist opines that the most interesting developments will arise fromattempts to “weigh individual attributes against other characteristics of theindividual and his situation” (p32).According to Härnqvist, the relevant individual determinants are: 1)characteristics of the individual, and 2) characteristics of the student’s personalenvironment. Characteristics of the individual include sex, intelligence,educational achievement, interests, and aspirations. Characteristics of thestudents’ personal environment include family background, peer group, and theclimate and student composition of the school.Institutional determinants of educational choiceHärnqvist points out that while institutional determinants of educationalchoice appear to be of considerable importance, empirical evidence ofeducational choice in relation to institutional or structural characteristics isscarce and less complete than for individual determinants.59Härnqvist considers institutional determinants of educational choiceunder two headings: 1) characteristics of the educational system itself, and 2)society outside the educational system. Characteristics of the educational systemitself are categorized into: 1) conditions antecedent to choice, 2) conditionsanticipated in the choice situation, and 3) predicted structural changes ineducation. Conditions antecedent to choice refer to ‘factors which operate in theschool to which the student belongs when he makes his plans for the next stage”(p.55). Included under conditions antecedent to choice are curriculum emphasis,terminal vs. transfer programs, differentiation system, and guidanceorganization. Conditions anticipated in the choice situation, which characterizethe stage which the individual is about to enter, are admission and selectionrules, geographic availability, and study finance at the stage of decision.Included under society outside the educational system are demographic factors,occupation and the economy, and social and cultural conditions.This schema captures a range of psychological, sociological, andeconomic factors, that, as Blau et a!. (1956) suggest, are necessary in thedevelopment of an inclusive framework. As such, it includes indicators of thesocialization and the allocation process in educational attainment, as proposedby Kerckhoff (1976).Blau et al. (1956) and Härnqvist (1978) maintain that in order todemonstrate how earlier decisions limit or extend the range of future choices, asystematic analysis of a series of successive choice periods is required. Härnqvistasserts that the importance of early and distant decisions may be greater thanthose that immediately precede what appears to be the educational choice. Headds, however, that while more is known about distant determinants than about60immediate determinants, distant determinants are relevant “only to the extentthat they in turn influence immediate determinants” (p.16)Given one’s decision regarding post-high school destination, Harnqvist’sframework allows for the exploration of how each individuals’ decision makingprocesses have been influenced or shaped by individual and institutionaldeterminants, and what decisions individuals make in response to these forces.Determinants, as enabling and constraining forces may also be investigated. Therelative importance and interrelationships of personal attributes, students’ use ofeducational resources, and formal and informal organization on the secondaryand post-secondary systems of education on educational choice, as suggested byBidwell and Friedkin (1988), may also be assessed. Differences among groups ofnon-participants and participants in colleges, universities and other institutionsmay be revealed by analyzing the differential impact of the determinants onmembers of these groups14.Employment of Härnqvist’s framework to analyse the choices thatindividuals make will illuminate what relationships exist. However, ademonstration of the relationships among a set of relevant individual andinstitutional variables, or macro-processes, will not reveal how and why certain14 This model, does not, of course, take into account all of the variables that have beenconsidered in previous work on educational and participation and attainment. Some of thevariables not included are: birth order and family size (Blake,1981; Lindert,1977; O’Neill,1981;Porter, Porter, & Blishen,1982), the influence of single parent families (Crysdale,1975), religion(Porter, Porter, & Blishen,1982), self-concept (Gilbert, 1977). However, as Allison (1971) explains:in attempting to explain a particular event, the analyst cannot simply describe thefull scale of the world leading up to that event. The logic of explanation requires thathe single out relevant, important determinants of the occurrence. Moreover, as thelogic of prediction underscores, he must summarize the various factors as they bearon the occurrence. Conceptual models not only fix the mesh of the nets that theanalyst drags through the material in order to explain a particular action; they alsodirect him to cast his nets in select ponds, at certain depths, in order to catch the fishhe is after. (Allison,1971, p.4)This model is an attempt to accomplish precisely what Allison suggests - to capture the relevant,important determinants of educational choice.61mechanisms influence choice. As several authors have commented, despite thepreoccupation by researchers on the effect of social origin on educational andoccupational outcomes, there has been little progress in unravelling how theserelationships are created and reproduced (Bielby, 1981; Knorr-Cetina & Cicourel,1981; Lamont & Lareau, 1988; Lareau, 1987).Campbell (1983) maintains that the really interesting and difficultquestions in stratification research, such as “Why is there an unequaldistribution of attainment? In a society which values meritocratic selection, whyare parents so easily able to pass on status to their children?”, remainunaddressed (p.59). While previous studies have demonstrated that an ‘upper-class’ child has a much greater chance of reaching higher education than onefrom a working-class’ background, not all upper-class students go to university,nor are all working-class students non-participants (Keller & Zavalloni, 1964;Lane, 1972). It continues to remain as difficult to explain why ‘working classkids’ let themselves get working class jobs (Willis, 1977), as it is to clarify whyothers escape the social reproductive forces and destinations predicted by theirascribed status (Gambetta, 1987). Härnqvist (1978), commenting on our limitedknowledge of these mechanisms, motives or reasons, states:how this choice is made is largely unknown and cannot be inferred from the morebasic individual characteristics that have dominated the research so far. Neither doesit seem possible to approach this problem with the same tools as have been used formeasuring the influence of individuals, mainly correlational techniques of differentkinds. More important is the close observation of individual decision sequences andthe construction of decision models that can be tested in individual cases. . . . Alongwith more objective variables the individual’s motives and perception of the choicesituation are worth studying. (p.112)Others have suggested that in order to explain the relationship betweeninteraction and structure, both micro and macro levels of analysis are required(Knorr-Cetina, 1981; Larnont & Lareau, 1988). In the next section, theoretical62perspectives for exploring the micro-processes of educational choice areconsidered.Post-high School Destination and Educational ChoiceRegardless of one’s family background, geographic location, educationalachievement, and the other variables identified in the model presented in thefirst section of this chapter, every graduating high school student reaches ajuncture in her or his life path. At this juncture, a route must be taken -- either tocontinue to post-secondary education, or to leave the educational system.Having identified the relevant determinants of educational choice, a secondquestion may now be considered: How does an individual make this decision?Or, to reframe the question in light of Härnqvist’s work, how do individuals makedecisions about post-high school destinations in relation to the individual andinstitutional determinants ofeducational choice?Gambetta (1982, 1987) posed a similar question and applied it toeducational choice. Setting out to determine whether the educational behaviourof a group of Italian youth could best be represented as a “product of intentionalchoice”, or, as the “result of processes which in one way or another minimize thescope for socially meaningful choice at the individual level”, he asked:the theoretical question is whether it is more realistic to think of educationaldecisions as, so to speak, non-decisions, as pure individual manifestations of socialforces that act “behind the back” of agents, or whether it is rather the case that peoplerespond thoughtfully to events and try to act according to what they generally want.(Gambetta, 1982, p.3)63He posits that there are two relevant perspectives of the individual agent whenconsidering decision making processes: the pushed-from-behind view and thepulled-from-the-front view15. The first view, pushed-from-behind, regardseducational decisions as essentially non-decisions. This perspective adopts theviewpoint that reproductive forces are overwhelming; thus, they constrain or actbehind the backs of agents. Since the actions of individuals are ‘propelled’ byforces that are beyond the immediate reach of their conscious states, individualsare pushed into given destinations. Rather than clearly perceiving the availablealternatives and choosing the best alternative among them, individuals areguided by “some inner mechanism” to select a particular course of action,“behaving as if the feasible set were more restricted than it is objectively” (p.12).As such, agents are directed by causes that “act independently of theirawareness” (p.12). These forces which act behind individuals’ backs push themin two different directions: middle- and upper-class children are pushedupward and working class children are pushed downward.The second view, pulled-from-the-front, posits that “people are rationaland jump towards the destinations that attract them most” (Gambetta, 1987, p.2).Gambetta identifies two distinct versions of the pulled-from-the-front view. Ingeneral, both “pull” versions refer to an intentional agent, who is capable ofadapting intelligently to circumstances and to the perceived probability ofsuccess, and thus plans her or his life according to personal preferences. In thefirst version of the pulled-from-the-front view, when individuals make decisions15 In his initial theoretical formulation, Gambetta included a third view, “the structural view”,which he quickly discounted as an unsuitable generalized explanation of behaviour. In thisview, “individuals’ actions are channelled by external constraints, with no provision for choice”.That is, individuals are seen to have no choice or lack of any relevant alternatives. Gambettacomments that this approach treats actors as ‘structural puppets’, and shortcircuits the agent byemphasizing the constraints on behaviour rather than the behaviour itself. It is very difficult toclearly distinguish between these two views, as posed by Gambetta; hence, in my research theyare treated as a single perspective.64about their education, they rationally respond to their past achievement and tolabour market opportunities; in other words, they choose options that maximizeexpected utility. Individual preferences are considered as generally irrelevant.The second version emphasizes that individuals try to act according to whatthey generally want. A rational calculation of personal preferences and futurerewards results in a decision. Economic maximization, however, does notnecessarily drive these decisions. Personal preferences and aspirations make adifference in educational choices irrespective of ones social origin.Gambetta suggests that the first view (pushed) emphasizes causality, andthe second (pulled) intentionality. He points out that most authors haveconcentrated on either the ‘push” or the “pull” perspective when studyingeducational behaviour. He suggests that rather than disregarding or rejectingthe other perspective as irrelevant, it may be more fruitful to ask: “to what extentcan educational behaviour be represented as a product of intentional choice, orconversely, to what extent is it the result of processes which, in one way oranother, minimize the scope for socially meaningful choice at the individuallevel?” (p.7’).These perspectives, as identified by Gambetta, correspond to the twobroad intellectual streams, the sociological versus the economic, that Coleman(1988) indicates are used to describe and explain social action. The first view, thesociological, is that of the socialized actor whose action is governed by socialnorms, rules and obligations. The second view, typical of the work of mosteconomists, views the actor as “having goals independently arrived at, as actingindependently, and as wholly self-interested” (p.S95). According to Coleman,the main strength of the first intellectual stream rests in its ability to “describeaction in social context and to explain the way action is shaped, constrained, and65redirected by the social context’, and the second stream “in having a principle ofaction, that of maximizing utility” (p.S95).However, consistent with Kerkhoff’s assertion regarding the difficulty ofdistinguishing an allocation from a socialization model, Coleman also maintainsthat the two views of action are not separable. He argues that to adopt eitherview of action, independent of the other, is misguided, for as defined by the firststream, the actor is treated as though he or she is without an ‘engine of action’but is completely shaped by the environment, and in the second stream,constraints of the social environment are totally ignored. He suggests that theinvestigation of action should commence from one conceptually coherentframework, and proceed to introduce elements from the other, withoutdestroying the coherence of the first.Giddens (1984) provides a similar criticism. He asserts that even whensevere constraints limit the courses of action that an individual can take, someaccount of purposive action is still implied. Commenting on Gambetta’s study,he states that:structural constraints . . always operate via agents’ motives and reasons,establishing (often in diffuse and convoluted ways) conditions and consequencesaffecting options open to others, and what they want from the options they have.(p.310)He suggests that it would be more profitable to examine, in greater depth, theinfluence of structural constraints over the course of a particular action. Heproposes that topics for further study include how an individual’s motives andprocesses of reasoning have been influenced or shaped by factors in their familybackground and previous experiences, the social forces themselves, andexploration of the limits of agents’ knowledgeability.66Elster (1989a) provides a cogent way of consolidating these two views.According to Elster, action may be explained if it is viewed as the final result oftwo successive filtering operations. All of the abstractly possible actions thatmay be undertaken by an individual pass through each filter. The first filterconsists of all of the constraints faced by the individual. The individualsopportunity set is thus formed by extracting actions that remain possible, aslimited by the existing constraints.The second filter, according to Elster, consists of a mechanism thatdetermines which action, within the existing opportunity set, will actually beimplemented. Of these actions, rational choice is one. Using this perspective,Elster states that “actions are explained by opportunities and desires - by whatpeople can do and by what they want to do” (p.18). It is upon the opportunityset that an individual acts.Elster’s formulation of opportunity set and subsequent action allows for1) an exploration of action based on a given opportunity set, and 2) differencesin opportunity sets, and thus actions, amongst groups (e.g. participants and non-participants in post-secondary education).Given an existing opportunity set, how will an individual act? Rationalchoice theory will be used to consider this question.Individuals as Rational ActorsThe notion of rational action is not foreign to studies of educationalattainment and participation. However, the manner in which rationality istreated in studies of participation is inconstant. In some studies, rational action67is simply assumed, without any explanation as to what is meant. For example, inhis study on post-secondary education choices of high school graduates, Anisef(1975) states:A major assumption which guides our thinking and analysis in this panel survey isthat adolescents make rational choices and decisions. (p19)Porter, Porter, and Blishen (1982) provide an illustration where rationalaction is implied:It is very likely the case that when a student considers the amount of education hewould like to have, he first thinks of the job he would like and then considers theeducation he would need in order to qualify for that job. (p.99)Others provide concrete definitions. Bidwell and Friedkin (1988) assert:We assume that students are rational actors, so that they tend to define theeducational situation by assessing the costs and benefits of schooling, on one hand,and the personal capacity to gain benefits and reduce costs, on the other. (p.460)They continue:First, as students progress through the school grades, they make increasinglyfrequent, realistic calculations about the relationship between schooling and adultsocial destinations (primarily occupational or marital). Given our rational actorassumption, we expect that the higher the value of the material or social goods towhich a student aspires and the stronger the perceived effect of education on theirrealization, the higher the student’s tolerance for education. In other words, we areproposing a reciprocal relationship between academic performance and educationaland postschool aspirations, in which these aspirations reinforce performance just asthey are reinforced by performance via the definition of the educational situation.(Bidwell & Friedkin, 1988, p.463)Härnqvist (1978) suggests that individuals make educational choices as follows:The immediate determinants [of educational choice] result in preferences andexpectations which have to be matched against each other. . .The individual’sinformation set limits not only to the number of possible actions he may take, butalso to the predictive validity of his estimated probability to succeed in and obtainthe rewards from different alternative actions. His expectancy to succeed in a certaineducation depends not only on knowing that he meets the minimum entrance68requirements but also on estimating whether his qualifications are strong enough ina competitive situation before or during the education he is considering. (p.18)Even the tenor of questions on survey instruments often reflects a perspectivethat implies rational action. The following is an example of such a question:Everyone does not end up doing the job he or she likes. Considering your ability,marks, ambitions, and family finances, what job do you think you will actually end updoing ? (Anisef, 1980, Appendix C)Since assumptions of rationality play a central role in studies ofeducational participation, a review of the literature on rational choice isimportant. Such a review is also warranted since most studies of individualchoices (i.e. Gambetta’s “pull’ forces) are premised on one particular version ofrational choice theory.According to rational choice theory, when an individual is confrontedwith several courses of action, the action taken is the one that the individualbelieves is most likely to have the best outcome. That is, rational choice involveschoosing the best means available for achieving a given end. In this sense,rational choice is instrumental, and actions are chosen as efficient means to afurther end. It is a way of optimal adaptation to existing circumstances (Elster,1989a; Harsanyi, 1986; Mortimore, 1976).Aiming to explain human behaviour, rational choice theory proceeds intwo steps. The first step is normative - to determine what a rational personwould do in a given circumstance. The normative or prescriptive componentprescribes how individuals should act in a given situation, and emphasis isplaced on guidelines, procedures, and analytical tools for optimizing decisions.It also predicts that individuals will act in the prescribed way. This is followed69by the second step, descriptive in nature, which sets out to ascertain whether theaction, as described in the first step, is what the individual actually did. Incontrast to the normative model, the descriptive model describes the way thatdecisions are actually made in the real world. The focus of the descriptive modelis to provide an account of decision making behaviour, including each step inthe process (Baird, 1978; Elster, 1989a, 1989b; Harsanyi, 1986; McGrew & Wilson,1982).For the purposes of this study, two types of rational action will beconsidered: practical rationality (or practical reasoning), and technicalrationality.Practical RationalityPractical rationality or reasoning is described as reasoning which isundertaken to determine what to do (Audi, 1982). This is contrasted withtheoretical or epistemic reasoning which is undertaken to determine what is thecase or what to believe (Audi, 1982; Benn & Mortimore, 1976; Coombs, 1986).Benn and Mortimore (1976) state that to explain an act as rational, it is tosay that “a certain kind of relationship holds between the agent’s action, hisbeliefs about his situation and options, and the end-states he wishes to bringabout” (p.3). They state that practical rationality can be best understood as “acomponent of the ordinary notion of rationality in action”. According to Elster,the “central explanada of rational choice theory are actions” (p.4).The notion of practical reasoning embraces three components: beliefs,wants or desires, and evidence (Audi, 1982; Coornbs, 1986; Elster, 1989b). For an70action to be deemed rational, it must be the final result of three optimizingoperations. These operations are:1. It must be the best means of realizing a person’s desire, given his beliefs.2. These beliefs must themselves be optimal, given the evidence available tohim.3. The person must collect an optimal amount of evidence - neither too muchnor too little. That amount depends both on his desires - on the importancehe attaches to the decision and on the beliefs about the costs and benefits ofgathering more information. (Elster, 1989a, p.30)These optimalizing operations are represented by Elster, in Figure 6.Action/Desires ‘< BeliefsEvidence5igure 6. i4ifaptathrn ofE(stercSc1tema ofRgthrna(Cltoice.According to Elster (1989b), an action is explained by first confirmingwhether it is the best way of fulfilling an agents’ desires, given her or his beliefs.Desires and beliefs should be, at minimum internally consistent, but preferablyrational in themselves. As well, beliefs should be optimally related to theevidence or information available to an agent. Also, the beliefs an individualholds must be true.71Rational belief and rational action are contrasted with ‘not rational’, ‘non-rational’ or ‘irrational’ beliefs or action. An ‘irrational’ act is considered to be onethat is done without a reason when it is thought that there should be a reason,doing something for a bad reason, or if there is a good reason for taking analternate course of action that was known or should have been known by theagent. “To say of an act that it is irrational is to evaluate it as failing to come upto some standard of appropriateness. A person who acts irrationally is notacting well from some point of view” (Benn & Mortimore, 1976, p.3). A ‘non-rational’ act is beyond the scope of rationality; that is, the act committed whenthe individual “either could not have a reason for doing it, or that to assess it interms of reason is somehow out of place” (p.3). A ‘not rational’ act is one that issometimes irrational, sometimes non-rational (p.3).Technical RationalityOften, a “technical account of rationality” is used to explain behaviourregarding educational choice. Benn and Mortimore (1976) point out that thisview differs from the former view on two counts: 1) it omits the condition thatagents act on rational beliefs, the epistemic requirement, and 2) it tends tostipulate among the requirements special restrictions on what are admissible asends (p.4).When using a technical account of rationality, the type of decision isimportant to consider. Decisions can be of three types: decisions under certainty,decisions under risk, and decisions under uncertainty. Of these types, the firsttwo are relevant for this discussion.72Rational choice in certainty, or riskiess choice, follows the principle of‘utility maximization’. Utility maximization, according to Elster (1989a), issimply a convenient way of saying that one does what one most prefers. Itassumes that the individual can rank all the alternatives open to him or her inorder of preference and will then select the course of action that yields the mostdesirable consequence. The most preferred alternative is the one which yieldsthe most utility; “to maximize utility is therefore to select the alternative you likebest” (Heath, 1976, p.8).The second type of decision, decision under risk, prescribes thatindividuals should maximize expected utility. This is achieved by calculating theexpected value of available courses of action by weighing the possible gains orlosses [utility value] by the probability of their occurrence. Implicit is the notionthat the better one’s chance of getting something, the more likely one is to try it(Heath, 1976). According to Heath (1976), in order to maximize expected utilitythe individual must:consider each of the possible outcomes of a given course of action, assess the utilityof each, multiply the utility by the probability of the outcome’s occurrence, sum theproducts, and compare this sum of the products with the sum of products of othercourses of action. (p.84)Decision making under risk requires that individuals rely on their‘subjective probabilities’ or informed hunches. According to this version ofrational choice theory, the action to be taken is the one that has associated with itthe highest expected utility (Elster, 1989a, p.28).Choice regarding post-high school destination is generally assumed to bea decision under risk. According to Härnqvist (1978) participation in postsecondary education requires not only the actions of the deciding individual,but also acceptance by the selecting agency (p.l8)73Boudon (1976) provides an elaborate account of what he calls 11rationalitytheory”. Claiming that people behave according to their own interests in thesense that they attempt to maximize the utility of their decisions, Boudonmaintains that specific conclusions on variations in inequality of educationalopportunity may be drawn. He provides the following example:let us assume that two children, one from a middle-class and one from a lower classfamily, are located at the same point of the Cartesian space . . . . Let us furthersuppose that at some stage these children have to choose between, say, a general anda vocational course or between staying in or leaving school. . . . This effect willprobably be reinforced if not only the youngsters but also the family take part in thedecision process. The expected benefit which is perceived as attached to a givencourse will probably be differently evaluated by the families, exactly as the issue islikely to be differently evaluated by the youngsters. Generally, let us assume thatyoungsters and families must at some time choose between alternative a andalternative b - a being more likely to lead to a higher social status. Then we may saythat the expected benefit of choosing a rather than b is an increasing function of thefamily’s social status. The higher the social status, the higher the anticipated benefitassociated with a. . . . In summary, there is considerable empirical evidence tosuggest that given two possible alternatives a and b (where a is associated withhigher social expectations), the anticipated cost of a generally will be greater, thelower the social status of the family. In short, we can reasonably assume that the costof choosing a over b will be a decreasing function of family status (Boudon, 1974,p.29-30)Often in an economic explanation of post-secondary choice, admissibleends are restricted to the expected rate of return on investment. According toStager (1989a; 1989b), one of the strongest influences on the enrolment decisionis the individual’s assessment of the rate of return on educational investment.Investment in higher education depends on the expected rate of return, or theadditional life-time earnings an individual expects to receive followinggraduation when compared with the costs of completing a post-secondaryprogram. This method dictates that all benefits (earnings based on investment inpost-secondary education) and all costs (tuition fees, books and other expenses,forgone earnings) associated with the choice are compared to determinewhether the benefits exceed the costs. The calculation of the expected income74differential between post-secondary and high school graduates with the totalcosts, including forgone earnings leads to economic expectations about thebenefits of attending post-secondary education. Stager (1989b) indicates thatwhen properly applied, the basic logic of this type of cost-benefit analysis is“unassailable1(p.2).Employment of rational choice theory may help explicate the means thatindividuals use to pursue certain goals. It does not, however, explain differencesin preferences and desires, beliefs, reasons offered, amounts of informationused, or costs and benefits considered. Elster (1989a) indicates that while anaction is explained by considering the individual’s desires together with her orhis beliefs about the opportunities, it is unclear how objective and subjectiveelements interact to produce an action. Mistaken beliefs and limited awarenessof certain opportunities may result in the best means of realizing one’s desire notbeing chosen. As well, Elster avows, “at a further remove only opportunitiesmatter since they also shape desires” (p.19). Yet, by employing rational choicetheory to explain action, differences in opportunity sets remain unproblematic.How does a given opportunity set influence wants, desires, beliefs, andthus actions? Do wants, desires, and beliefs differ within and between groups ofparticipants and non-participants? If so, what accounts for these differences? Or,in more general terms, what processes underlie the decisions people make inchoosing whether or not to pursue a post-secondary education?To pursue these questions, the work of Bourdieu, and Bourdieu andPasseron, which focusses on the complex mediating processes in education, willbe utilized.75Bourdieus Theory of PracticeAccording to Bourdieu (1984), practices (action) can only be accounted forby illuminating the series of effects which underlie them. He proposes that thefollowing formula be used to analyse these effects:[(habitus) (capital)] + field = practice (p.101)As specified in this formula, three concepts, capital, habitus, and field are centralto Bourdieus theoretical formulation. In the next section, two forms of capital(cultural and social), habitus, and field are defined.According to Bourdieu (1984), primary differences distinguishing themajor classes of conditions of existence, derive from the overall volume ofcapital possessed by an individual. Capital is defined as, “the set of actuallyusable resources and powers’ and exists as many types - as economic, cultural,social, and symbolic capital16 (p.114). Capital can exist in objectified form, suchas material properties, or in incorporated form as in cultural capital, and thekinds of capital “like trumps in a game of cards, are powers which define thechances of profit in a given field” (Bourdieu, 1991, p.Z3O).Cultural CapitalOf the forms of capital defined by Bourdieu that contribute to thereproduction of the structure of power relationships and symbolic relationshipsbetween classes, cultural capital has received the most attention. Stimulated by16 Symbolic capital is defined as “prestige, reputation, fame, etc., which is the form assumed bythese different kinds of capital when they are perceived and recognized as legitimate” (Bourdieu,1983, p.Z3O).76the observation that discrepancies in ‘educational death rates” between socialclasses were not sufficiently explained by educational obstacles, Bourdieu (1986)states that the notion of cultural capital arose:as a theoretical hypothesis which made it possible to explain unequal scholasticachievement of children originating from different social classes by relatingacademic success, i.e. the specific profits which children from the different socialclasses and class fractions can obtain in the academic market, to the distribution ofcultural capital between the classes and class fractions. (Bourdieu, 1986, p.243)It is Bourdieu’s thesis that educational institutions, rather than beingsocially neutral institutions, are part of a larger universe of symbolic institutionsthat reproduce existing power relationships. The culture that is transmitted andrewarded by the educational system reflects the culture of the dominant class.Schools reinforce particular types of linguistic competence, authority patterns,and types of curricula. Children from higher social backgrounds acquire thesecultural resources (that is, dispositions, behaviour, habits, good taste, savoirfaire, and attitudes) at home, and enter the educational system already familiarwith the dominant culture. Acquisition of the information and training offeredby the school is dependent on the student’s ability to receive and decode it,which in turn depends on previously acquired cultural capital. According toBourdieu and Passeron (1979):all teaching.. . implicitly pressupposes a body of knowledge, skills, and above all,modes of expression which constitute heritage of the cultivated classes. . . Secondaryschooling. . . conveys second-degree significations which takes for granted a wholetreasury of first-degree experiences - books found in the family library, ‘choice’entertainments chosen by others, holidays organized as cultural pilgrimages,allusive conversations which only enlighten those already enlightened. It can onlylead to a fundamental inequality in this game reserved for privileged persons, whichall must enter because it presents itself adorned with universality. (p.22)Schools, however, do not teach the techniques required to receive and decodeculture. For those students who already possess the requisite cultural resources,77adjustment to school is facilitated, and academic achievement is enhanced;children who lack first-degree experiences are handicapped. Thus,comprehension of the second-degree significations, reflected in academicachievement, becomes difficult, if not impossible.Because students with the requisite cultural capital are able to excel inschool, cultural capital becomes objectified in the form of academicqualifications. In this way, cultural capital is converted into academic capitalwhich is academically sanctioned by legally guaranteed qualifications”(Bourdieu, 1986, p.2z18). Over time, cultural capital is eventually converted toeconomic capital through the guarantee of monetary value of a given academiccapital.Bourdieu (1986) explains that maximum appropriation of objectifiedcultural capital in the form of educational (or academic) capital depends onearly transmission by families endowed with strong cultural capital, since “theprecondition for fast, easy accumulation of every kind of useful cultural capital,starts at the outset, without delay, without wasted time, only for the offspring offamilies endowed with strong cultural capital” (Bourdieu, 1986, p.246). Thus, theacquisition of cultural rewards, is determined by the amount of cultural capitalthat is transmitted by the family. Families of higher social status transmit theculture which is the dominant culture. As a result, their children are more easilyable to access academic rewards.Differential academic achievement is usually perceived to be the result ofdifferential ability, rather than as a result of the volume and composition ofcultural capital transmitted by the family; thus, domestic transmission ofcultural capital is recognized as legitimate competence and is unrecognized ascapital. As such, it remains the “best hidden and socially most determinant78educational investment” (Bourdieu, 1986, p.244) In this way, the educationalsystem contributes to the reproduction of the social structure through itssanctioning of the hereditary transmission of cultural capital (Bourdieu, 1986).Cultural capital is considered to be a key mechanism in the reproductionof the dominant culture through which background inequalities are convertedinto differential academic attainments and hence rewards. This is accomplishedby producing and distributing a dominant culture that, as Giroux (1983) states,“tacitly confirms what it means to be educated” (p.87).Social CapitalThe second form of capital included in cultural reproduction theory isthat of social capital. According to Bourdieu (1986), social capital is:the aggregate of the actual or potential resources which are linked to possession of adurable network of more or less institutionalized relationships of mutualacquaintance and recognition - in other words, membership in a group - whichprovides each of its members with the backing of the collectively-owned capital, a‘credential’ which entitles them to credit, in the various senses of the word. (p.248)Social capital consists of social obligations or ‘connections’. Two criteriadetermine the volume of the social capital a given agent has at her or hisdisposal: first, the size of the network of connections that the agent caneffectively mobilize, and second, the volume of capital (economic, cultural, orsymbolic) possessed by each of those to whom the agent is connected (Bourdieu,1986).Coleman (1988, 1990) also advances the notion of social capital, andprovides a more complete, albeit somewhat different account. He states that“social capital exists in the relations among persons” (Coleman, 1988, p.S100).That is, it is inherent in the structure of relations between persons and among79persons. It is not conceived as a single entity, but a variety of different entities,each possessing two common characteristics: 1) some aspect of a social structure,and 2) the facilitation of certain actions of individuals who are within thestructure. Social capital, like other forms of capital, is productive; it actuates theachievement of certain ends that would be unattainable in its absence (Coleman,1990).Coleman (1988) maintains that social capital exists in three forms: asobligations and expectations, as information channels, and as social norms.Obligations and Expectations. Obligations are conceptualized as anetwork of outstanding credit slips, which are reciprocally called in, as required,by the holders. Two elements, trustworthiness among group members, and theextent of the obligations held, are necessary for this form of social capital towork. Coleman explains:If A does something for B and trusts B to reciprocate in the future, this establishes anexpectation in A and an obligation on the part of B. This obligation can be conceivedas a credit slip held by A for performance by B. If A holds a large number of theseslips, for a number of persons with whom A has relations, then the analogy tofinancial capital is direct. These credit slips constitute a large body of credit that Acan call in if necessary - unless, of course, the placement of trust has been unwise,and these are bad debts that will not be repaid. (S102)Individual actors differ not only on the number of outstanding credit slips intheir possession, but whether or not they are included in a given network of thisform of social capital. Those ‘in’ the network are more powerful than thoseexcluded.Information Channels. Coleman asserts that the potential for information,inherent in social relations, is an important form of capital, for informationprovides an important basis for action. This is consistent with the requirement ofsufficient information posited in the theory of practical rationality. Information,80however, is expensive and requires vigilance. Coleman suggests that one way ofappropriating information is through the use of social relations which aremaintained for other purposes. He provides an example of an individual,wishing to keep abreast with current events but finds little time to do so,depends on a well-informed spouse or parents to keep her or him informed.According to Bourdieu, one of the most valuable types of informationtransmitted by inherited cultural capital is practical or theoretical knowledge ofcurrent and future worth of academic qualifications. The ‘informed’ individual isthus able to invest wisely, including pulling out of devalued disciplines atpropitious moments, in order to achieve the best return for her or his inheritedcultural and educational capital. Those poorly informed about the diplomamarket lack the social capital to differentiate between the value of various typesof education (e.g. between community college and university). By attributingmore value on educational credentials than that which is objectivelyacknowledged, they continue to participate in education of less worth, and“become, in a sense, accomplices in their own mystification” (Bourdieu, 1984,p.l42)Norms and Effective Sanctions. According to Coleman, the existence ofeffective norms provides a powerful form of social capital. For example,community norms providing effective rewards for academic achievement,greatly facilitate the school’s role. Norms such as these, however, can be bothfacilitating and constraining. Recognition of achievement in academic courses,but neglect of other types of achievement, may stifle actions which deviate fromthe norm but would actually benefit the deviant individual as well as others.This may result in reduction of innovation in a given area.81One or more of these forms of social capital, used in simplex or multiplexrelations (Gluckrnan, 1967), facilitate actions of actors. In a multiplex relationship,linkages among people occur in more than one context, allowing forappropriation of resources among the various relations. An example relevant tothis study would include the interrelated linkage of a student with parents,guidance counsellors, someone in the aspired profession, and a family friendwho is knowledgeable about post-secondary education. While linkages betweenthe student and various individuals may exist in a simplex relationship, theywould not be interrelated.Bourdieu (1986) adds another dimension to social capital. He argues thatmembers of the dominant culture, who tend to increasingly emphasizeeducational investment, are also able to use social capital as a way of “evadingscholastic verdicts”. That is, through the use of social capital in the form of ‘ahelping hand, ‘string-pulling’, and/or the ‘old boy network’, the effect ofacademic sanctions may be corrected.HabitusMost simply, habitus is a system of dispositions which are created andrecreated as objective structures and personal history converge. Disposition, forBourdieu, has a three-fold meaning. First, it is the result of an organizing action,thus similar to the word structure. Second, it implies a way of being, a habitualstate. Third, and most important, it expresses the idea of predisposition,tendency, propensity, or inclination (Bourdieu, 197Th). As such, habitus is“history turned into nature” (Bourdieu, 197Th, p.78) Bourdieu (197Th) providesthe following definition:82the habitus, a product of history, produces individual and collective practices - morehistory - in accordance with the schemes generated by history. It ensures the activepresence of past experiences, which, deposited in each organism in the form ofschemes of perception, thought and action, tend to guarantee the ‘correctness ofpractices and their constancy over time, more reliably than all formal rules andexplicit norms. The habitus is a system of dispositions “a present past that tends toperpetuate itself into the future by reactivation in similarly structured practices, aninternal law through which the law of external necessities, irreducible to immediateconstraints, is constantly exerted. (p.54)andthe habitus is necessity internalized and converted into a disposition that generatesmeaningful practices and meaning-giving perceptions; it is a general, transposabledisposition which carries out a systematic, universal application - beyond the limitsof what has been directly learnt - of the necessity inherent in learning conditions.(Bourdieu, 1984, p.170)The habitus is a practice-unifying and practice-generating principle that iscapable of generating an infinity of practices depending on changing objectivesituations. The habitus, as a generative principle, is limited only by objectivestructures. Structures are portrayed as systems of objective relations which areimparted to individuals which they pre-exist and survive. The structures whichconstitute a particular type of environment produce the habitus, and is thereforea ‘structured structure’, which, in turn, predisposes it to be a ‘structuringstructure’ as the generating principles are inculcated and become “objectively‘regulated’ and ‘regular” (Bourdieu, 197Th, p.72)Kennett (1973) likens the habitus to DNA coding in organisms. Once thehabitus is sufficiently developed, it begins to generate an appropriate inodusoperandi by informing and reproducing that which is deemed ‘appropriate’ innew contexts. Because the habitus is structured, it also possesses a structuringnature. Thus:83the ‘informed’ individual comes to find ‘naturally’ within him the cognitive andexpressive styles that legitimate his eventual place in the social structure. Theforming of the habitus may be regarded as the programming of the individual andthe group to which he ‘belongs’, the handing down of the code which reaps itsharvest in the educational system leading to ‘legitimized’ places in the socialhierarchy. (Kennett, 1973,p.242)According to Bourdieu, actions (or practices) are neither mechanicallydetermined nor the result of creative free will. Rather, practices are “determinedby past conditions which have produced the principle of their production”(Bourdieu, 1977b, p.73). He asserts that when agents’ actions are described as aconscious adjustment of their aspirations to an exact evaluation of their chancesof success, it is assumed that probabilities are calculated based on spontaneousdispositions. He suggests, instead, that unlike scientific estimations ofprobabilities, when an individual undertakes a practical evaluation of thelikelihood of his or her success, “a whole body of wisdom, sayings,commonplaces, ethical precepts (‘that’s not for the likes of us’), and at a deeperlevel, the unconscious principles of ethos17 . . . determines ‘reasonable’ and‘unreasonable’ conduct for every agent subjected to those regularities” isintroduced (Bourdieu, 1977b, p.77). Even when practices appear as therealization of the explicit, and explicitly stated, purposes of a project or plan,these practices are, in reality, produced by the habitus, which is the strategy-generating principle enabling agents to cope with unforseen and ever-changingsituations (Bourdieu, 197Th).Dispositions are durably instilled by objective conditions, and thusgenerate aspirations and practices which are objectively compatible with thoseobjective requirements. In this way, the most improbable aspirations and17 Bourdieu (1974) defines ethos as “a system of implicit and deeply interiorized values which,among other things, helps to define attitudes toward cultural capital and educationalinstitutions” (ph0).84practices are excluded from one’s repertoire of choices. Exclusion results becausepractices are perceived as either unthinkable, and therefore not examined, or as aresult of double negation which “inclines agents to make a virtue of necessity, thatis, refuse what is anyway refused and love the inevitable” (Bourdieu, 1977b,p.77). He adds that it is rather like an example provided by Leibniz, in which“the magnetic needle . . . actually enjoying turning northwards” (p.77). This iswhat Bourdieu calls the hysteresis effect, in which practices are susceptible tonegative sanction when individuals are confronted with an environment whichis too remote from the one to which they are objectively and ‘naturally’ fifted(Bourdieu, 1977b). It is due to the hysteresis of habitus, which he states isinherent in the social conditions of the reproduction of the structures in habitus,that a structural lag exists between opportunities and the dispositions to graspthem, thereby resulting in missed opportunities (p.83). The hysteresis effect issimilar to Elster’s (1983) mechanism of “sour grapes”, a mechanism of cognitivedissonance reduction which acts to ensure that there is no option outside theopportunity set that is preferred to the most preferred option within it.The habitus, as a concept, is relevant both at the individual level andgroup or class level. Group or class habitus exists because individuals of aparticular class or group are exposed to homogeneous conditions of existence,and thus are the product of dispositions because of internalization of the sameobjective structures. This enables practices to be objectively harmonized withoutconscious intention, explicit co-ordination, or direct interaction; in other words itoccurs as “conductorless orchestration”. In this way, the same class is endowedwith an objective meaning that is both unitary and systematic, and transcends“subjective intentions and conscious projects whether individual or collective”(Bourdieu, 1977b, p.Sl). While it is not possible for all members of the same class85to have had the same experiences, in the same sequence, members of the sameclass are more likely than members of another class to have faced situationsmost commonly experienced by members of that class (Bourdieu, 197Th).FieldBourdieu (1991) describes the social world as represented in the form of amulti-dimensional space comprised of intersecting fields. Agents, or groups ofagents, are “defined by their relative positions in this space” (p.23O) Each agent isconfined to one, and only one, position. A set of active properties whichconstitutes this multi-dimensional social space is able to confer force or poweron the agents who occupy it. Since these properties selected in the constructionof this space are active properties, the space can also be described as a field offorces --“as a set of objective power relations imposed on all those who enter thisfield, relations which are not reducible to the intentions of individual agents oreven to direct interactions between agents” (Bourdieu, 1991, p.Z3O). The activeproperties that construct the social space are the different kinds of power orcapital relevant to a given field. Thus, the position occupied by a given agent inthe social space is defined by the position that she or he occupies in the differentfields (of which the educational field is one) and in the distribution of powersthat are active in each field. These powers or capital are economic capital,cultural capital, social capital, and symbolic capital. He summarizes:86the social field can be described as a multi-dimensional space of positions such thateach actual position can be defined in terms of a multi-dimensional system of coordinates whose values correspond to the values of the different pertinent variables.Agents are thus distributed, in the first dimension, according to the overall volumeof the capital they possess, and in the second dimension, according to thecomposition of their capital - in other words according to the relative weight of thedifferent kinds of capital in the total set of their assets. (Bourdieu, 1991, p.Z31)Success at accessing the specific profits offered by a field (for example, theacademic requirements necessary to gain admission to university) depends on 1)the configuration of the various forms of capital which is socially or legallyrecognized as legitimate in a particular field, and 2) the relative positions ofagents (dictated by the volume and composition of capital with which one entersthe game) in the field. Every position, even the most dominant one, is dependenton the other positions which constitute the field. Thus:the structure of the field, i.e. the space of positions, is nothing other than thestructure of the distribution of the capital of specific properties which governssuccess in the field and the winning of the external or specific profits. . . which are atstake in the field. (Bourdieu, 1983, p.312)The social trajectory of a given individual arises from the intersection of thedifferent fields (Robbins, 1991).Harker (1990) explains that in the educational field, agents struggle forcapital in the form of credentials. The educational field may be viewed not onlyas a field of forces, but also as a field of struggles which tends to transform orconserve the field as a field of forces. Occupants of various positions in the fieldare oriented, through the network of objective relations between the positions, tothe strategies which may be implemented in their struggles to either defend orameliorate their positions. The usefulness and eventual success of implementingthese strategies, however, depends on the original position occupied by eachagent (Bourdieu, 1983, p.3t3).87In order to adjust to the demands of a given field requires that onepossess “a feel for the game” (Bourdieu, 1990b, p.66) which he describes as themeeting of the incorporated history of the habitus of an individual and theobjectified history of a particular social field. A “feel for the game” is producedby experience with the game, and thus experience with the “objective structureswithin which it is played out” (p.66). An individual who is born into the gameand born with the game has a natural advantage over those not born into thegame, because:native membership in a field implies a feel for the game in the sense of a capacity forpractical anticipation of the ‘upcoming’ future contained in the present, everythingthat takes place in it seems sensible: full of sense and objectivity directed in ajudicious direction. (Bourdieu, 1990b, p.66)A Theory of Practice and Post-high School DestinationBourdieu (1977a, 1986) claims that as groups and organizations withinsociety purport to adopt policies that support equality of opportunity, dominantgroups increasingly adopt other indirect mechanisms of reproduction. In thecase of equality of opportunity in post-secondary education, the demise of directmechanisms of reproduction (ascriptive forces such as social position, gender,and race) and adoption of selection policies based on meritocratic criteria,results in the emergence of other indirect mechanisms of reproduction, in theform of cultural capital and social capital. These forms of capital originate withinthe family domain, are transmitted via the educational system, and areconverted into educational capital. In this way, social origin, in the guise ofcultural and social capital, is able to “exert its influence throughout the whole88duration of schooling, particularly at the great turning points of a school career’(Bourdieu & Passeron, 1979, p.l3) They assert that:the chances of entering higher education can be seen as the product of a selectionprocess which, throughout the school system, is applied with very unequal severity,depending on the student’s social origin. In fact, for the most disadvantaged classes,it is purely and simply a matter of eliminahon. (p.2)Rather than direct exclusion, however, which is no longer sanctioned,other forms of exclusion occur. Lamont and Lareau (1988) summarize the fourmajor forms of exclusion identified by Bourdieu, and Bourdieu and Passeron:self-elimination, overselection, relegation, and direct elimination. They indicatethat the first three forms of elimination are distinguished from direct eliminationby their ‘elective affinities’ which are based on similarities in taste. The influenceof cultural capital, social capital, and habitus on each of these forms of exclusion,is considered in the next section.Self-eliminationSelf-elimination is the work of the habitus. It occurs when individualsadjust their aspirations to their perceived chances of success. Individuals alsoexclude themselves from specific social situations in which they feeluncomfortable because they lack familiarity with specific cultural norms.In relation to post-high school destinations, self-elimination occurs whenindividuals with credentials to attend post-secondary education choose insteadnot to attend. Reasons provided for non-attendance may be the unlikelyprobability of success or unfamiliarity with post-secondary life. More likely,according to Lamont and Lareau (1988), participation in post-secondaryeducation is described as undesirable, based on beliefs of its questionable value,89thus ‘not for me’. Similar reasons would be provided for choice of communitycollege over university.OverselectionOverselection results when individuals who possess less valued resourcesare subjected to the same selection processes as those who are privileged. Inother words, their handicap, limited capital, is not taken into account, and theyare required to perform equally well as those who possess more valuedresources. Thus, they are required to perform more than others.In the case of overselection, the existence of a relationship betweeneducational levels of parents and academic achievement of children, which inturn affects participation levels of children in higher education is consistent withan explanation of parental transmission of cultural capital. Evidence of theinfluence of social capital is consistent with the existence of disadvantagedindividuals who are less subject to the positive influence of significant others(e.g. parents, guidance counsellors), less well informed, less likely to be inenvironments with strong positive educational norms, and less likely to be inmuliplex relations. A relationship would exist between participation in postsecondary education and some or all of these factors. The influence of economiccapital would be related to the effect of fees and distance from post-secondaryinstitutions on participation.90RelegationIndividuals who possess less valued resources are relegated to lessdesirable positions. Ultimately, they get less out of their educational investment.According to Bourdieu and Passeron (1979):for students from the lower classes who have survived elimination, the initialdisadvantages have evolved: their social past has been transformed into aneducational handicap through relay mechanisms such as early, often ill-informeddecisions, forced choices, or lost time. (p.14)A relationship between curricular differentiation (at both the secondaryand post-secondary level) of the student and the student’s family background isconsistent with an explanation of parental transmission of cultural capital.Possession of social capital would be demonstrated by knowledge of prerequisite courses, and qualitative differences among the various types of postsecondary institutions.Table 4 summarizes the relationship between capital and habitus on thedifferent forms of exclusion:91Table 4.Forms of Exclusion in Relation to Capital and Habitus.Self- Overselection Relegation Directelimination ExclusionCultural • Presence of a • Association • In the form ofCapital relationship between curric- academic capital -between parents’ ular differentiat- either as an unsocial background ion of student and acceptable GPA, orand educational social class of as unrecognizedcapital of child. parent. credentials.Social • Relationship • Knowledge-Capital between inform- ability of studentation channels, about pre‘connections’, requisites,influence of differentsignificant others, institutions.presence of educational norms andparental socialclass.Economic • Ability to afford • Lack of moneyCapital fees, to pay fees.. Distance frompost-secondaryeducation.Habitus • Disposition • Acceptance of • Acceptance oftoward post- the one’s place in thesecondary need to 1) seek educationaleducation e.g. out hierarchy, i.e.“it’s not for me” student loans, satisfaction withor “I always knew 2) go to a conim- curricular choices,I would go’. unity college limitations.. Acceptance of whenacademic ability, desires, beliefsas defined by the anddominant culture. abilities indicatethat universitywould be a betterchoice.Together, these forms of elimination or exclusion, assessed consciously orunconsciously, present an image of higher education as an “impossible,”92‘possible’, or “natural” future. Direct exclusion is no longer necessary, sinceeverything occurs as if those who were eliminated, excluded themselves.Evidence of the existence of indirect forms of elimination is provided when,despite the standardizing influences of thirteen years of schooling, differences inaffitude and ability, and participation are significantly related to social origin(Bourdieu & Passeron, 1979).The lack of clearly delineated educational streams or tracks, according toBourdieu (1984) encourages and entertains blurred and fuzzy aspirations, whichfacilitates the process of indirect elimination. He continues:whereas the old system tended to produce clearly demarcated social identities whichleft little room for social fantasy but were comfortable and reassuring even in theunconditional renunciation which they demanded, the new system of structuralinstability in the representation of social identity and its legitimate aspirations tendsto shift agents from the terrain of social crisis and critique to the terrain of personalcritique and crisis” (Bourdieu, 1984, p.156)Bourdieu comments that it is significant that divisions, while looselydifferentiated throughout elementary and secondary school, are sharplyclarified at the points where access to the dominant class is decided. In Canada,these divisions occur at the point of entry into higher education. However, evenwithin systems of higher education, subtley ranked paths and skilfullydisguised ‘dumping grounds’ help to blur perception of its hierarchies(Bourdieu, 1984).93Reproduction and AgencyWhile the influence of social origin, transmitted as cultural and socialcapital through the habitus, is relevant to the choice of post-high schooldestination, action does not take the form of mechanical determinism. Familybackground provides individuals with social, cultural, and economic capital.This capital, however, must be actively invested. As Jencks et al. (1983) indicate:while individuals with high SES parents, high aptitude scores, high grades, andcollege-bound friends all enjoy appreciable occupational advantages, they only do soif they get more schooling than average. (p.6)When used rationally, educational success is facilitated by the possession ofvarious forms of capital. Through shrewd investment of the capital at hand,even individuals from the most disadvantaged classes, those who are mostlikely to be “crushed by the weight of their social destiny”, are able to overcometheir excessive handicap, and thus “avoid the common fate of their class”(Bourdieu & Passeron, 1979, p.25).Bourdieu (1976) uses the analogy of players in a card game todemonstrate how individuals, as agents, invest various forms of capital18.Cardsdealt to the players represent social, cultural, and economic capital. The outcomeof the game depends on the nature of the hand dealt, whose strength is definedby the 1) rules of the game, and 2) the degree of skill with which the hand isplayed. Thus, strategy plays an important role in profiting from the varioustypes of resources (Bourdieu, 1976; Lamont & Lareau, 1988). Cultural, social,and economic capital can be invested and converted in to one another to18 Although Bourdieu uses this example as an illustration of marriage strategies, it seemsequally relevant to educational strategies.94maximize one’s upward mobility (Bourdieu, 1985). In this way, individuals,directed by the habitus, are able to act on their resources.Destinations, Determinants, and DecisionsAdmission into the Canadian system of higher education is determinedexclusively on the basis of academic achievement and curricular differentiation.It is, to use Turner’s (1960) term, a system of contest mobility, and the rules ofthe game are defined according to meritocratic principles. That is, academiccapital, in the form of a high school graduation diploma, is the only requirementfor entrance into some form of post-secondary education. University entrancerequires certain prerequisite academic courses and a minimum grade pointaverage.Given a rational choice explanation of post-secondary participation, itwould be expected that individuals would apply to and attend post-secondaryinstitutions most compatible with their grade point averages and prerequisites --in other words, their actions should be based on evidence optimal to thedecision at hand. Also, wants and desires regarding participation in post-secondary education, the beliefs that form the basis for wants and desires, andreasons provided for actions, should be based on evidence (as described inChapter 2).However, given the explanations provided by Bourdieu’s Theory ofPractice, relationships should be detected between curricular differentiation andsocial and cultural capital transmitted by the family (relegation), academicachievement and social class background (overselection), and among social and95cultural capital, dispositions (or habitus) toward post-secondary education, andparticipation (self-elimination).In Chapter 4, research questions and related conceptual frameworks toexplore these relationships are developed from the bodies of literature reviewedin this chapter.SummaryThis chapter began with a review of two dominant bodies of literature oneducational attainment and participation, the social stratification perspectiveand research on status attainment. From this review, a model of educationalchoice as proposed by Härnqvist was deemed to provide a comprehensiveframework on which to base analyses of the macro-processes of educationalchoice by non-participants, non-university participants, and universityparticipants. Next, in order to pursue the micro-processes of educational choice,rational choice theory, from both a practical reasoning and technical rationalityperspective, offered one approach to the examination of how individuals act inrelation to the individual and institutional determinants in Härnqvists model.Finally, the introduction of Bourdieus Theory of Practice and related concepts ofcultural capital, social capital, habitus, and field presented another avenue toexamine the processes which underlie the decisions people make in choosingwhether or not to pursue post-secondary education.Chapter 4RESEARCH QUESTIONS, CONCEPTUAL FRAMEWORKS, ANDHYPOTHESESWhy is it that some students do not continue to the post-secondarysystem following high school graduation? Why do other students proceeddirectly to post-secondary education? Of those who do continue, why do theychoose one type of institution over another? It is clear from the previous twochapters that the problem of educational choice may be conceptualized andanalysed in a variety of ways. In Chapter 3 several approaches to post-secondaryparticipation were reviewed. Also, two theories -- rational choice theory andBourdieu’s Theory of Practice -- were presented as providing possibleexplanations for how individuals arrive at various post-high school destinations.In order to grasp the complexity of how individuals arrive at variouspost-high school destinations, three separate but interrelated questions, eachrequiring a particular conceptual and/or methodological approach, areadvanced. In this chapter, the research questions and related conceptualframeworks are presented. The conceptual frameworks are based on theHärnqvist’s determinants of educational choice, rational choice theory primarilyas posited by Elster, and Bourdieu’s Theory of Practice. Together they provide acomprehensive heuristic for exploring factors affecting participation in postsecondary education, the social processes behind these actions, and individualsperceptions and understandings of these processes.9697Question 1. What factors influence whether and where one participates in post-secondary education?l.a. What are the individual and institutional determinants ofeducational choice?l.b. What combination of individual and institutional determinantsdiscriminate between participants and non-participants? That is, doparticipants and non-participants possess different opportunity sets?In order to address the first set of questions, Härnqvists framework ofeducational choice, as depicted in Figure 5 (Chapter 3) has been recast into ananalytical model, as portrayed in Figure 7. In this model, individual andinstitutional determinants of educational choice are framed within the context ofthe social and cultural conditions and labour markets and the economy, asdescribed in Chapter 2.Employment of Härnqvists framework allows for an exploration of therelationship between individual and institutional determinants of educationalchoice and whether and where one participates in post-secondary educationfollowing high school graduation. The nature of opportunity sets, and thus thedifferential impact of the determinants possessed by non-participants, non-university participants, and university participants, may be revealed.As indicated in Chapter 3, however, illumination of these relationshipswill not reveal how and why certain individual and institutional variablesinfluence choice. Different factors are determinants, of course, only in the sensethat while individuals make choices, they do not always do so under conditionsof their own choosing (Giddens, 1984). Of interest in this study is whether andhow individuals overcome or succumb to constraining factors and whether theyrecognize, acknowledge, and embrace enabling factors. Thus, in order to begin to98Labour Markets and the EconomySocial and Cultural ConditionsIndividual Determinants of Educational ChoiceI. Student Characteristics-sex-GPA— interestsexpectationsbeliefsII. Personal Environmenta. family background- parents’ education- parents’occupation- parents’ influence- other family members’ influenceb. peer groupc. school climate- school district size¼ .• socioeconomic status of school district- % of gr.12 graduates on honour roll in s dNon participantUniversity¼_______________________________¼ Institutional Determinants o¼• EducationalSystem¼ i) Conditions antecedent to choicea curricular differentiation¼ I- university entrance requirementsb. guidance organization- teachers’ influence- counsellors’ influence¼ - number of sources of information used¼ ii) Conditions anticipated in the choice situationa. geographic availability- distance from nearest university¼ - distance from nearest community collegeb. study finance¼ - total number of awards receivedI II L.L.T4qure 7’: etenninant.c ofrEilucationalCñoice99unravel how these relationships are created and reproduced, a second question isposed:Question 2. What processes underlie the decisions people make in choosingwhether or not to pursue a post-secondary education?As reviewed in Chapter 3, rational choice theory is often used to explaineducational choice. Given the problem of deciding about one1s post-high schooldestination, a rational choice, in the sense of practical rationality, would havebeen made if: an individual chose the post-high school destination that was thebest means of realizing her wants and desires, given her beliefs; that her beliefswere optimal, or true given the available evidence; and finally, that an optimalamount of evidence was gathered (Figure 8).59qure 8. R.çtiortaCClwice ‘Theory aost-Iig11ScIioo(Statu.c.100According to tenets of technical rationality, an individual would have behavedrationally if he calculated the expected value of available post-high schooloptions by weighing the utility of each possible outcome by the estimatedprobability of that outcome. Or more specifically, rational action would requirethat individuals calculate their expected rates of return on investment in furthereducation.Thus, one way of unravelling the processes behind the decisionsindividuals make about life after high school is to determine whether and towhat extent rational choice theory helps to make sense of students’ actions. Thefollowing questions may be posed:2.a. Do individuals use the tenets of practical rationality when makingdecisions about post-high school destinations?2.a.i. Do students make choices based on wants and desires,given their beliefs?2.a.ii. Are these beliefs optimal, or true, given the availableevidence?2.a.iii. Has an optimal amount of evidence been collected inorder to justify one’s choice?2.b. To what extent is a technical account of rationality relevant indescribing actions?2.b.i. Under conditions of risk, do students calculate theexpected value of available options by weighing the utilityof each possible outcome by the estimated probability ofthat outcome? Do individuals choose the action that hasthe highest expected utility?2.b.ii. Do individuals calculate their expected rates of return oninvestment in further education?101Employment of the principles of rational choice theory may be useful inelucidating, as Figure 8 portrays, whether individuals act according to theirdesires, given their beliefs and in light of available evidence. Also, it may bedetermined whether desires, beliefs, and the collection of evidence differbetween groups of participants and non-participants.However, while rational choice theory may reveal that differences doexist, it does not explain why or how these differences arose. As Hindess (1988)asserts, rational choice “accords a very limited role to the significance of socialstructure or social relations for actors and their actions” (p.36). Nor does it takeinto consideration the “processes of deliberation” among beliefs, desires, andaction (p.6).Bourdieu,in what he calls a Theory of Practice, argues that the conceptsof cultural capital, social capital, and dispositions toward post-secondaryeducation (habitus) are superior to those advanced by rational choice theory inexplaining action. The relationship between these concepts and post-high schooldestinations is outlined in Figures 9 and 10..!Tiqure 9. Cultural CapitalaiufPost-fliqfl. SchoolStatus.102As Figure 9 portrays, parents as sources of cultural capital directly affect theirchildren’s dispositions toward post-secondary education and the amount ofacademic capital accrued over the high school years. The subsequentrelationship between dispositions toward post-secondary education andacademic capital is reciprocal; that is, dispositions impact on academic capitaland vice versa. In turn, dispositions toward post-secondary education andacademic capital directly affect post-high school status.In this study, social capital is conceptualized as existing in two forms -- asprimary social capital as supplied by the family and as secondary social capitalacquired through relationships with school personnel and friends. The effects ofprimary and secondary social capital are illustrated by the presence anddirection of paths as depicted in Figure 10.103To ascertain the relationship between cultural capital, social capital,beliefs about and dispositions toward post-secondary education, academic andenabling capital on the post-high school status of the individual, the followingquestions may be asked:Fqure 10. Social Capital an ost-I1ig! Sc!oolStatus.1042.c.i. How and to what extent do parents as sources of culturaland primary social capital directly and indirectly affect thepost-high school status of their children?2.c.ii. Do counsellors, teachers, and friends as sources ofsecondary social capital influence the post-high schooldestinations of high school students?This study, however, endeavours to go one step further. In his study ofeducational opportunity in Italy, Gambetta (1987) concluded that:educational decisions are the joint result of three main processes: of what one can do,of what one wants to do, and, indirectly, of the conditions that shape on&spreferences and intentions. They are partly the result of causality and partly ofintentionality. (p.168-9)Guided by this conclusion, the following question is posed:2.d. What is the relationship between the concepts advanced inrational choice theory and Bourdieu’s Theory of Practice?Rather than treating these two theories as competing, a conceptual model ofPost-high School Status, as presented in Figure 11, is proposed. This model arisesfrom the previous set of research questions and integrates concepts central torational choice theory and Bourdieu’s Theory of Practice in order to provide adetailed portrait of the processes behind individuals educational decisions.The model, as illustrated in Figure 11, includes eight constructs. They are:sources of cultural capital, sources ofprimary social capital, beliefs about post-secondaryeducation, academic capital, sources of secondary social capital, dispositions toward postsecondary education, enabling capital, and post-high school status. As withHärnqvisttsframework, this model of Post-high School Status is framed by thelarger social, cultural, and economic context.Justification for the causal arrangement of the constructs in this model hasbeen explored in Chapters 2 and 3. Hypotheses indicating predictedQiLFiqure11.Sv1ot[e1ofPost-fiigfiSc1woCStatus106relationships between paths and their directions, as illustrated in Figure 11, arespecified in the next section. While these hypotheses specify only the predicteddirect effects of one construct on another, the model in its entirety is expected tobest explain post-high school status. Thus, indirect effects are also expected.HypothesesHypothesis One. It is hypothesized that the effects of the two exogenousvariables, sources of cultural capital, and sources of primary social capital, and oneendogenous variable, sources of secondary social capital, will have positive effectson beliefs about post-secondary education.Hypothesis Two. One exogenous variable, sources of cultural capital, and twoendogenous variables, beliefs about post-secondary education and dispositions, ispredicted to have positive effects on academic capitaLHypothesis Three. It is hypothesized that the two exogenous variables -- sourcesof cultural capital and sources ofprimary social capital - will have positive effects onsources of secondary social capital.Hypothesis Four. The two exogenous variables -- sources of cultural capital andsources of primary social capital -- and sources of secondary social capital, beliefs aboutpost-secondary education, and academic capital are hypothesized to have positiveeffects on dispositions toward post-secondary education. That is, a non-recursive orreciprocal path between academic capital and dispositions toward post-secondaryeducation is hypothesized.107Hypothesis Five. Three endogenous variables, academic capital, sources ofsecondary social capital, and dispositions toward post-secondary education arepredicted to have positive effects on enabling capital.Hypothesis Six. It is hypothesized that one exogenous variable, sources ofprimarysocial capital, and three endogenous variables including academic capital,dispositions toward post-secondary education, and enabling capital will have positiveeffects on post-high sciwol status.Furthermore, both sources of cultural capital and sources of primary socialcapital are predicted to have strong indirect effects on post-high school status.Sources of cultural capital is not, however, predicted to have a direct effect on post-high school status.One final question, which focuses directly on the actor, is advanced.Question 3. How do students perceive the processes underlying their decisionsregarding their post-high school destinations?The model of Post-high School Status, as proposed in Figure 11, is used inChapters 8 and 9 to further unravel the processes, and the perceptions of theseprocesses, which lie behind the decisions individuals make when contemplatingwhether and where to participate in post-secondary education.This set of research questions, and conceptual frameworks based onHärnqvist’s conceptualization of the determinants of educational choice, rationalchoice theory as explicated primarily by Elster, and Bourdieus Theory ofPractice, is intended to help explain the relevant determinants of educational108choice, the processes behind the decisions people make in choosing whether ornot to pursue post-secondary education, and individuals’ perceptions of theseprocesses.In the next chapter, a description of the data sources, instruments andmethods of data collection, and details of the survey sample and interviewsample is provided. The observed variables and formulation of the latentconstructs are described in detail in Chapter 6. Questions 1 and 2 are explored inusing discrirninant function analysis in Chapter 7 and structural equationmodelling (LISREL) in Chapter 8. Question 3 is investigated in Chapter 8through the use of indepth interviews with Grade 12 students.Chapter 5RESEARCH DESIGNGiven the nature of the research questions and the conceptual frameworksas described in Chapter 4, the strategy of multiple triangulation was employed inthis study. That is, multiple sources of data and methodologies were used withthe intent of providing a rich, composite depiction of educational choice. Thischapter includes a description of the data sources, details of the samples,instruments and methods of data collection, and preparation of the data. Thechapter concludes with a statement of delimitations and limitations.Three sources of data have been used in this study: 1) data from the LinkFile Data Base, 2) data generated by the Grade 12 Graduate Follow-Up surveyquestionnaire, and 3) interviews conducted with a sample of Grade 12 studentswho were in the process of making decisions regarding post-high schooldestinations. Each source of data will be described separately.Link File Data BaseThe Link File Data Base is a data base of confidential individual studentrecords from British Columbia secondary schools, colleges, institutes, anduniversities. The purpose of this data base is to provide a clear picture of studentsas they progress through the entire educational system. It is comprised of twoseparate data files - a transcript file and a post-secondary institution file. Thetranscript file contains pre-tertiary level information about the individual such asschool district attended, provincial examination results, and grade point average109110earned. The post-secondary institution file documents information about post-secondary status such as post-secondary institution attended, major programarea, and discipline cluster. The data, of which these files are comprised, aresubmitted by the various British Columbia educational institutions to the B.C.Research Corporation. The B.C. Research Corporation is entrusted with itsmanagement. The Link File Project data base served two purposes in this study.First, it was used to generate the sample of individuals surveyed in the Grade 12Graduate Follow-Up survey questionnaire, and second, information available inthe Link File data base was merged with questionnaire data to provide acomprehensive data set.Grade 12 Graduate Follow-Up Survey DataIn May 1989, a survey of Grade 12 graduates was conducted by the BritishColumbia Research Corporation and the British Columbia Institute ofTechnology, under contract with the Ministry of Education and the Ministry ofAdvanced Education and Job Training. Two of the primary purposes of thissurvey were to “collect fundamental, student-based information” (BritishColumbia Research, Corporation, 1990a, p.2) and “to investigate reasons whystudents choose to go, or not to go, to post-secondary education” (p.4). In thisstudy, 10,000 Grade 12 graduates of the 1988 cohort were sent a surveyquestionnaire entitled Grade 12 Graduate Follow-Up. Respondents included bothnon-participants and participants in the post-secondary system. The followingsections describe the target and frame population, stratification and samplingstrategy, return rates, and representativeness of the sample.111The SampleDuring the 1987/88 school year, approximately 43,800 students wereenrolled in Grade 12 in British Columbia. Of these enrollees, 28,677 fulfilled therequirements for Grade 12 graduation. The latter group, the Grade 12 graduates,was defined as the target population for this study.The frame population differs from the target population in two ways:noncoverage and foreign elements. Of the 28,677 graduates, only 23,428 records,representing 82% of the target population, were available in the Link File database. This figure represents those students who granted permission to theMinistry of Education, at the time of writing provincial examinations, to releasetheir Grade 12 records for research purposes.Total Graduates Permission Granted PermissionRefused28,667 23,428 5,247(100%) (82%) (18%)Since records of the 18% who did not give permission to release their records arenot available for comparison, the characteristics of this group remain unknown.Refusal to grant permission for release of records creates an inexorablenoncoverage problem, and a limitation of this study.Of the remaining 23,428 graduates, 127 were from the Yukon. They weretreated as foreign elements and eliminated from the population. Thus, the framepopulation consists of 23,301 Grade 12 graduates.112Sampling StrategyThe frame population was divided into two groups according to post-secondary status (participant and non-participant) as identified by the Link FileData Base. Each of these groups was then stratified by geographic location andeligibility for admission to university. Criteria used to divide the sampleaccording to post-secondary status and stratify by geographic location andeligibility for university admission are explicated in the following sections.Post-secondary status. The Institutional File of the Link File Data Base wasused to determine the post-secondary status of the frame population. Participantswere defined as those students registered in one of the following post-secondaryinstitutions according to the Link File as of October 1, 1988; non-participantswere defined as those not registered in one of these institutions:Community Colleges: Camosun, Capilano, Cariboo, New Caledonia, Douglas, EastKootenay, Fraser Valley, Kwantlen, Malaspina, North Island (Comox, Port Alberrii,Courtenay, Campbell River), Northern Lights, Northwest, Okanagan, Selkirk (Castlegar,Rosemont), Vancouver Community (Langara, King Edward, Continuing Education,Vancouver Vocational Institute).Institutes and Vocational Schools: British Columbia Institute of Technology, Emily CarrInstitute of Art, Open Learning Institute, Pacific Marine Training Institute.Universities: University of British Columbia, Simon Fraser University, University ofVictoria, Trinity Western University. (British Columbia Research Corporation, 1990a)Students attending institutions outside this list (e.g. students attending out ofprovince institutions or private post-secondary institutions) were classified asnon-participants for the purposes of this survey as were those students whocommenced their studies after October 1, 1988. This created an inevitable source113of error in correctly identifying participants and non-participants (see BritishColumbia Research Corporation, 1990a).Geographic region. Geographic regions in this study were definedaccording to categories used in many other studies on post-secondary students inBritish Columbia (e.g. Ministry of Advanced Education and Job Training,1986).The geographic regions include:Metropolitan Region - This grouping includes school districts which are largemetropolitan cities or centres (School Districts 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 48,61, 62, 63, 64).Urban/Rural Region - This grouping includes school districts which are either located inthe interior of the province or on Vancouver Island. They generally include communitieswhich are moderate in size and typically have a mixture of urban and rural settlements.These districts are located closer to the Lower Mainland than those in the Remote Regiongrouping. (School Districts 14, 15, 16, 17, 19, 21, 22, 23, 24, 26, 27, 28, 29, 30, 31, 32, 33, 34, 47,55, 56, 57, 65, 66, 68, 69, 75, 76, 77, 89).Remote Region - This grouping indudes school districts which have relatively smallpopulations, typically scattered in small communities. All are located quite remote fromthe Lower Mainland area of the province. (School Districts 1, 2, 3, 4, 7, 9, 10, 11, 12, 13, 18,49, 50, 52, 54, 59, 60, 70, 71, 72, 80, 81, 84, 85, 86, 87, 88, 92). (British Columbia ResearchCorporation, 1990a)Eligibility for university admission. Eligibility for admission to universitycategories were constructed by calculating students’ grade point averages basedon eligibility for admission to the University of Victoria. Those students withoutthe requisite courses for university entrance, regardless of their academicstanding in high school, were assigned a score of 0. Students were then allocatedto eligible, borderline, or not eligible categories based on the followingdefinitions:Eligible: Grade point average of 2.5 or greater.Borderline: Grade point average between 2.0 and 2.4.Not eligible: Grade point average of less than 2.0.114The stratification scheme for the frame population is represented in Table5. Figures in parentheses indicate the percentage of the population in a particularstratum; for example, the 3,818 individuals belonging to the stratum defined asmetropolitan and eligible for university admission represent 31.7% of the framepopulation of participants.Table 5.Frame Population of the 1988 Grade 12 Graduates(as determined by the Link File).Post-secondary ParticipantsGeographic Eligibility for University AdmissionRegionEligible Borderline Not Eligible Total% % % %Metropolitan 3,818 (31.7) 686 (5.7) 2,704 (22.4) 7,208 (59.8)Urban/Rural 1,441 (12.0) 284 (2.4) 1,588 (13.2) 3,313 (27.5)Remote 667 ( 5.5) 121 (1.0) 740 ( 6.1) 1,528 (12.7)Total 5,926 (49.2) 1,091 (9.1) 5,032 (41.7) 12,049 (100.0)Post-secondary Non-participantsGeographic Eligibility for University AdmissionRegionEligible Borderline Not Eligible Total04 % % %Metropolitan 1,413 (12.6) 433 (3.8) 4,332 (38.5) 6,178 ( 54.9)Urban/Rural 692 ( 6.2) 190 (1.7) 2,619 (23.3) 3,501 ( 31.1)Remote 313 ( 2.8) 87 (0.8) 1,173 (10.4) 1,573 ( 14.0)Total 2,418 (21.6) 710 (6.3) 8,124 (72.2) 11,252 (100.0)115Sample SelectionA probabilistic sampling strategy was used to generate the survey samplefor this study. That is, each unit in each stratum of the frame population had anonzero probability of being selected into the sample. The sample was generatedby making distinct systematic selections19,commencing from a random start,within each stratum. According to the British Columbia. Research Corporation(1990), the rationale for the differential sampling fractions for each stratum wasto “yield as many students as possible in the ‘Borderlin& [university eligibility]category and in the ‘Remote geographic region. . . , yet still maintain a reasonableoverall balance to the sample” (p.7). Table 6 describes the total numbers sampledand the sampling fractions in each stratum.19 Kish (1965) warns that monotonic trends and periodic fluctuations of the data may result in aspuriously high computed variance when systematic sampling is employed. Individual recordsused to generate the sample for this study, are sorted and stored in the Link File Project data baseby provincial examination identification number. Neither periodic trends or periodic fluctuationsof the data are problematic in this study.116Table 6.Sample Size and Sampling Fractions by Stratum.Post-secondary ParticipantsGeographic Eligibility for University AdmissionRegionEligible Borderline Not Eligible Total%* % % %Metropolitan 1,025 ( 26.8) 390 ( 56.9) 548 (20.3) 1,963 (27.2)Urban/Rural 1,112 ( 77.2) 284 (100.0) 619 (39.0) 2,015 (60.8)Remote 667 (100.0) 121 (100.0) 590 (79.7) 1,378 (90.2)Total 2,804 ( 47.3) 795 ( 72.9) 1757 (34.9) 5,356 (44.5)Post-secondary Non-participantsGeographic Eligibility for University AdmissionRegionEligible Borderline Not Eligible Total% % % %Metropolitan 371 ( 26.3) 249 ( 57.5) 875 (20.2) 1,495 (24.2)Urban/Rural 524 ( 75.7) 190 (100.0) 1,096 (41.8) 1,810 (51.7)Remote 313 (100.0) 87 (100.0) 939 (80.1) 1,339 (85.1)Total 1,208 (50.0) 526 ( 74.1) 2,910 (35.8) 4,644 (41.3)* Sampling fractions in parenthesesIn total, 44.5% (n=5,356) of the participants and 41.3% (n=4,644) of the non-participants, representing 42.9% of the frame population, were included in thesurvey sample.Questionnaire Development and Data CollectionThe questionnaire used in this survey was developed by a working groupof individuals representing the following institutions: Ministry of AdvancedEducation and Job Training, Ministry of Education, British Columbia ResearchCorporation, British Columbia Institute of Technology, the University of British117Columbia20,and Vancouver Community College. The penultimate draft of thequestionnaire was piloted with three geographically disparate Grade 12 classesand one first year class of university students. The final questionnaire wasprepared in booklet form and consisted of three sections for a total of 24questions. Section A was to be completed by respondents who were non-participants in post-secondary education, and Section B by participants. SectionC was to be answered by all respondents. The maximum number of questions tobe answered by any respondent was 21. At the end of the questionnaire, studentswere invited in an open-ended question, to comment on any aspect of theeducational system.The self-administered mail questionnaire, along with a postage-paidenvelope and introductory letters by B.C. Research, the Ministry of AdvancedEducation and Job Training, and the Ministry of Education, was sent to eachindividual in the sample. The first questionnaires were mailed on May 5, 1989,followed by a postcard reminder to the total sample on May 12, 1989. On June 2,1989, all non-respondents were sent a second questionnaire. A copy of thesurvey questionnaire and postcard reminder, can be found in Appendix A. Forfurther details of sampling, mail follow-ups and response rates, see BritishColumbia Research Corporation (1990a).Response RateOf the 10,000 individuals included in the sample, 5,345 responded,resulting in an overall response rate of 53.5%. When the 728 undeliverablequestionnaires are eliminated from the sample, the adjusted response rate was57.7%. The survey respondents for this study, those who responded to the20 was one of two members representing the University of British Columbia.118questionnaire, are described in Table 7. Figures in parentheses indicate thepercent response rate within each stratum.Table 7.The Survey Respondents(Response Rate).Post-secondary ParticipantsGeographic Eligibility for University AdmissionRegionEligible Borderline Not Eligible Total% % % %Metropolitan 638 (62.2) 205 (52.6) 281 (51.3) 1,124 (57.3)Urban/Rural 760 (68.3) 155 (54.6) 319 (51.5) 1,234 (61.2)Remote 450 (67.5) 82 (67.8) 310 (52.5) 842 (61.1)Total 1,848 (65.9) 442 (55.6) 910 (51.8) 3,200 (59.7)Post-secondary Non-participantsGeographic Eligibility for University AdmissionRegionEligible Borderline Not Eligible Total% % % %Metropolitan 216 (58.2) 101 (40.6) 354 (40.5) 671 (44.9)Urban/Rural 298 (56.9) 95 (50.0) 460 (42.0) 853 (47.1)Remote 179 (57.2) 45 (51.7) 397 (42.3) 621 (46.4)Total 693 (57.4) 241 (45.8) 1,211 (41.6) 2,145 (46.2)Representativeness of the SampleRepresentativeness of the sample was determined in several ways. First,the overall response rate was compared with response rates of other studieswhich were similar in nature. Second, the survey population was compared to119the frame population. Third, within the survey sample, characteristics ofrespondents and non-respondents were examined.Overall Return RateNon-response has been identified as a persistent problem in studies whichuse survey questionnaires (Kish, 1987; Miller, 1977; Wallace, 1954). Miller (1977)indicates that a response rate of less than 50% is typical in mail questionnaires(p.7’9). Heberein and Baumgartner (1978), in an analysis of 80 published studiesusing mail questionnaires, found that in 50% of these studies, the response ratewas less than 61% and in 25% the response rate was less than 41%.As discussed in the previous section, the overall return rate for this studywas 53.5%. Of those identified as participants in the sample, 59.7% responded.This figure represents 26.5% of the frame population. Of the sampled non-participants, the response rate was 46.2%, or 19.1% of the frame population. Inother words, the survey population for this study includes over 1 of every 4graduates identified as participants in post-secondary education, and almost 1 in5 graduates deemed a non-participant by the Link File Project data base.The overall response rate is not unlike other studies of this nature. In afollow-up study of Grade 12 graduates, Alberta Advanced Education (1989)reported an overall response rate of 62%. In her study of a cohort of Grade 12graduates from one British Columbia school district, Bellamy (1988) achieved anoverall response rate of 45%. Dennison et al. (1975) report a 56% response rate ina survey of students who had entered post-secondary schools.Given the high initial sample size and a response rate comparable to otherpost-high school follow-up studies, it can be argued that the overall response rateis reasonable. Several authors warn, however, that non-response introduces the120possibility of a biased sample; that is, the respondents to the questionnaire maynot be representative of the intended survey sample (Denzin, 1989; Wiersma,1986; Wallace, 1954). Information contained in the Link File Project data baseallows for a comparison of the frame population with the survey population andseveral of the characteristics of respondents and non-respondents.Frame Population and Survey RespondentsA comparison of the frame population, survey sample, response rate, andsurvey respondents within each stratum is summarized in Table 8. By way ofillustration, the table may be read as: in the metropolitan, eligible for universityadmission, participant group, the population size was 32% (3,818) of the totalframe population (A), the sampling fraction was 27% (1025) (B), the response ratewas 62% (638) (C), which represents 20% of all respondents belonging to theparticipant group (D). Finally, the percent difference between the framerespondents of this stratum (32%) and the survey respondents (20%) was -12%(E).In 11 of the 18 strata, oversampling resulted in the survey respondentsample proportion exceeding the frame population proportion. In theparticipant/metropolitan/borderline stratum, oversampling resulted in thesurvey respondent sample proportion to equal the frame population proportion.In 3 strata (participant, urban/rural, not eligible; non-participant, metropolitan,eligible; non-participant, urban/rural, not eligible), despite oversampling, thesurvey respondent sample proportion is slightly less than the frame populationproportion. This may be due to a relatively low oversampling fraction and/or alow response rate in these strata. The participant, metropolitan, eligible stratum isTable 8Frame Population (A), Sampling Fractions (B),Response Rate (C), Survey Respondents (D), Percent Differencebetween the Frame Population and Survey Respondents(E)ParticipantsEligibility for University AdmissionEligible Borderline Not Eligible TotalGeographicRegionNon-participants0/0Metro.Urban/RuralRemoteTotalA B CD E13 26 58 10 (- 3)6 76 5714 (+8)3100 57 8 (+5)22 50 57 32 (+10)A BCDE4 58 41 5 (+1)2 100 50 4 (+2)1 100 52 2 (+1)6 74 46 11 (+5)A B CD E39 20 41 17 (-21)23 424221 (-2)10 80 42 19 (+9)72 36 42 56 (-16)ABC D E55 24 45 31 (- 24)31 52 47 40 (+ 9)14 85 46 29 (+15)100 41 46 19A - percentage of the frame populationB - sampling fractionC - response rateD - percentage of respondentsE - percent difference between frame and survey respondents121GeographicRegionA B CD E ABCDE ABCD B ABCD E%Metro. 32 27 62 20 (-12) 6 57 53 6 ( 0) 22 20 51 10 (-12) 60 27 57 35 (-25)Urban/Rural 12 77 68 24 (+12) 2 100 55 5 (+1) 13 39 52 10 (- 3) 28 61 61 39 (+11)Remote 6 100 68 14 (+ 8) 1 100 68 3 (+2) 6 80 53 10 (+ 4) 13 90 61 26 (+13)Total 49 47 6658 (+9) 9 73 5614 (+5) 4235 5228 (-14) 10045 6027EligibleEligibility for University AdmissionBorderline Not Eligible Total122underrepresented in the survey respondent sample because of undersampling. In3 other strata (participant, metropolitan, eligible; participant, metropolitan, noteligible; non-participant, metropolitan, not eligible), a combination ofundersampling and low response rates resulted in larger discrepancies betweenthe frame population size and the survey respondent sample proportion. Overall,in both the participant and non-participant sample, the metropolitan region forall eligibility for university admission categories and the urban/rural region inthe not eligible for university admission category are underrepresented.Response rates of individual strata range from a high of 68% to a low of41%. In each stratum, response rates of non-participants were lower than in thecorresponding stratum of participants. Also, the more likely ones eligibility foruniversity admission, the greater the response rate. It appears that low responserates in some strata are a result of perceived low salience of the survey topicrather than faulty questionnaire design and mailout procedures. As described inthe section on questionnaire development and data collection, proceduresrecommended in the survey questionnaire literature (Heberlein & Baumgartner,1978; Miller, 1977; Dillman et al., 1974) were followed to increase the responserate. That is, the questionnaire was prepared in booklet form, the length of thequestionnaire was deliberately brief, respondent anonymity was assured,postpaid return envelopes and introductory letters explaining the importance ofthe study were included, letters from the Ministry of Education and Ministry ofAdvanced Education and Job Training were signed by their respective deputyministers (i.e. government sponsored), and three mailings including one postcardreminder were sent. Other measures, such as a fourth mailing by registered mail,telephone follow-up, and the use of incentives, may have increased the responserate (Heberlein & Baumgartner, 1987; Miller, 1977; Dillman et al., 1974). From a123cost perspective, however, the size of the survey sample prohibited this type offollow-up.As Heberlein and Baumgartner (1987) point out, when questionnaires aredeemed to be salient, they are more likely to be returned. They also found thatstudents, compared with the general population, are more likely to respond toquestionnaires. This may explain higher response rates in the participant andeligible for university admission groups.In order to detect the possibility of response bias due to non-response, onefurther comparison, - between respondents and non-respondents - can be made.Respondents versus Non-respondentsThere are two types of non-respondents to the questionnaire. The first typeof non-respondent is comprised of those individuals to whom questionnaireswere not delivered. Of the 10,000 questionnaires mailed, 728 (7.3%) werereturned undelivered. The second type of non-respondent includes thoseindividuals who chose not to participate in the study. Of the Grade 12 graduatessurveyed in this study, 4655 (46.5%) belong to the second group.Using Link File Project data, respondents, non-respondents, and the‘undelivered group in each stratum were compared on the following dimensions:age, sex, college region, school district, and eligibility for university admission ascalculated according to the requirements of the each of the following universities:University of British Columbia, Simon Fraser University, and the University ofVictoria.Appendix B provides a detailed account of differences, including chisquare tests, of these dimensions among respondents, non-respondents, and124undelivered. These results are summarized in Table 9. Significant differences arenoted below; however, the largest effect size (an expression of the magnitude ofthe difference between means, Glass & Hopkins, 1984) is .44 and in 62% of thesignificant differences noted in Table 9, the effect size does not exceed .30. Thissuggests that in the majority of cases, the magnitude of the difference is small.Significant differences are evident between groups on several variables, asindicated in Table 9. In the participant group, respondents tend to be younger,female, and have higher than average grade point averages. Non-respondents aregenerally older, male, and have lower grade point averages. Differences in gradepoint average are particularly evident among the eligible for universityadmission group. Only in the urban/rural region are significant differencesnoted within the eligible for university admission category. Respondents aremore likely to be eligible for entrance at all three British Columbia universities;non-respondents are less likely to qualify for university entrance.Few significant differences arise in the non-participant group. It isinteresting to note, however, that the highest number of differences are detectedin the participant urban/rural group, and no differences are evident in the nonparticipant urban/rural group. In all but one instance, no significant differencesas determined by chi-square (p<.O5) are noted between respondents and nonrespondents by geographic location or college region. Significant differences(p<.O5) were detected in the non-participant, eligible for university admission,remote stratum. Response rates for this stratum by college region are as follows:125Table 9.Respondents and Non-respondents - Significant DifferencesBy Geographic Region and Eligibility for University Admission.Participants Non-participantsEligible Borderline Not Eligible Borderline NotEligible EligibleMETROPOLITANage *sex ** *** * *U.B.C. eligibility - - -U.B.C. gradeU.Vic. eligibility - - -U.Vic grade *S.F.U. eligibility - - -S.F.U. grade *college regionschool districtURBAN/RURALage **sexU.B.C. eligibility * - - -U.B.C. gradeU.Vic. eligibility *** - - -U.Vic. grade **S.F.U. eligibility ** - - -S.F.U. grade *college regionschool districtREMOTEagesex** * *U.B.C. eligibility - - -U.B.C. gradeU.Vic. eligibility - -U.Vic. grade *S.F.U.. eligibility - -S.F.U. gradecollege region *school district* significant at p < .05** significant at p < .01significant at p < .001-not applicable126n 179 110 24 313% 57.2 35.1 7.7 100respondents non-respondents undelivered row%totalEast Kootenay 66.7 28.8 4.5 21.1North Island 39.3 49.4 11.2 28.4Northern Lights 68.4 26.3 5.3 18.2Northwest 64.0 26.0 10.0 16.0Selkirk 56.9 37.3 5.9 16.3100.0%The North Island college region has a high rate of non-response and undeliveredquestionnaires, and East Kootenay and Northern Lights college regions have ahigh rate of response. While Northwest college region has a high rate of response,the number of undelivered questionnaires is high.In some instances, discrepancies between the frame population percentageand the percentage of respondents in the survey population appear to beassociated with the number and level of significant differences within strata. Forexample, in the urban/rural, eligible, participant stratum, the survey populationis 12% higher than the frame population (as reported in Table 8). This stratumalso has the highest number of significant differences between respondents andnon-respondents. In other strata (e.g. eligible, urban/rural, non-participant),discrepancies between the two populations do not result in significantdifferences.Tables 10 and 11 show these findings by comparing mean values of thevariables used to compare the groups. Consistent with the findings in AppendixB, mean values demonstrate that respondents and non-respondents differ verylittle across strata in age, sex, and grade point average. The ‘undelivered grouphas a slightly higher proportion of females. There does not appear to be any otherconsistent differences, across strata, in this group, which suggests that theincidence of undelivered questionnaires occurs randomly in this sample.Table10ComparisonofMeanValues-RespondentsandNon-respondentsByGeographicRegionandEligibilityforUniversityAdmissionPost-secondaryParticipantsUniversityEligibleEligibilityBorderlinerespondentnonresp-undelivondentableNotEligiblerespondentnonresp-undelivondenterablerespondentnonrespondentMETROPOLITAN 63862.2xn % agesextU.B.C. gr.U.Vicgr.S.F.U.gr.33833.0S518.1.441.5.502.8.692.9.703.0.4520552.6 x18.0.401.6.503.0.503.0.723.0.5016241.5S23 5.95URBAN/RURAL18.2.451.65021.491.9.5420.32n760291%68.326.218.2.4018.3.691.4.491.5.512.1.471.9.771.9.491.8.7520.2621.2261 5.528151.3518.3.561.6.50.1.39.1.35.1.39515554.6sundeliverable49 4.8S18.0.281.7.482.9.753.0.783.1.49518.2.501.6.502.8.8428.8529.5629 4.35S18.2.351.5.513.0.3329.392.9.39230420518.3.611.4.49.2.52.1.45.2.22S10737.7x37 6.8518.2.541.5.51.1.37.1.35.1.35S522 7.7531951.5S265428agesexU.B.C.gr.U.Vic.gr.S.F.U.gr.REMOTEn % agesexU.B.C. gr.U.Vic.gr.S.F.U.gr.518.0.3018.1.351.6.491.4.503.0.5629.453.0.6229.523.0.522.9.4945018867.528.2S18.0.3218.0.331.6.491.5.503.1.4929.623.0.5329.643.1.4929.4935 5.718.1.3618.1.4218.1.4218.2.4518.4.6218.3.631.6.491.5.501.5.511.6.491.4.491.5.5121.4521.3921.14.1.36.1.37.1.281.9.4620.461.9.26.1.33.1.35.1.2620.2620.321.9.26.1.33.1.35.1.268267.8 x3226.4S7 5.8S31053.5S23439.7 x46 7.8S18.2.4918.2.3718.3.4918.2.5118.4.5918.3.651.6.491.4.491.3.491.6.501.5.501.6.492.1.301.9.6321.14.1.46.1.46.1.451.9.491.8.6320.28.1.40.1.39.1.331.9.4520.2220.28.1.40.1.39.1.335tInthistable,sexwasmeasuredaslmale,2’female.Table11ComparisonofMeanValues-RespondentsandNon-respondentsByGeographicRegionandAcademicStandingPost-secondaryNon-partldpantsUniversityEligibleBorderlineNotEligibleEligibilityrespondentnonresp-undellv-respondentnonresp-undeliv-respondentnonresp-undelivondenterableondentableondenterableMETROPOLITANn216120351011262235443091%58.232.39.440.650.68.840.549.110.4sCsXsXsXsCsCssXsage18.0.4118.1.3718.0.4918.1.4018.1.4217.9.4218.3.6418.4.6018.3.61sext1.6.491.5.501.5.261.6.501.4.491.6.501.6.501.5.501.5.50U.B.C.gr.2.8.782.7.842.9.722.1.502.0.481.9.66.1.25.1.32.1.22U.Vicgr.2.8.7128.872.9.701.9.461.9.561.8.62.1.20.1.30.1.22S.F.U.gr.2.9.553.0.473.0.492.0.3220.362.0.20.1.20.1.33.1.26URBAN/RURALn29818739957619460521115%56.935.77.450.040.010.042.047.510.5sCsCsXsXsXsXsXsXsage18.0.3918.0.4718.0.5418.1.3218.1.4418.2.5018.3.5718.4.6118.4.64sex1.6.501.4.501.5.511.6.501.5.461.5.511.5.501.5.501.5.50U.B.C.gr.3.0.572.9.5428.632.0.502.1.4622.17.1.32.1.26.1.17U.Vic.gr.3.0.5929.602.8.631.9.541.9.5220.24.1.63.1.24.1.14S.F.U.gr.3.0.5229.5229.4320.3220.352.0.24.1.30.1.24.1.14REMOTEn179110244539339747171%57.235.17.751.744.83.442.350.27.655CsXsXsCsXsXsCsXsage18.1.3918.1.3318.2.3918.2.4518.1.3018.0.0018.3.5618.4.6418.6.73sex1.5.501.5.501.4.501.6.481.4.501.7.571.5.501.5.501.4.50U.B.C.gr.3.0.4729.422.9.792.2.172.2.1422.14.1.26.1.32.1.30U.Vic.gr.2.9.612.8.6629.782.0.371.9.402.0.20.1.25.1.28.1.30S.F.U.gr.29.5728.663.0.4920.371.9.402.0.20.1.25.1.30.1.30c_iDfInthistable,sexwasmeasuredas1=male,2female.129Preparation of the Data SetThe data were received, on tape and in three files, from the BritishColumbia Research Corporation. The files consisted of 1) Grade 12 GraduateFollow-up Survey data (n=1O,000), 2) secondary school transcript data (n30,771)and 3) post-secondary institutional data (n5507). In order to construct acomplete data set for the 5345 respondents to the Grade 12 Graduate Follow-upsurvey, relevant information from the other files was extracted, matched bysurvey identification number to survey respondent data, and merged into onefile.Of the 5345 respondents to the Grade 12 Graduate Follow-up survey, 527cases were eliminated from the final sample. In 174 cases, either post-secondarystatus could not be determined, questionnaires were spoiled or technicalproblems existed. Those students attending post-secondary institutions (n=353)outside of British Columbia were also eliminated from the sample, as it was notpossible to determine which type of post-secondary institution they attended(that is, university or non-university). The final sample consisted of 4818 cases.SummaryIn this section of the chapter, I have endeavoured to evaluate the integrityof the sample by describing the target and frame population, stratification andsampling strategies, development of the survey instrument, data collection,response rates, the survey population, representativeness of the sample, andpreparation of the data set. This detailed description is provided to justify the useof data generated from the Grade 12 Graduate Follow-up survey questionnaire130and corresponding Link File Project data. Figure 12 provides a summary of thedifferent populations in this survey.All Grade 12 graduateswith characteiistics Inferential Populationsimilar to the surveyrespondent sampleIndudes all Grade 12 Taiet Populationgraduates in the 1988cohort in British 28,677ColumbiaNot induded ai 5,247 Frame Populationwho nfused release of 23 428of their records and 127Yukon graduatesIndudes 5,356 (44.5%)participants and 4,644 10 000Survey Sample(41.3%) non-participantsin post-secondaryeducation___________________________________Not induded ai Survey Respondentsnon-respondents and728 undeliveredquestionnairesFigure 12. Topulation.c aiu[Samp(e.c e[evrnt to the nzd 12 Qraduate To1Tow-upSurveyIn the ideal study, survey respondents would be representative of thetarget population, randomly selected, and free from bias. Kish (1987), however,indicates that “for most surveys it is difficult or impossible to make the samplesentirely representative of the desired populations. Beyond sampling variationsare the diverse divergences that may bias the selection, such as defective framesand nonresponses” (p.28).131In order to alert the reader to a less than ideal, but nevertheless reasonable,representation by the survey respondents of the target population, thepopulations and samples in this study have been described in considerable detail.Findings of this study will be interpreted with these caveats in mind. However,given that 1988 Grade 12 graduates from the entire province were surveyed, thesize sample is considerably large, and that secondary and post-secondaryinstitutional data bases have been linked to the survey questionnaire data, thisdata base offers a unique opportunity to examine the choices individuals makeregarding post-high school destinations.In the next section, the interview sample for this study, including schooland student selection, the interview procedure, and representativeness of theinterview sample is described.Interviews with Grade 12 StudentsThe third source of data in this study involved interviews with Grade 12students who were in the process of making decisions regarding post-high schooldestinations. The purpose of the interviews was to 1) determine the post-highschool plans of the sample of students, and 2) to explore in depth students’perceptions of the processes underlying their decisions in choosing post-highschool destinations. In the following section, selection of school districts,secondary schools, and students is described, and the interview procedure isexplained.132The SampleSelection of SchoolsA multisite approach was adopted in this part of this study. A purposiveor judgment sampling strategy was used to select three schools in which toconduct the interviews. According to Kish (1965), such a strategy is preferred torandom selection when a research project must be limited to a few locations. Theaim of the selection strategy was to ensure that one metropolitan, oneurban/rural, and one remote school, each typical or modal of the category, wasincluded in the study.After tentative selection of three school districts, permission to conductresearch was requested by letter to each district superintendent (Appendix C).Secondary schools deemed appropriate for the interviews were then selected bythese superintendents. Each of these schools is described in the following section.Metropolitan School (MSS). MSS, the metropolitan school for this study, islocated in the Vancouver College Region and in a school district with more than50,000 students. In 1989/ 90, approximately 1650 students enrolled were in grades8 to 12 at MSS. This number includes a total of 349 students enrolled in Grade 12(156 males and 193 females). MSS offers a full range of courses including careerpreparation programs in Business Education and Auto Mechanics. There wereapproximately 30 Grade 12 students enrolled in the business education programand 14 in the auto mechanics program.One university, one community college, and two public institutes arelocated in the Vancouver School District. In addition, within easy commutingdistance from MSS are two universities, three community colleges and two publicpost-secondary institutes.133Remote Secondary School (RSS). RSS, the remote school in this sample, islocated in the the Northwest College region of British Columbia, approximately1200 km. north west of Vancouver. RSS is located in a small town ofapproximately 5000, and in a school district with less than 3000 students.Approximately 560 students attend grades 9 to 12 at RSS. There were 98 students(46 male, 52 female) enrolled in Grade 12 in 1989/90. This school did not offercareer preparation programs.A very small satellite of Northwest Community College is located in thesame town as RSS. In the 1988/89 year, only one high school graduate entereddirectly into the university transfer program at this satellite college. The other 23students enrolled in university transfer courses were described as older students.The main campus of Northwest College in Terrace is over 200 kilometers away.The College of New Caledonia in Prince George is 400 kilometers east of RSS.Urban/Rural Secondary School (URSS). URSS, the urban/rural secondaryschool, is located in the Okanagan College Region in a town of 20,000 people andin a school district size of about 8000. Approximately 1200 students attendGrades 8 to 12 at URSS, with 264 students (128 male, 136 female) in Grade 12.Career preparation programs are available in Mechanics, Hospitality and Foods,and Commercial Art and enrol 12 students in total.A branch of the Okanagan College is located approximately 3 kilometersfrom URSS. The first two years of university equivalent courses are offered at thisbranch. In 1989/90, the Kelowna campus of Okanagan College, located 50kilometers from URSS, became a degree-granting university college. Degreeprograms are available in arts, science, education, and nursing. Cariboo Collegein Kamloops is located approximately 120 kilometers from URSS.134Student SelectionA purposive sampling strategy was also used to select interviewees, basedon the recommendations of school guidance counsellors. In each school, a slightlydifferent method of eliciting student volunteers was carried out by the guidancecounsellor responsible for the task. Student participants were selected for thisstudy based on their 1) willingness to participate in the study (see consent forms,Appendix C), 2) eligibility to graduate from Grade 12 in June 1990 and likelihoodof doing so, and 3) ability to contribute to an understanding of the processes ofeducational choice. Guidance counsellors were asked to ensure that the sampleincluded students who were not likely continue to post-secondary education aswell as those who were likely to continue.MSS. At MSS, a call for interviewees was announced at a school assembly.In total, 15 students, 9 females and 6 males, participated in both sets ofinterviews.ESS. Every third student on the Grade 12 class list (ranked according tograde point average), for a total of 25, was invited to participate in the interviews.Of this number, 16 students (12 females and 4 males) participated in the first setof interviews. Fourteen of the original 16 interviewees were re-interviewed inMay 1990. Of the 2 students who did not participate in the second set ofinterviews, one had dropped out of school and the other was participating in aGrade 12 exchange program in South America. A second student had alsodropped out of high school, but was re-interviewed in May.URSS In order to recruit interviewees at URSS, counsellors approachedclasses of Grade 12 English students. Twenty students (12 females, 8 males)participated in the first set of interviews and 17 of the 20 were re-interviewed inMay 1990. Of the 3 students not available for the second interview, two had135dropped out of school and one was in hospital. One of the remaining 17 studentshad dropped out of high school, but agreed to be re-interviewed.Interview ProcedureTwo sets of face-to-face, semi-structured interviews, approximately onehour in length, were conducted with the student participants from each school.The first interviews21 were conducted in November 1989. At this time, 51interviews (with 33 females and 18 males) were completed. The purpose of theseinterviews was to 1) discuss students post-high school plans, 2) determine theroles of cultural, social, and academic capital, dispositions toward and beliefsabout post-secondary education in the transition process, and 3) detail howstudents perceived the processes behind their decisions. While questions guidingthe interviews were based on the theoretical framework of this study (seeAppendix C) as described in Chapter 4, student participants were encouraged todiscuss decision making, post-high school destinations, and the transition periodin their own ‘voices’ and within their own personal contexts (Mishler,1986). Thus,the form used was that of the non-scheduled or focused interview (Denzin, 1989).All interviews were taped, and typed transcripts were prepared from the tapes.In preparation for the second interview, each student participant wasgiven a copy of the transcript of her/his initial interview. Discussion of thetranscript served as a starting point for the follow-up interview, allowed theinterviewer and interviewee to work as research collaborators in a joint effort tounderstand the previous interview and plan for the second stage of the study,and gave interviewees a “voice in the interpretation and use of the findings”(Mishler,1986, p. 127; 132). The purpose of the follow-up interviews was to: 1)21 In September 1989, the interview questions were piloted with both individual students and agroup of students who were not otherwise a part of this study.136verify the data obtained in the initial interviews and explore more fully thethemes arising from the initial interviews, 2) to determine what strategies andactions individuals have taken since November 1989 to prepare for the transitionfrom high school, 3) discuss reasons for their plans and actions, and 4) explore infurther depth their perceptions of the processes behind their decisions aboutpost-high school destinations. Typed transcripts were prepared from the secondset of tapes.In October 1990, interviewees (or their parents) were again contacted, bytelephone, to ascertain their actual post-high school destinations. In total, 44 ofthe original 51 students were contacted. Table 12 summarizes the interviewsample, for each contact period, by sex and geographic location.Table 12.Interviewees by Sex and Geographic Location.Urban/Remote Rural Metro TotalOctober 1989Female 12 12 9Male 4 8 6Total 16 20 15 51May 1990Female 10 10 9Male 4 7 6Total 14 17 15 46October 1990Female 10 10 9Male 3 7 6Total 13 16 15 44Of the 44 individuals contacted in October 1990, 10 were attendinguniversity, 13 were attending a community college22,15 were employed (9 fulltime, 6 part-time), 2 were unemployed, 3 were participating in travel/exchangeOf these 13 students, 11 were attending the community college nearest to their high school.137programs (other), and 1 had returned to high school to complete graduationrequirements. Actual post-high school destinations of the interviewees, by sex,are summarized in Table 13.Table 13.Interviewees by Sex and Post-high School Destination.Non F/T P/t Unem- Back RowUniv. Univ. Work Work Other ployed to h. s. TotalOctober 1990Female 9 6 6 4 3 2 0 30Male 4 4 3 2 0 0 1 14Total 13 10 9 5 3 2 1 44Representativeness of the Interview SampleIn order to capture the choices made by a range of potential universityparticipants, non-university participants, and non-participants, every effort wasmade to interview a wide variety of students. Since a purposive samplingstrategy was employed, it cannot be claimed that the interview sample isrepresentative of the British Columbia Grade 12 student population. Theinterview sample is representative only insofar as the interviewees arerepresentative of other British Columbia Grade 12 students from similargeographic locations. However, when compared with Statistics Canada data forBritish Columbia (Standing Senate Committee on National Finance, 1987) theinterview sample, at least in terms of post-high school destination directlyfollowing high school, appears to be reasonably representative. According toStatistics Canada, 17% of British Columbia high school graduates continueddirectly to university, 29% to community college, and 55% were non-participants.In my sample of interviewees, 23% continued to university, 30% to communitycollege, and 48% were non-participants.138Preparation of the Interview DataApproximately 1500 typed transcript pages were prepared from the 97taped interviews, and from these transcripts a detailed coding scheme wasgenerated. A coding scheme was generated using the technique of constantcomparative analysis (Glaser & Strauss, 1967; Goetz & LaCompte, 1984). Thisscheme was guided by the theoretical framework as depicted in Figure 11(Chapter 4).In order to preserve the individuality of the student while protectingher/his identity, each interviewee was given a pseudonym. If the students ownname reflected her or his cultural or ethnic background, a comparablepseudonym was chosen.While a multisite approach was used in the collection of interview data,the primary unit of analysis is the individual. That is, I have focussed on how theindividual, within a particular context, perceives and makes sense of thetransition from high school. However, when perceptions vary by geographicalregion or gender, the context or ascriptive attributes are taken into account.Reliability and Validity of the Interview DataIn order to enhance the credibility of the interview data, the tenets ofreliability and validity for qualitatitve data, as provided by Goetz and LaCompte(1984), were followed. The foregoing description of school and sample selection,and interview schedules and procedures provide guidelines for the replication(comparability) of this analysis. Chapter 2 included a detailed description of theeducational and societal contexts in which decisions by these interviewees139regarding post-high school destinations took place. In Chapter 4, the theoreticalconstructs used to analyse these data are clearly delineated.Two strategies specified by Goetz and LaCompte (1984) were used toreduce the threat to internal validity of the interview data. These strategiesincluded the use of low-inference descriptors and mechanically recorded data. InChapter 9, frequent citation of low-inference descriptors, in the form of directquotations, provide principal support for the claims made and conclusionsdrawn. The use of a tape recorder ensured that the interview data were preservedin their original form.In this study, the effects of history and maturation were accounted for byconducting two sets of interviews, with a seven month interval, with the same setof students. The transcript of her or his first interview was shared with theinterviewee. Five months following the second interview, a telephone follow-upwas carried out. The validity of reports provided by interviewees was furtherenhanced by the use of effective communication and interviewing techniques,such as perception checking and reflection (Adler & Towne, 1984; Egan, 1982). Amultisite approach was adopted to reduce the effects of distortion of results dueto selectivity (Goetz & LaCoinpte, 1984).SummaryIn this section, I have described the interview sample for this study.Selection of school districts, secondary schools, and students was described, andthe interview procedure and representativeness of the sample were discussed.The data sources used in this study are summarized in Figure 13. Thisstudy considers choices made by a large sample of recent high school graduates,140as reported on Grade 12 Graduate Follow-up survey questionnaire and enrichedby corresponding Ministry of Education Link File Project data, and two sets ofintensive, focused interviews with a sample of Grade 12 students who were inthe process of making choices about post-high school destinations. In doing so,depth and breadth are added to the examination of 1) the complex of individualand institutional influences of educational choice, 2) the processes which liebehind individuals decisions, and 3) perceptions of theses processes.Delimitations and LimitationsDelimitationsThis study was delimited to the examination of choices made by currentGrade 12 students and Grade 12 graduates in British Columbia. The participantgroup of the survey data set was further delimited to include only studentsattending post-secondary institutions in British Columbia.LimitationsLimitations of the frame population, sampling strategy, response rates,and representativeness of the survey population have been described in thischapter. The interview sample was drawn from only one school in each of threegeographic locations (metropolitan, urban/rural, and remote) in BritishColumbia. Limitations related to the variables and their related measures arehighlighted in Chapter 6.1.-age sex-GPA-allgr.12graduatessampledandwhowereparticipantsininstitutionsrecordedinthisfile(n”5507)-institutionattended-majorprogramarea-disciplineclusterInterviewswithGrade12Students-interviewswithcurrentgr.12students(metro,urban-rural; remote)n51(Nov.89)n=46(May90)n=44(Oct.90)(telephone)41-post-highschoolplans-decisionmakingprocesses 44,Totalnumberofinterviews=51+46+44=141[Grade 12 Graduate Follow-up QuestionnaireIInstitutionalDataFile(linkfile)TranscriptDataFile(linkfile)-correspondingtranscript data(n30,771)-Sampleofgr.12graduates(n=10,000)collegeregion eligibilityn5345respondentsFinal Samplen4818Fiqiti13.Da*a Source.c.Chapter 6OBSERVED MEASURES, LATENT CONSTRUCTS, AND THEORETICALMEANINGTwo types of variables are used in the statistical analyses conducted inChapters 7 and 8. The purpose of this chapter is to provide a description of thesevariables.In Chapter 7, discriminant function analyses are carried out to determinewhether and which individual and institutional determinants of educationalchoice best predicts post-high school status. In these analyses, manifest orobserved variables, chosen on the basis of Härnqvists framework, are employed.The source of each variable is identified in Table 14. In Chapter 8, structuralequation modelling which employs latent constructs is undertaken to test thetheoretical model of Post-high School Status (Figure 11, Chapter 4). This type ofanalysis explores relationships among latent constructs or unobserved variables,as hypothesized in Chapter 4. Latent constructs are formed from the observedvariables used in the previous analyses. In Chapter 9, this theoretical model andits latent constructs, as depicted in Figure 11, are used as an organizingframework for an analysis of qualitative data generated from interviews withGrade 12 students.Depending on which theoretical approach is embraced, each observed orunobserved variable carries with it a particular theoretical meaning. Competingtheoretical interpretations, based on either rational choice theory and/orBourdieu’s Theory of Practice, as explicated in Chapters 3 and 4, are provided(where applicable) for each observed variable and each latent construct.142Table 14Determinants of Educational Choice and their Sources143Grade 12 Link FileVariable Graduate ProjectFollow- Data Base OtherupINDIVIDUAL DETERMINANTSStudent Characteristics1.Sex2. Educational Achievement3. Interests4. Expectations I5. Beliefsi. p.se. necessary to prepare me for a job Iii. p.s.e necessary to increase my income Iiii. p.s.e necessary to give me a wider choice of jobs IPersonal Environment6. Family SE. Backgroundi. mothers education III. fathers education Ilii. fathers occupation I7. Family Influencei. mothers influence Iii. fathers influence Iiii. influence of other family members I8. Peer Influence I9. School Climateiii. % Gr.12 honours in districtINSTITUTIONAL DETERMINANTSConditions Antecedentto Choice10. Curricular Differentiation ‘11. Guidance Organizationi. counsellors’ influence Iii. teachers’ influence ,Conditions Anticipated in theChoice Situation12. Geographic Availabilityi. distance from nearest university Iii. distance from nearest communty college ,13. Study Financei. total no. of awards received IDependent Variablesi. Participant/Non-participant Statusii. Post-secondary Institution Status Iffl. Post-high School Status ‘144This chapter is arranged as follows: A description of each determinant,following the sequence as specified by Härnqvist, is provided and the manifestor observed variables and their related measurement scales are described. Whena determinant, for example, family background, is modelled into a latent orunobserved construct, the latent construct and its related indicator variables aredescribed.This chapter commences with a description of the individual determinantsof educational choice and their associated measures. These individualdeterminants are discussed under the headings of 1) characteristics of theindividual, and 2) characteristics of the individual’s environment.Individual Determinants of Educational ChoiceAccording to Härnqvist (1978), research on individual determinants isessential in order to gain a thorough understanding of educational choice. In thefollowing section, characteristics of the individual are discussed under thefollowing headings: sex, educational achievement, curricular differentiation,interests, and expectations. One additional determinant -- beliefs -- which isrequired to determine the role of rational choice in educational decision making,has been included in this analysis. Measures of intellectual ability were notavailable for this data set.145Characteristics of the IndividualSexTraditionally, major studies on post-secondary participation, educationaland occupational attainment, and post-high school destinations, have excludedwomen from the analyses (Halsey, Heath, and Ridge, 1980; Sewell and Hauser,1975; Willis, 1977). Yet, findings related to participation and choice patternsbased on the results of these studies continue to be generalized to women. Forexample, in his introduction to Willis’ (1977) treatise on working class males,Aronowitz states “This is the enduring contribution of Learning to Labor: it helpsus understand that people.. . reproduce themselves in an antagonistic relation tothe prevailing culture and ideological practices” (p.xii). Women, however, werenot included as subjects of analysis in this study.Canadian women are now more likely than males to participate andsucceed in all levels of post-secondary education (Bellamy & Guppy, 1991). Inthose studies that do recognize gender differences, a growing body of evidencesuggests that the factors influencing women’s educational attainment aredifferent from those influencing that of men. For example, Rosenfield and Hearn(1982) found that women’s educational attainment is less strongly related toability and academic achievement but more strongly related to parents’socioeconomic status. Anderson (1988), in a study of the determinants ofeducational careers of both male and female college entrants, demonstrated thatfor women early goal commitment (measured as level of education expected,parents’ aspirations for the student’s education, and occupational aspirations)was the best predictor of educational attainment seven years after high schoolgraduation, and this predictor was particularly strong for women. She speculates146that early goal commitment may represent a more deeply instilled commitmentto career development for women.Similarly, Canadian studies have explored gender differences in thevariables that influence decisions about post-secondary participation andprogram choice. In relation to choice of program, Gilbert and Pomfret (1991) inthe context of making recommendations on the Canadian ScholarshipProgrammes (which are science and technology focused), claim that femalerecruitment to science is affected by “support from others, demonstrated academiccompetence, and self-assessment of self-management and interpersonalcompetencies” (p. 44). These factors are less consequential for male recruitment.While the primary purpose of my study is not that of gender, I endeavourto be sensitive to gender differences. In Chapter 7 analyses are first conductedwith the total sample, followed by separate analyses by sex. In chapter 8,separate analyses are conducted for males and females. The variable measuringsex (SEX) is coded “0” if male, and “1” if female.Educational AchievementEducational achievement is central to both rational choice theory andBourdieu’s Theory of Practice. If one adopts a practical rationality approach toexplain post-secondary participation, achievement is an important form ofevidence in deciding what to do. Evidence, in the form of achievement, shouldbe optimally related to what one believes, and in turn, relevant evidence shouldbe used to formulate beliefs. Thus, the relationship between achievement asevidence and beliefs is reflexive in nature.Achievement takes on quite a different meaning in Bourdieu’s Theory ofPractice. According to Bourdieu, members of the dominant class inculcate their147children with the very set of cultural resources required to achieve in school.These first-degree significations, embodied in the form of cultural capital, lead tosecond-degree significations, academic achievement. Academic achievement isthen objectified in the form of academic qualifications, and is available for use asacademic capital. Thus, academic qualifications are perceived as legitimatecompetence and remain unrecognized as the domestic transmission of culturalcapital.Educational achievement (GPA) was measured by calculating a gradepoint average for each student. A mean grade point average was calculated, fromLink File Data (see Chapter 5), using the following: Grade 11 social science,Grade 11 mathematics (one of algebra 11, introductory algebra 11, consumermathematics 11, technical mathematics 11, or introductory accounting 11), andthe score obtained on the Grade 12 provincial examination for English (eitherEnglish or communications).In Härnqvist’s schema of determinants of educational choice, curriculardifferentiation is located with the institutional determinants of educationalchoice (Table 14). It is useful, however, to consider curricular differentiationtogether with grade point average for a more complete portrayal of academiccapital.Curricular DifferentiationCurricular differentiation refers to the track or stream from which theindividual graduated. For respondents to this study, curricular differentiationwas not the result of rigid selection rules and sorting schemes. Instead, whenthese students were in Grade 10 they chose, with the help of counsellors andteachers, courses most suited to their interests, abilities demonstrated to date,148and planned educational and career path as formulated by this point in theirhigh school careers. Over the course of Grades 11 and 12, depending again oninterest, successful completion of courses, and evolving educational and careerinterests or disinterests, programs of study were followed, modified, mollified,or completely diverted23.For British Columbia high school graduates, curriculardifferentiation is an outcome of courses completed in high school, rather than aset trajectory.In this study, curricular differentiation is defined as either graduationwith the requirements for university entrance (sometimes referred to in thisstudy as an academic program), or graduation without these requirements (non-academic program), according to entry requirements for the University ofVictoria. For those without university entrance requirements, in all butexceptional cases, the path to university is truncated. The measure curriculardifferentiation (CURRDIFF) is coded ‘1” for possession of university entryrequirements, and ‘0’ for lack of these requirements.The latent construct academic capital in Figure 14 is hypothesized to becomprised of two manifest variables -- academic achievement (GPA) andcurricular differentiation (CURRDIFF).CURRDIFF GPA.Tigure 14. .f4caéemic Capital23 The intricacies of program planning by high school students are further developed in Chapter 9.149Hypothesized relationships among academic capital and the other constructs inFigure 11 are explicated in Chapter 4.Interests and ExpectationsAccording to practical rationality, action (i.e. post-secondaryparticipation) is explained by confirming whether it is the best way of fulfillingan agent’s desires, given one’s beliefs in relation to the available evidence. Inother words, action depends primarily on what one wants to do. Bourdieu’sTheory of Practice, however, posits that the conscious adjustment of aspirationsbased on assessment of one’s chances for success is really the result of longstanding, durable dispositions produced by the habitus. These dispositions,created as objective structures and personal history converge, result in theexclusion of improbable aspirations and actions from one’s repertoire of choices.In other words, the habitus as “history turned into nature” produces individualaction, of which choice of post-high school destination is one.Two variables, interests and expectations, provide insight into whatrespondents want in terms of education, and what they expect they willultimately achieve. The level of education desired or wanted (INTEREST) wasdetermined by asking “What is the highest level of education that you would liketo obtain?” and measured on a 6-point scale from “1” high school graduation to“6” graduate degree (master’s or doctorate Degree).Although Härnqvist did not specify expectations as an individualdeterminant, he argues that educational choice is a compromise betweenpreferences and expectations. Several other studies (Marjoribanks, 1988; Porter,Porter, and Blishen et al., 1982) consider expectations to be an important variable.Educational expectations were measured using the following question: “What is150the highest level of education that you erpect to obtain”, and measured on a 6-point scale from “1” high school graduation to “6” graduate degree (master’s ordoctorate Degree).The latent construct dispositions toward post-secondary education (Figure 15)is constructed from level of education wanted (INTEREST) and level ofeducation expected (EXPECT).To the extent that the dispositions one holds towards post-secondary educationare explained by the two parental background constructs -- sources of culturalcapital and sources ofprimary social capital -- and its subsequent effects on academiccapital and post-high school status, Bourdieu’s Theory of Practice is supported.Absence of these relationships supports a rational choice hypothesis.BeliefsBeliefs play a critical role in the theory of practical rationality. Whileaction is deemed to be rational if it is the best way of fulfilling an agent’s desires,desires must be in line with one’s beliefs. Beliefs themselves must be optimal, ortrue, and relevant evidence should influence belief formation. In Chapter 2 it wasestablished that it is optimal to believe that post-secondary education does9igure 15. isposition.c towardFost-secoiufanj T4ucatürn151enhance one’s life chances, given the statistical evidence on employability,income, and range of employment opportunities in relation to educationalattainment.Bourdieu, however, contends that the formation of durable beliefsrequires powers beyond those of reason. He asserts that:decision, if decision there is, and the ‘system of preferences’ which underlies it, dependnot only on all the previous choices of the decider but also on the conditions in which his‘choices’ have been made, which include all the choices of those who have chosen forhim, in his place, pre-judging his judgements and so shaping his judgement. . . . Theprinciple of practices has to be sought instead in the relationship between externalconstraints, which leave a very variable margin for choice, and dispositions which are theproduct of economic and social processes that are more or less completely reducible tothese constraints, as defined at a particular moment. (Bourdieu, 1990b, p.49-50)Habitus, as a practice-generating structure, structures not only what onebelieves, but also structures the evidence used in formulating beliefs.In order to assess the influence of beliefs on decisions about post-highschool destinations, three belief variables were added to Härnqvist’s framework.Respondents were asked to indicate the degree to which they believed that post-secondary education would help them 1) to prepare them for jobs (BELIEF2)24,2)to increase their income (BELIEF3), and 3) give them a wider choice of jobs(BELIEF6). These variables were measured on a 4-point scale, ranging from “1”definitely or probably not to “4” yes, definitely. Together, these three variablesform the latent construct beliefs about post-secondary education as depicted inFigure 16.24 The survey questionnaire contained six items that could have been used to measure beliefsabout post-secondary education. Three of these six items were considered relevant for this study.152Relationships among beliefs about post-secondary education, sources of culturalcapital, sources of primary social capital, and post-high school status supportBourdieus theory. To the extent that relationships exist between beliefs about post-secondary education, academic capital, and post-high school status but not amongparental background constructs, practical rationality is supported.Characteristics of the Personal EnvironmentAccording to Härnqvist (1978), characteristics of the individual’s personalenvironment include family background, peer group, and school environment.Following the discussion of the influence of family background on participationin post-secondary education, the school environment as an individualdeterminant is considered.Tigure 16. Be(iefr about fPost-.secolufanj Etfucatioii153Family BackgroundExplanations of action that adopt the theory of rational choice do not takeinto account if and how family background is related to action. Rational choicetheory focuses solely on the individual as an independent actor and rationalaction, including practical rationality, treats the social environment of thedeciding individual as “given” (see, for example, Stager, 1989b).In Bourdieus Theory of Practice, however, the family milieu is crucial inexplaining action. The cultural capital argument rests on the notion that familiesof higher social status transmit cultural resources, in the form of dispositions,meanings, habits, and affitudes of the dominant culture to their children.Transmission of the dominant culture via the family ensures that their childrenare more easily able to reap academic rewards. Social capital -- as obligations andexpectations, information channels, and norms and effective sanctions -- dependson the extent and power of social networks, and these networks often revolvearound the family.In this study, family background is analysed in two ways. First, familysocioeconomic background is assessed by measuring the educational levels andoccupational status of mothers and fathers by the post-secondary participantstatus of their children. Second, influence of parents as sources of primary socialcapital is determined by measuring the influence of mother, father, and otherfamily members on the individual.Mother’s education (MOTHED) and father’s education (FATHED) weredetermined by asking ‘What is the highest level of education completed by yourmother and father (or legal guardian)?tand was measured on an 8-point scale,from “1” less than Grade 9 to “8” completed Master’s or Doctorate Degree. Thisvariable was recoded to reflect actual years of schooling completed, from 7 to 19154years. Fathers occupation (FATHOCC) was determined by a two-part question,which asked usual ‘occupation or kind of work” and ‘nature of the servicesprovided or types of products produced by the business or industry”. Responseswere coded using The Canadian Standard Occupational Classification Schemeand transformed into Blishen and McRoberts’ (1976) Socio-economic Index.In various studies, several measures have been used to assess thecomposition of cultural capital in one’s possession. These measures generallyinclude attitudes towards, attendance at, and knowledge about various forms ofcultural events and activities (DiMaggio, 1982; DiMaggio & Mohr, 1985; Katsillis& Rubinson, 1990). However, Robinson and Garner (1985) point out, it is notcultural capital itself that is central to Bourdieu’s theory; rather, the transmissionby parents of cultural resources which are subsequently converted intoeducational (academic) capital is central. Hence, in this study, mother’seducation (MOTHED), father’s education (FATHED), and father’s occupation(FATHOCC) were used to construct the latent construct sources of cultural capital(Figure 17).Fzqure 17. Source.c ofCultural CapitalE155Since over 1100 respondents to the Grade 12 Graduate Follow-up questionnaireindicated that their mothers were homemakers, mothers occupation was notused as a measure in this study.Of particular interest in this study are the direct effects of sources of culturalcapital on beliefs about post-secondary education, dispositions toward post-secondaryeducation, and academic capital, and its indirect effects through these mediatingvariables on post-high school status.The influence of various family members on post-high school plans wasdetermined by asking “How important was 1) your mother, (MOTHINF) 2) yourfather (FATHINF), and 3) other family members (FAMINF), in helping orinfluencing your plans? These influence variables were measured on a 5-pointrating scale from ‘1” none to “ 5” very strong. Influence of friends (FRIENINF)was measured on the same scale.The latent construct, parents as sources of primary social capital, iscomprised of mother’s influence (MOTHINF) and father’s influence (FATHINF)and illustrated in Figure 18. The influence of friends was deemed to be a measureof secondary sources of social capital and is included as a manifest variable for thatconstruct.L9qure 18. Source.c of!Erimanj Social Capital156Parents as sources of secondary social capital are hypothesized to have direct andindirect effects on post-high school status.School EnvironmentHärnqvist (1978) defines school environment or school characteristics as“those effects which derive from the composition of the student body and fromthe climate of the student’s own school” (p.51). He acknowledges that analyticalproblems exist because when schools with different compositions are located invery different communities, it is difficult to ascertain whether differences are dueto school or community environments.School environment variables provide some sense of the “norms andeffective sanctions” aspect of social capital. Measures of school environmentcharacteristics provide indirect ways of assessing the academic and social climateto which students are exposed.In this study, measures at the individual school level were not available.Three measures that were available to assess whether and to what degree schoolenvironment influences educational choice were school district level variables.Two of the three measures, school district size and school district socio-economicstatus, are not included in the quantitative analyses due to multicollinearityproblems in the multivariate analyses. The achievement atmosphere of theschool district (SDHONOUR) was assessed by calculating the percentage ofGrade 12 students in each school district who, in 1988, graduated with honours.157Institutional Determinants of Educational ChoiceIn Härnqvists schema, institutional determinants of educational choiceare categorized as: 1) the educational system, and 2) society outside theeducational system (see Chapter 3, Figure 5). Society outside the educationalsystem was the focus of Chapter 2 and provides the contextual frame for thisstudy (see Chapter 4, Figure 7). Thus, only those determinants relevant to theeducational system are considered in the findings section of this study.The educational system is divided into two parts: 1) conditions antecedentto the choice situation, or those determinants operating in the school to whichthe student belongs as she or he plans for the next stage, and 2) conditionsanticipated in the choice situation, or those conditions which characterize thestage in which she or he is about to enter (Harnqvist, 1978, p.5).Conditions Antecedent to the Choice SituationIn this study, two determinants constitute conditions antecedent to thechoice situation; curricular differentiation and guidance organization. Curriculardifferentiation has already been discussed, along with grade point average, inthe section on student characteristics. In this section, guidance organization isconsidered.158Guidance OrganizationThe following variables are used to examine guidance organization as aninstitutional determinant of educational choice: influence of teachers andinfluence of counsellors.Influence of Teachers and CounsellorsIn terms of making decisions about post-high school destinations, teachersand counsellors may be described as secondary sources of social capital. They aresecondary in that their influence over students’ decisions occurs over a shorterperiod of time than does parents’ influence. Both teachers and counsellors,however, have significant roles to play as sources of information. Counsellorshave been described as critical ‘gatekeepers’ in the progress of students as theyjourney through the educational system (Erickson & Schultz, 1982; Lee &Ekstrom, 1987). They are the custodians of materials such as application forms topost-secondary institutions and information about awards and student financialaid. They possess key information about the types and roles of various post-secondary institutions and the value of different types of academic credentials.The degree to which teachers’ and counsellors’ influence coincides andcomplements the social capital provided by the family determines the extent towhich students have access to social resources of the simplex or multiplex kind.Teachers and counsellors as sources of social capital are potentially able tocontribute to cultural reproduction. Educational personnel tend to be ahomogeneous group and reflective of the dominant culture -- universityeducated, middle class, usually white, and at the high school level andparticularly in the case of teachers, more likely to be male. Students possessing159the cultural resources necessary to formulate questions and decode informationabout post-secondary prerequisites, application procedures, availability offinancial aid and scholarships, choice of post-secondary institution and programare more likely to benefit from the availability of teachers and counsellors assources of social capital.The influence of guidance organization on post-high school plans wasdetermined by two measures. The influence of guidance counsellors and teacherswas measured by asking HHow important were 1) guidance counsellors(COUNSINF), and 2) teachers (TEACHINF), in helping or influencing yourplans? These variables were measured on a 5 - point rating scale from “1” none to1511 very strong.Teachers influence (TEACHINF), counsellors influence (COUNSINF),and friends influence formed the latent construct sources ofsecondary social capital.The effects of sources of cultural capital and sources of primary social capital onsources of secondary social capital, as depicted in Figure 11, are of interest in thisstudy. In turn, the direct and indirect effects of these constructs on dispositionsTiqure 19. Source,s ofsecoinjsocia(Capita(160toward post-secondary education, academic capital, and ultimately post-high schoolstatus will further elucidate the role of social capital on post-secondaryparticipation.Conditions Anticipated in the Choice SituationConditions anticipated in the choice situation are “the individual’santicipations of future conditions which become antecedent to choice”(Harnqvist, 1978, p.61). These anticipated conditions are considered under thefollowing headings: geographic availability, and study finance. Perceptions ofadmission and selection rules are explored, in interviews with Grade 12 students,in Chapter 9.Following the tenets of practical rationality, conditions anticipated in thechoice situation may serve as evidence which, according to Elster (1989b), is usedto formulate the best grounded beliefs. In turn, for given desires and beliefs,rational action requires that the right amount of evidence is collected. However,in both belief formation and collection of evidence, “agents should consider alland only the relevant evidence, with no element being unduly weighted” (Elster,1989b, p.4) Undue emphasis on distance variables and lack of study finance, inlight of other forms of evidence (such as a high grade point average andpossession of university entrance requirements) may suggest a failure to practicepractical reasoning.In Bourdieu’s Theory of Practice, conditions anticipated in the choicesituation are structures constituting a particular type of environment. Thesestructures produce the habitus -- as “structured” structures that influencecategories of perception and assessment, and as “structuring” structures that161organize principles of action regarding post-high school life. Since dispositions,according to Bourdieu, are durably instilled by objective conditions (such asgeographic location and distance from post-secondary institutions, availability ofstudy finance, and admission and selection rules), aspirations and actionsobjectively compatible with those objective requirements, at both the individualand group level, are generated.Geographic AvailabilityGeographic location and distance variables may serve as evidence withina practical rationality framework. In Bourdieu’s Theory of Practice, however,these variables would be portrayed as “structured” and “structuring” structuresproduced by the luibitus.One way of portraying geographic availability is to examine theparticipation status of respondents by geographic region, as defined in Chapter5. However, another less subjective measure of geographic availability is tomeasure the distance from the nearest university or community college centrefrom the largest town or city in the school district. Two measures, distance fromthe nearest university (DISTU2) and distance from the nearest communitycollege centre (DISTCC1) were used to assess the influence of geographicavailability. For each measure, the following scale was used: “1” 0 km, “2” 1 to 49kilometers, “3” 50 to 99 kilometers, and 14 100 kilometers or more.Study FinanceAdequate measures of study finance were not available for bothparticipants and non-participants in this study. Only one measure related tostudy finance was available for both the participant and non-participant groups.162This measure is number of awards received (AWARDTOT). Respondents wereasked to indicate whether they received the following awards for post-secondaryeducation: provincial scholarship, school district scholarship, ‘Passport toEducation’, private scholarship, or any other scholarship or bursary. A score foreach respondent was computed by summing the number of awards received.This single observed variable was used to form the latent constructenabling capital.EnablingCapital AWARDTOTfFzqure 20. Ena6(ing CapitalIdeally, this construct as depicted in Figure 20 would have included observedmeasures of sources of financial assistance. The inadequacy of this construct withonly one manifest variable is recognized as a limitation in this study.Dependent VariablesParticipant statusParticipant status (STATPART) was determined by asking the respondentto indicate whether she or he had attended a post-secondary institution sincegraduating from high school. This variable was scored “0” for no, and “1” for yes.163Post-secondary Institution StatusPost-secondary institution status (STATPSI) was determined by askingrespondents to indicate the type of post-secondary institution attended. Thoseattending a non-university institution (either a community college ortechnical/vocational institute) were assigned a score of “1”, and participants atuniversity were assigned a score of “2’.Post-secondary StatusPost-secondary Status (STATPS) was determined by asking respondentsto indicate whether and where they attended some post-secondary institutionfollowing high school graduation. Non-participants were assigned as score of“1”, those attending a non-university institution (either a community college ortechnical/vocational institute) were assigned a score of “2”, and participants atuniversity were assigned a score of “3”.The latent construct post-high sciwol status, and thus the dependentvariable in the model of Post-high School Status proposed in Figure 11 (Chapter4) and estimated in Chapter 8 was measured with a single indicator, postsecondary status (STATPS).Post-highSchool STATPSTqure 21. !Post-IqI1ScIioo(Status164SummaryThe purpose of this chapter was to provide a description of the manifestand latent variables used in this study. Härnqvist’s determinants of educationalchoice provided the framework for selection of measures. Theoreticalinterpretations of the measures arose from rational choice theory as depicted byElster and Bourdieu’s Theory of Practice.This framework and related measures is used in Chapter 7 to address thefirst research question. That is, when considered simultaneously, docombinations of these measures reveal differences among non-participants, non-university participants, and university participants? If so, which combination ofvariables best predicts group membership? Finally, given the nature of differentopportunity sets possessed by non-participants and participants in postsecondary education, which theoretical explanation best accounts for theseopportunity sets? Does a rational choice explanation prevail, or do the tenets ofreproduction theory provide a more cogent interpretation of post-high schooldestination? To what extent, if any, do these two theoretical approaches work inconcert, as asserted by Coleman? In Chapter 8, a model integrating these twotheoretical approaches is tested.Chapter 7POST-HIGH SCHOOL DESTINATIONS AND OPPORTUNITY SETSIn this chapter, the first research question is addressed: T’Vhat factorsinfluence whether and where one participates in post-secondary education? Through useof the multivariate technique of discriminant function analysis, differences amongnon-participants, non-university, and university participants are explored.Discriminant function analysis allows an exploration of the dimensions onwhich the groups differ, the variables contributing to differences among thegroups on these dimensions, and the degree to which cases can be correctlyclassified into their own groups (Tabachnick & Fidell, 1983). In other words, thefollowing questions may be posed:1. How well do the predictor variables, as specified by Härnqvist,discriminate among the groups?2. What set of predictor variables best predicts membership in thefollowing groups:a) non-participant,b) non-university participantc) university participantThree separate discrirninant function analyses were performed to explorewhether a linear combination of individual and institutional determinants ofeducational choice discriminates among groups, and whether this combinationcan be used to predict the group membership. In the first analysis, the groupswere participants and non-participants, and in the second analysis, nonuniversity participants and university participants. The third analysis consisted of165166three groups -- non-participants, non-university participants, and universityparticipants.The sample of 4818 high school graduates is described in Chapter 4.Twenty predictor variables were chosen on the basis of Härnqvist’s individualand institutional determinants of educational choice, as depicted in Table 14. Acomplete description of the predictor variables may be found in Chapter 6. Thesame predictor variables were used in each of the three analyses.For each analysis, four investigations were carried out: a directdiscriminant function analysis, a cross-validation procedure, a stepwise analysis,and finally, separate analyses were conducted using male and female onlysamples. Each analysis will be described separately, under the followingheadings: 1) participation or non-participation in post-secondary education, 2)non-university or university participation in post-secondary education, and 3)non-participation, non-university participation, or university participation inpost-secondary education.Participation or Non-participation in Post-secondary EducationDiscriminant function analysis was used in the first analysis to determinewhether participants in post-secondary education could be differentiated fromnon-participants by a linear combination of individual and institutional variables.The grouping variable (STATPART) is dichotomous: 1) participants, and 2) nonparticipants.First, the assumptions required for discrirninant function analysis will beevaluated. Next, results of the discriminant analyses are reported.167Evaluation of AssumptionsMissing dataOf the total sample of 4818, 1690 cases contained missing values. SPSSDISCRIMINANT excludes cases with missing values on any of the variables.Missing data appear to be scattered over variables and groups, thus exclusion ofthese variables does not appear to be problematic25.In this analysis, 3128 caseswith no missing values were used.Unequal Sample SizesOf a total of 3128 cases, the number of participants is 2415 (76%) and non-participants is 713 (24%)26. According to Tabachnick & Fidell (1983), since thegrouping variable usually consists of naturally occurring groups, groups rarelyoccur or are sampled with equal numbers of members. Thus, sample sizes are notusually equal for applications of DISCRIM. They indicate that the greater thegroups differ in size, the larger the overall sample size necessary to assurerobustness. They suggest that robustness could be expected with 20 cases in thesmallest group if there are only a few predictors. In this study, the sample size far25 Two further analyses were carried out to determine the effect of missing data. In the firstanalysis, group means were substituted for missing values. The classification matrix indicated that77% of the participants and 74% of the non-participants were correctly classified. In the secondanalysis, the discriminant functions were derived using only cases with no missing values. At theclassification stage, means were substituted for missing values. Seventy-four percent ofparticipants and 74% of non-participants were correctly classified. When only cases with completeinformation were used, i.e. in this analysis, 79% of participants and 74% of non-participants arecorrectly classified. Thus, either mean substitution approach results in slightly less classificationpower.26 The total sample consists of 3566 participants (74%) and 1252 non-participants (26%).168exceeds these guidelines. Tabachnick & Fidell state that “in these cases, robustnessof the statistical procedures need not be worrisome” (p.300).Stevens (1986) states that when group sizes are sharply unequal, it becomesnecessary to check the homogeneity of variance-covariance assumption. The Boxtest will be discussed in the section which addresses this assumption.Multivariate NormalityDiscriminant function analysis requires that the multivariate normalityassumption be met. That is, the predictor variable scores are independently andrandomly sampled from a population of scores, and that the sampling distributionof any linear combination of predictor scores is normally distributed (Tabachnick& Fidell, 1983).The distribution statistics of each of the variables for each of the two groupswere visually examined, and for the 19 variables measured on at least an ordinalscale, no markedly non-normal distributions (other than moderate skewness),were detected. Discriminant analysis is considered to be robust to violations ofmultivariate normality caused by skewness (Tabachnick and Fidell, 1989).The set of predictor variables contains one dichotomous variable,CURRDIFF. This variable is coded as a dummy variable. Although lineardiscriminant function requires that the predictor variables have a multivariatenormal distribution, in the case of dichotomous variables, most evidence suggeststhat the linear discriminant function often performs reasonably well (Gilbert, 1968;Lachenbruch, 1975). Stevens (1986) states that when violation of this assumptionoccurs due to the use of some discrete dichotomous variables, logistic regressionmay be be preferable to discriminant function analysis.169Homogeneity of Variance-Covariance MatricesDiscriminant function analysis also requires that the assumption ofhomogeneity of variance-covariance, or equal group covariance matrices be met.In this analysis, the Box’s M test is significant (F=3.64, p <.001), which indicatesheterogeneity of the covariance matrices. Violation of this assumption may be afunction of the large sample size. According to Kiecka (1980), when thisassumption is violated, the canonical discriminant functions may not providemaximum separation among the groups, and the probabilities of groupmembership may be distorted.In the case of violation of this assumption, several texts (Klecka, 1980;Lachenbruch, 1975; Norusis, 1990) suggest using quadratic discrimination. Inquadratic discrimination, individual group covariance matrices are used forcomputing the probability of group membership. However, as N becomes large,quadratic methods tend to yield less dissimilar results (Dillon & Goldstein, 1984).This option is not available in SPSS.Lachenbruch (1975) and Norusis (1990) state that the linear function is quitesatisfactory if the covariance matrices are not too unequal. Tabachnick & Fidell(1983) claim that robustness can be expected with respect to violation of theassumption of equal variance-covariance matrices with equally sized or largesamples.Examination of the plots of the discriminant function for each groupindicates that the spread of cases is not too unequal. Therefore, for the purpose ofthis study, it is assumed that the effects of unequal variance-covariance matriceswill not be serious.170Direct AnalysisIn direct discriminant function analysis, all of the predictor variables enterthe equations simultaneously. Table 15 displays the means and standarddeviations for each of the groups and the total sample.Discrirninant function analysis is used for both inteipretation of groupdifferences and classification of cases into groups. In the next section, theinterpretation phase is discussed.InterpretationInterpretation involves an examination of the ways in which groups differ.The interpretation phase of discriminant function analysis is concerned with thenumber and importance of the canonical discriminant functions to be derived, andthe interpretation of their meaning for explaining group differences. Table 16provides a summary of the interpretation phase of this analysis. Examination ofunivariate F’s, canonical discriminant function, canonical correlation, and chisquare test of significance provides an answer to how well the discriminantfunction distinguishes between groups.Significance tests for equality of group means was carried out for eachvariable and are displayed in Table 16. The F value for each variable indicatessignificant differences between group means (p <.001) on all but two variables,DISTU2, and DISTCC.Table15.MeansandStandardDeviations:Non-participantsandparticipants.VariableNon-participantParticipantTotalDescriptionINTERESTEXPECTMOTHEDFATHEDFATHOCCMOTHINFFATHINFFAMINFFRIENINFCURRDIFFGPASDHONOURTEACHINFCOUNSINFDISTU2DISTCCAWARDTOTBELIEF2BELIEF3BELIEF6mean4.772.7911.9912.0847.893.123.002.352.600.331.8827.402.111.913.761.711.133.493.393.42s.d.1.491.572.26 2.7114.711.341.361.251.170.470.74 6.161.231.141.671.671.220.790.86 0.82mean5.283.9712.7113.1251.763.863.78 2.883.110.75 2.5728.492.822.423.541.601.863.623.523.54s.d.1.051.302.523.0515.531.061.141.301.170.430.836.281.281.301.831.621.080.660.720.74mean5.163.7012.5512.8850.873.703.602.763.000.662.4128.242.662.313.591.631.693.593.493.51s.d.1.191.45 2.483.0015.481.171.241.311.190.470.866.271.311.291.801.631.150.700.760.76HighestlevelofeducationwantedHighestlevel ofeducationexpectedMother’seducationFather’seducationFather’soccupationMother’sinfluenceonpost-highschoolplansFather’sinfluenceonpost-highschoolplansOtherfamily’sinfluenceonpost-highschoolplansFriends’influenceonpost-highschoolplansCurriculardifferentiationGradepointaverage%Grade12graduatesindistrictgraduatingwithhonourTeachers’influenceonpost-highschoolplansCounsellors’influenceonpost-highschoolplansDistancefromnearestuniversityDistancefromnearestcommunitycollegecentreTotalnumberofawardsreceivedBeliefthatp.s.e.isnecessarytoprepareforajobBeliefthatp.s.e.isnecessarytoincreasemyincomeBeliefthatp.s.e.isnecessarytohaveawiderchoiceofjobsTable16.DiscriminantFunctionAnalysisSummaryTable:Non-participantsandparticipants.CorrelationsoftheStepwisepredictorvariableswiththePredictordiscriminantfunctionUnivariatefunctionVariablesfunctioncoefficientsF(1,3046)coefficientsPooledwithin-groupcorrelationsamongpredictors1234567891011121314151617181920StandardizeddiscriminantAnalysis:Standardizeddiscriminant1.INTEREST0.290.08104.100.091.0002.EXPECT0.580.30412.100.32.2491.0003.MOTHED0.200.0146.84.048.1421.0004.FATHED0.240.0467.93.071.186.5601.0005.FATHOCC0.170.0434.79.068.127.304.4771.0006.MOTHJNF0.440.17234.600.20.045.064.081.043.0181.0007.FATHINF0.440.19231.600.20.059.071.047.120.068.6911.0008.FAMINF0.280.0394.17.060.052-.015-.021-.038.431.3931.0009.FRIENINF0.300.03106.50.060.092-.044-.043-.028.294.237.3201.00010.CURRDIFF0.640.38504.100.40.133.248.140.142.120.013.029.022.0451.00011.GPA0.570.30399.400.30.090.284.150.133.087-.042-.033-.073-.016.4181.00012.SDHONOUR0.120.0416.61.010.032.057.104.087-.009.009.012.042.057.0521.00013.TEACHINF0.380.10173.000.10.073.097-.044-.039-.076.250.197.290.398.036.069.0011.00014.COUNSINF0.270.0992.040.09.023.021-.076-.067-.100.234.212.295.339-.047-.040-.013.5931.00015.DISTIJ2-0.08-0.017.92-.057-.034.009-.092-.084-.027-.025-.013-.038-.047.016-.497-.008.0211.00016.DISTCC-0.04-0.012.39-.049-.035-.013-.068-.069.024.021.021-.016-.044-.015-.399.024.060.4011.00017.AWARDTOT0.440.26238.200.26.071.088-.015-.018-.025.127.096.096.180.098.074.049.213.198-.029.0161.00018.BELIEF20.130.0420.30.110.082-.026-.025.007.071.071.040.024.045-.016-.046.060.062.065.033.0541.00019.BELIEF30.120.0217.05.088.111.005.021.018.051.045.044.041.042.012-.047.054.052.062.006.036.4891.00020.BELIEF60.10-0.0612.95.091.093.030.064.051.075.101.055.067.063.035-.021.054.064.037.002.074.332.3781.000Csnonica!REigenvalue0.530.39173The maximum number of canonical discriminant functions is the smaller ofthe two numbers p and (g - 1), where p is the number of predictor variables and gis the number of groups. In this analysis, only one discriminant function ispossible.The canonical correlation coefficient provides indication of the substantiveutility of the discrirninant function, or ‘how well the discriminant function isdoing” (Klecka, 19 80, p.36). The canonical correlation is a measure of the degree ofassociation (measured from 0 to 1) between the discriminant scores and thegroups.The canonical correlation in this analysis is .53, which indicates a moderaterelationship between the groups and the discriminant function. This indicates thatthe groups are quite different on the variables being analysed.A chi-square test of significance, based on Wilks’ Lambda, is a test of thenull hypothesis that there is no difference between the group means in thepopulations from which the samples are drawn. Group differences are highlysignificant (x2 (20) = 1029.3, p <.001).Based on an examination of the canonical correlation and chi-square test ofsignificance, it may be concluded that the predictor variables provide reasonablygood discrimination between participants and non-participants. However, noinformation is provided about the individual predictor variables. Thestandardized canonical discriminant function coefficients and the structurecoefficients are used to determine which predictor variables are the most powerfulpredictors.In discriminant analysis, a linear combination of the independent variablesis formed and serves as the basis for assigning individual cases to groups. The174coefficients are derived so that the group means on the function are as different aspossible, and result in the ‘best separation between the groups.Table 16 contains the standardized canonical discrirninant functioncoefficients which provide information about the relative importance of a variablein determining the discriminant score. The standardized coefficients may be usedto assess which variables contribute most to determining the discriminant scoreson each function.Table 16 indicates that CURRDIFF makes the greatest contribution,followed by GPA, EXPECT, and AWARDTOT. Next in importance are MOTHINFand FATHINF. The other predictor variables appear to contribute considerablyless to determining the discriminant scores on this function.Another way of assessing the contribution of a variable to the discriminantfunction is to examine the correlations between predictor variables and each of thediscriminant functions. A structure coefficient reveals how closely a variable and afunction are related. The function is ‘named’ on the basis of the structurecoefficients by noting the variables with the highest coefficients.The structure matrix, displayed in Table 16, and in Table 17 in descendingorder by size of the correlation with the discriminant function, shows that thediscrirninant function is most highly correlated with CURRDIFF (r.64), followedby EXPECT (r=.58) and GPA (r=.57). AWARDTOT (r=.44), MOTHINF (r=.44), andFATHINF (r=.44) are moderately correlated with the discriminant function,followed by TEACHINF (r=.38).175AWARDTOT .44MOTHINF .44FATHINF .44TEACHINF .38FRIENINF .30INTEREST .29FAMINF .28COUNSINF .27FATHED .24MOTHED .20FATHOCC .17The structure matrix may be interpreted as being comprised of five levels,based on the size of the correlations of the variables within each level. In the firstlevel, CURRDIFF and GPA along with EXPECT, the most highly correlated withthe discriminant function, are, depending on the theoretical interpretation,academic capital variables as evidence or as conversion of cultural capital intoachievement. The second level, consisting of variables which each correlatemoderately with the discriminant function, are one achievement variable(AWARDTOT), primary social capital variables and one secondary social capitalvariable. The third level is comprised of the other secondary social capital variablesand one disposition variable (INTEREST). The fourth and fifth levels containvariables that are poorly correlated with the discriminant function. The fourthlevel is comprised primarily of family socioeconomic background or culturalTable 17.Pooled Within-Groups Correlations (Structure Coefficients) between Discriminating Variablesand the Canonical Discriminant Functions. Non-participants and Participants.CURRDIFF .64EXPECT .58GPA .57BELIEF2 .13BELIEF3 .12SDHONOUR .12BELIEF6 .10DISTU2 -.08DISTCC - .04176capital variables. The fifth level contains variables identified as institutionaldeterminants of educational choice, (DISTCC, DISTU2, and SDHONOUR, and beliefvariables (BELIEF2, BELIEF3, BELIEF6).Standardized coefficients and structure coefficients provide different typesof information. Standardized coefficients provide an indication of the contributionof the variable in calculating the discrirninant score. However, if variables arehighly correlated, thus sharing nearly the same discriminating information, theircontribution to the score is shared even if the joint contribution is important.Because structure coefficients are simple bivariate correlations, they are notaffected by relationships with other variables. Both MOTHINF and FATHINFhave relatively low standardized coefficients, but both have large structurecoefficients. This is probably due to a moderately high correlation (r=.69) betweenthe two variables. For the most part, the standardized coefficients and thestructure coefficients provide similar information about the predictor variables;however, their relative importance differs depending on which coefficient is used.Klecka (1980) and Tabachnick & Fidell (1989) assert standardized coefficients aredifficult to interpret; therefore structure coefficients are a better guide to themeaning of the canonical discriminant functions than are the standardizedcoefficients.It may be concluded from an analysis of the structure matrix andstandardized coefficients, that variables associated with achievement or academiccapital, along with expectations regarding educational attainment and number ofawards received, provide the most powerful predictors of group membership.Participants in post-secondary education are more likely to have completed anacademic program in high school (mean.75) than non-participants (mean.33),have higher grade point averages (rnean’2.57) than non-participants (mean4.88),177expect to obtain higher levels of post-secondary education (mean3.97) than non-participants (mean=2.79), and receive more more scholarships and bursaries(mean1.86) than non-participants (mean=1.13). Social capital variables are next inimportance. Participants are more strongly influenced by mothers (mean=3.86),fathers (mean=3.78), teachers (mean=2.82), and friends (mean3.11) than non-participants (rnean=3.12, 3.00, 2.11, and 2.60 respectively). Participants also reportthat they want to obtain higher levels of education (rnean5.27) than non-participants (mean=4.75).It is also interesting to examine the predictor variables that contribute littleto the prediction of group membership. Influence of other family members(rnean2.88 for participants, mean2.35 for non-participants), and counsellors(rnean=2.42 for participants, mean4.91 for non-participants) are weak predictorsof group membership. Neither do cultural capital variables discriminate wellbetween groups. Mother’s education (rneanl2.71 for participants, meanll.99 fornon-participants), father’s education (meaiv43.12 for participants, mean=12.08 fornon-participants), and father’s occupation (mean51.76 for participants,mean=47.89 for non-participants) are also weak predictors of group membership.Non-participants and participants hold similar beliefs, which does not supportrational choice or Bourdieu’s Theory of Practice. Non-participants appear tobelieve that post-secondary education is necessary to prepare for a job(mean3.49), to increase one’s income (mean3.39), and to give one a wider choiceof jobs (meaiv=3.42) as do participants (mean3.62. 3.52, and 3.54 respectively).Characteristics of the student’s environment, measured as percentage of honoursgraduates in a district, and institutional variables such as distance fromcommunity college, and distance from university are not useful predictors of postsecondary participation. Lack of discriminating power of the two distance178variables is particularly interesting, given the ‘access as availability to ensureAccess for All’ approach adopted by the Ministry of Advanced Education and JobTraining (Report of the Provincial Access Committee, 1988). This finding,however, concurs with earlier findings by Tinto (1975) that proximity to a post-secondary institution may influence the type of post-secondary institutionattended, but does not enhance overall participation rates.ClassificationClassification is a separate component of discriminant function analysis.The classification procedure provides another test of the discriminating power ofthe discrirninant variables being used. It can be used to classify ‘unknown’ casesor, as in this study, it is used to test the accuracy of the classification procedure.The proportion of cases correctly classified indicates the accuracy of the procedureand indirectly confirms the degree of group separation.The classification decision, whether a case belongs to a particular group, isbased on information carried by the discriminating variables. The classificationprocedure typically involves defining some notion of ‘distance’ between the caseand each group centroid with the case being classified into the ‘closest’ group.In the classification phase, either the discriminating variables or thecanonical discrirninant functions are used to predict the group to which the casemost likely belongs. SPSS uses discrirninant function values, not the originalvariables (Norusis, 1990). According to Klecka (1980), this approach results in amore thorough analysis.179A classification or confusion matrix, found in Table 18, is used to displaythe results. In a two-group analysis, it is possible to classify at least 50% of thecases correctly by random assignment. However, as Table 18 reveals, 79% of theparticipants and 74% of the non-participants are correctly classified. The totalnumber of correct classifications is 2425, or 78%.Table 18.Classification (Confusion) Matrix. Non-participants and Participants.Actual Group No. of cases Predicted Group Membership1 2Group 1Non-participant 713 525 18873.6% 26.4%Group 2 2415 515 1900Participant 21.3% 78.7%Percent of grouped cases correctly classified: 77.5%Klecka suggests that a proportional error reduction statistic, tau, provides astandard level of improvement of classification over chance. In this analysis,classification on the basis of the discriminating variables made 54% fewer errorsthan would be expected by random assignment. That is, 703 actual errors, ratherthan 1564 expected by chance, were made.When considered together with Wilks Lambda and the canonicalcorrelations, it appears that the amount of discrimination contained in thevariables is moderately strong.180Cross-validationBecause classification of cases into groups is based on the same cases usedto derive the classification functions, the power of the classification procedure isoverestimated. When the sample size is large, the classification procedure can bevalidated by randomly spliffing the sample into two subsets. One sample is usedto derive the classification functions, and the other subset is used only to test theclassifications. The subset used only for classification purposes will provide abetter estimate of the ability to correctly predict the total population, since eachsubset will have different sampling errors.In this analysis, the total sample of 3128 was randomly split into 2 subsets.The first subset (n=1565), comprised of 50% of the sample, was used to derive theclassification functions. Using these functions, 78% of the participants and 75% ofthe non-participants were correctly classified. The total number of correctclassifications for this group was 77%. When the classification functions derivedfrom the first subset were used to classify the 1566 cases in the second subset, 77%of the participants and 72% of the non-participants were correctly classified. Theproportional error reduction statistic, tau, indicates that classification on the basisof the discriminating variables made 52% fewer errors than would be expected byrandom assignment.It can be concluded from the results of the cross-validation procedure thatthe classification functions accurately classify the sample of Grade 12 graduatesnot used to derive these functions.181Stepwise Discriminant Function AnalysisIn this study, the data set generated from the Grade 12 Graduate Follow-upand corresponding Link File data contains a wealth of potential discriminatingvariables. The conceptual frameworks based on Harnqvists determinants ofeducational choice, (Figure 7, Chapter 4), and theories of rational choice andBourdieus Theory of Practice (Figures 12 to 19, Chapter 5) specified theunobserved predictor variables. The measures that were deemed appropriate andwere available in the data set were used in the previous analysis. However, two ormore variables may provide similar discriminating information. The LISRELanalyses employed in Chapter 8 account for shared information by using multipleobserved indicators to form unobserved latent constructs. For these analyses,however, the value of these predictor variables as discriminators, or the existenceof redundancy among variables because they share the same discriminatinginformation, may be further determined by employing a stepwise discriminantfunction analysis.According to Klecka (1980), stepwise procedures produce an optimal set ofdiscriminating variables. In this analysis, stepwise inclusion of variablesemployed Wilks Lambda as the criterion for selection, with the F-to-enter = 4.0, F-to-remove = 1.0, minimum tolerance level = 0.001. Wilks’ Lambda takes intoconsideration both the differences between groups and the cohesiveness orhomogeneity within groups27 (Klecka, 19 80).Table 19 summarizes the F value for the change in Wilks’ Lambda when avariable is entered into the model. The upper triangle contains the F-to-remove forvariables entered into the model, and the lower triangle contains the F-to -enter for27 results were obtained using Mahalanobis’ distance as a stepping method.Table19.StepwiseDiscriminafltFunctionAnalysis:NonpartiCiPafltsandparticipants.STEP0123456789OrderVariablesCUBRDIFFEXPECTMOTIUNTAWARDTOTGPArATHINFTEACIUNfINTERESTCOUNSNFEnteredCURRD1FF504.12504.12285.48271.60235.75117.01113.13114.56110.03112.14EXPECT412.10199.03199.03165.49145.5698.2793.9288.1874.3474.94MOTHINF234.58194.42160.93160.93125.36135.5525.7718.7418.8418.22AWARDTOT238.22152.43122.8387.6987.6980.8379.5262.4260.8956.89GPA399.41117.2461.8472.4365.6165.6167.1562.2862.4664.33FATHINF231.60182.63149.3621.8620.6522.1822.1820.6920.0418.63TEACHINF172.98131.3898.1746.6826.3721.5420.0520.0519.205.73INTEREST104.1045.7712.729.617.177.326.575.735.735.89COUNSINF92.0497.8283.4438.3920.4421.6018.534.714.874.87•MOTHED46.8412.083.400.801.710.350.441.040.991.23•FATHED67.9322.416.114.035.863.811.912.892.733.08•FATHOCC34.798.952.331.863.142.461.512.712.442.89•FAMINF94.1773.2258.565.653.776.773.791.090.960.53•FRIENINF106.5174.7852.8213.375.326.965.890.990.940.53•SDHONOUR16.616.795.155.523.632.812.492.612.642.74•DISTU27.922.701.620.870.551.171.111.130.911.06•DISTCC2.390.26-0.020.230.420.530.580.710.550.72•BELIEF220.2910.584.671.660.851.761.451.110.720.62•BELTEF317.058.812.140.770.460.780.700.480.310.25•BELIEF612.954.160.780.000.270.230.600.731.001.15•NotenteredCanonicalR0.53Cliisquare(9)1020.30p<.001183variables not yet entered into the model. The diagonal contains the F-to-enter forthe variable at the point it entered into the analysis.At the last step, 11 variables had F values of less than 4.0, and were notincluded in the model. These variables are: MOTHED, FATHED, FATHOCC,FAMINF, FRIENINF, SDHONOUR, DISTU2, DISTCC, BELIEF2, BELIEF3, andBELIEF6.Only one variable -- counsellor’s influence (COUNSINF) -- deemed to berelatively unimportant in the direct analysis, was retained in the stepwise analysis.Results of the stepwise analysis are consistent with the direct analysis, asdemonstrated in Table 16. Table 16 compares the standardized coefficients and thestructure matrix of the direct analysis with the standardized structure coefficientsin the stepwise analysis.Table 20 displays the results of the classification procedure whenclassification coefficients are derived from 9 rather than the original 20 variables.Actual Group No. of cases28 Predicted Group Membership1 2Group 1Non-participant 897 664 23374.0% 26.0%Group 2 2889 676 2213Participant 23.4% 76.6%Percent of “grouped” cases correctly classified: 75.9%Table 20.Stepwise Analysis Classification (Confusion) MatrixNon-participants and Participants.28 Because fewer variables are employed, the number of cases classified increases by 658.184When Table 20 is compared with Table 18, it appears that classification of casesbased on 9 variables retained in the stepwise analysis, rather than the original 20variables, is almost as effective.Tabachnick & Fidell (1989) strongly recommend that cross-validation becarried out to reduce bias caused by capitalization on chance differences andoverfitting of the data. When the stepwise discriminant analysis was carried outwith a 50% randomly generated subset of the sample (n1541), 8 variablesremained in the analysis at the last step. The following compares the variablesretained and order they are entered in 1) the stepwise analysis conducted with thetotal sample, and 2) the same stepwise analysis employing a cross-validationprocedure:StepwiseStepwise Cross validationCURRDIFF 1 1EXPECT 2 2MOTHJNF 3 3AWARDTOT 4 5GPA 5 4FATHINF 6 6TEACHINF 7 7INTEREST 8 -COUNSINF 9 -BELIEF2 8Results of the cross-validation procedure are consistent with the stepwiseanalysis. The classification coefficients, derived from 8 variables and used toclassify 2112 cases in the first subset, resulted in correct classification of 74% of theparticipants and 72% of the non-participants. When the classification functionsderived from the first subset were used to classify the 2164 cases in the secondsubset, 75% of the participants and 75% of the non-participants were correctlyclassified.185The stepwise discriminant analysis provides further confirmation thatgiven this sample of grade twelve graduates and the set of measures used, thefollowing variables best predict group membership:1. curricular differentiation2. level of education expected3. grade point average4. number of awards received5. mother’s influence6. father’s influence7. teachers’ influence8. level of education wanted9. counsellors’ influenceThe remaining predictor variables appear to contribute little additionaldiscriminating power, or provide redundant discriminating information withthose variables retained in the analysis.Gender DifferencesTable 21 displays the standardized discriminant function coefficients,structure coefficients, and shows which variables were retained in a stepwiseanalysis, in separate analyses conducted for men and for women. Means andstandard deviations for females and males for each analysis may be found inAppendix D.The canonical correlation for each group, indicating the degree ofassociation between the discriminant scores and the groups, is essentially equalfor the two groups (female.53, male=.54). However, the standardized canonicaldiscriminant function coefficients (providing information about the relativeimportance of a variable in determining the discrirninant score structure186coefficient), and the structure coefficients (revealing how closely a variable and afunction are related) provide somewhat different information for men andwomen.Both the standardized coefficients and structure coefficients indicate thatgrade point average, while important for both men and women, is considerablymore important for men. Table 22 reveals that for women, expectations about thelevel of educational attainment is correlated more highly than grade point averagewith the discriminant function. Also, for women the primary and secondary socialcapital variables, mother’s, father’s, friends’, other family members, andcounsellors’ influence are more important than they are for men. For women,mother’s education is more important (r=.23) than it is for men (r.16); theopposite pattern is evident for father’s occupation (r.20 for men, r.14 forwomen). These latter correlations, however, are quite low.Table21.Discriminant FunctionAnalysis SummaryTable:Non-participantsandParticipants-FemalesandMales.withthefunctionstepwiseVariablesdiscriminant functionscoefficientsPooledwithin-groupcorrelationsamongpredictors*femalemalefemalemalefemalemale12345678910111213141516171819200.530.540.390.42PredictorCorrelationsofthepredictorvariablesStandardizedVariablesdiscrirninantretainedinanalysis1.INTEREST0.280.290.120.03.161.073.081.082.037.049.026.017.129.056.007.061-.008-.039-.072.063.111.088.0892.EXPECT0.560.600.300.30*.324.145.167.114.078.072.084.082.240.254.035.095.005-.049-.052.074.040.103.1003.MOTHED0.230.160.04-0.04.021.137.541.302.104.063.000-.061.156.138.044-.051-.114.020-.018-.001.024.025.0524.FATHED0.230.250.040.06.063.205.584.467.061.134-.005-.066.127.113.088-.046-.087-.105-.080-.003-.001.029.0605.FATHOCC0.140.200.030.04.052.144.310.493.036.080-.030-.055.099.055.071-.080-.131-.087-.081-.030.032.045.0556.MOTHINF0.470.380.180.18**.051.058.058.035-.004.670.421.290.026-.031-.012.229.216-.006.020.089.061.053.0757.FATFIINF0.470.370.230.16**.071.075.027.108.054.717.380.207.048-.030.026.188.201-.021-.002.080.056.040.0788.FAM]NF0.310.230.000.05.098.017-.033-.032-.048.437.406.331.054-.068.010.278.282-.005.047.076.033.047.0569.FRIENINF0.330.240.11-0.07*.107.113-.019-.007.007.289.269.299.029-.019.031.373.314-.015-.001.036.003.029.04910.CURRDIFF0.620.650.380.38**.138.258.119.162.148-.002.006-.020.067.394.048.055-.074-.047-.061.100.035.036.03911.GPA0.500.640.260.34**.131.323.169.159.126-.054-.034-.078-.009.450.019.078-.051.030-.011.070-.047.004.04812.SDHONOUR0.060.190.020.06*.013.028.076.124.105-.003-.008.017.059.068.092.005-.018-.494-.387.048-.074-.066-.02213.TEACHINF0.370.360.030.18*.087.104-.033-.065-.069.273.207.302.429.011.060-.002.585-.015.043.196.046.049.05914.COUNSINF0.290.240.150.01*.059.049-.024-.033-.060.247.222.306.366-.010-.024-.004.602.017.082.176.034.045.05215.DISTU2-0.03-0.140.02-0.05-.078-.014-.008-.076-.078-.055-.032-.025-.070-.046.001-.500.001.026.415-.051.086.078.03816.DJSTCC0.00-0.100.04-0.06-.021-.011-.008-.053-.051.028.049-.017-.038-.021-.017-.414-.004.027.382-.011.049.017.00617.AWARDTOT0.440.410.280.24**.075.117-.028-.025-.019.157.111.112.225.096.081.053.232.218.000.051.019.023.05818.BELIEF20.080.170.050.01.107.133-.080-.048-.023.078.087.047.046.057.017-.016.076.093.043.018.089.468.31319.BEUEF30.060.19-0.050.11.088.120-.022.007-.019.054.055.043.062.049.018-.027.062.065.042-.007.056.518.39720.BEUEF60.100.10-0.04-0.08.089.093.008.076.045.065.124.047.081.092.020-.019.045.072.036-.004.083.350.362Canonical REigenualue*Correlationsformalesampleinlowertriangle, forfemalesampleinuppertriangle188Table 22.Pooled Within-Groups Correlations (Structure Coefficients) between Discriminating Variablesand the Canonical Discriminant Functions - Females and Males.Non-participants and Participants.Female MaleCURRDIFF .62 .65EXPECT .56 .60GPA .50 .64FATHINF .48 .37MOTHThJF .47 .38AWARDTOT .44 .41TEACHINF .37 .36FRIENINF .33 .24FAMINF .31 .23COUNSINF .29 .24INTEREST .28 .29FATHED .23 .25MOTHED .23 .16FATHOCC .14 .20BELIEF6 .10 .10BELIEF2 .08 .17BELIEF3 .06 .19SDHONOUR .06 .19DISTU2 -.03 -.14DISTCC 00 -.10Table 23 displays results of the classification procedure which areremarkably similar for the male and female sample, and with that of the totalsample (Table 18).189Table 23.Classification (Confusion) MatrixFemale and Male Sample - Non-participants and Participants.Actual Group No. of cases Predicted Group MembershipFemale1 2Group 1Non-participant 372 278 9474.7% 25.3%Group 2 1405 289 1116Participant 20.6% 79.4%Percent of ‘grouped’ cases correctly classified: 78.5%Male1 2Group 1Non-participant 341 254 8774.5% 25.3%Group 2 1010 227 783Participant 22.5% 77.5%Percent of “grouped” cases correctly classified: 76.8%It appears that while individual predictors have a differential impact onparticipation or non-participation for males and females, group membership ispredicted equally well for each group.SummaryThe first set of analyses sought to to determine whether participants inpost-secondary education could be differentiated from non-participants by alinear combination of individual and institutional variables. The findings indicatethat these variables do provide reasonably good discrimination between190participants and non-participants, and that academic capital, variables, either asevidence of achievement or as conversion of cultural capital into academicachievement and primary and social capital variables, account for most of thediscrimination.University or Non-university ParticipationA second discriminant function analysis was carried out to determinewhether non-university participants in post-secondary education could bedifferentiated from university participants by a linear combination of individualand institutional variables, how well the predictor variables discriminate betweenthe two types of participants, and what set of predictor variables best predictsmembership in the non-university and university participant groups.Of the total sample of 4818 high school graduates, 3566 reported that theyhad participated in some form of post-secondary education. The groupingvariable (STATPSI) is dichotomous: 1> non-university participants, and 2)university participants. Of the total sample of 3566, 1151 cases contained at leastone missing value. Of a total of 2415 cases with complete information, 1484 (61%)were non-university participants and 914 (39%) were university participants. Inthe total sample, of the 3566 participants, 65% (n2316) attended non-universityinstitutions and 35% (n1250) attended universities. Although non-universityparticipants are slightly underrepresented and university participants are slightlyoverrepresented as the result of missing values, missing data appear to bescattered over variables and groups, thus exclusion of these cases should nothinder the analysis.191Since the same 20 predictor variables used in the first analysis are used inthis analysis, the previous discussion of multivariate normality pertains.Heterogeneity of the covariance matrices, however, is indicated by a significantBox’s M test (F=4.60, p <.001). As in the first analysis, violation of this assumptionmay be a function of the large sample size and it is assumed that the effects ofunequal variance-covariance matrices will not be serious.Direct AnalysisTable 24 displays the means and standard deviations for each of the groupsand the total sample. Table 25 provides a summary of the interpretation phase ofthis analysis.Significance tests for equality of group means was carried out for eachvariable and are displayed in Table 25. The F value for each variable indicates nosignificant differences between group means (p <.001) for the following variables:MOTHINF, FATHINF, FAMINF, FRIENINF, COUNSINF, DISTCC, BELIEF2,BELIEF3, and AND BELIEF6.The canonical correlation in this analysis is .59, which indicates amoderately strong relationship between the groups and the discriminant function.A chi-square test of significance, based on Wilks’ Lambda, indicates that groupdifferences are highly significant ( 2(2O) = 1014.4, p <.001 ). Based on anexamination of the canonical correlation and chi-square test of significance, it maybe concluded that the predictor variables provide reasonably good discriminationbetween non_university participants and university participants and indicates ahighly reliable relationship between the groups and the predictor variables.Table24.MeansandStandardDeviations.Non-universityparticipantsanduniversityparticipants.VariableNon-universityUniversityTotalDescriptionmeans.d.means.d.means.d.INTEREST5.151.175.460.815.281.05HighestlevelofeducationwantedEXPECT3.671.334.431.093.971.30Highestlevel ofeducationexpectedMOTHED12.432.4513.152.5712.712.52MotherseducationFATHED12.733.0213.742.9713.123.05FatherseducationFATHOCC50.2015.4154.2415.3951.7615.53FathersoccupationMOTHINF3.861.063.871.043.861.06Mothersinfluenceonpost-highschoolplansFATHINF3.751.163.831.113.781.14Fathersinfluenceonpost-highschoolplansFAMINF2.861.312.911.272.881.30Otherfamilysinfluenceonpost-highschoolplansFRIENINF3.071.173.191.173.121.17Friendsinfluenceonpost-highschoolplansCURRDIFF0.640.480.930.260.750.43CurriculardifferentiationGPA2.250.773.080.642.570.83GradepointaverageSDHONOUR27.725.9829.726.5528.496.28%Grade12graduatesindistrictgraduatingwithhonourTEACHINF2.731.292.971.252.821.28Teachersinfluenceonpost-highschoolplansCOUNSINF2.431.302.431.312.431.30Counsellorsinfluenceonpost-highschoolplansDISTU23.791.703.151.963.541.83DistancefromnearestuniversityDISTCC1.551.621.701.621.601.62DistancefromnearestcommunitycollegeAWARDTOT1.761.082.021.061.861.08TotalnumberofawardsreceivedBELIEF23.650.633.570.693.620.66Beliefthat p.s.e.isnecessarytoprepareforajobBELIEF33.510.733.530.713.520.72Beliefthat p.s.e.isnecessarytoincreasemyincomeBELIEF63.510.753.580.723.540.74Beliefthatp.s.e.isnecessarytohaveawiderchoiceofjobsCorrelationsTable25.Discriminant FunctionAnalysis SummaryTable:Non-universityanduniversityparticipants.ofthepredictorvariableswiththePredictordiscnminantVariablesfunctionStepwiseAnalysis:StandardizeddiscriminantUnivariatefunctionF(1,3046)coefficients1234567891011121314151617181920StandardizeddiscriminantfunctioncoefficientsPooledwithin-groupcorrelationsamongpredictorsI.INTEREST0200.0948.670.091.0002.EXPECT0.410.21211.800.22.2461.0003.MOTHED0.190.0447.28.028.1031.0004.FATHED0.230.0764.630.13.058.146.5711.0005.FATHOCC0.180.0839.28.037.099.326.4891.0006.MOTHINF0.00-0.070.02.029.035.098.044.0351.0007.FATHINF0.030.052.87.050.029.057.130.086.6521.0808.FAMINF0.030.060.97.061.034.027-.024-.039.393.3731.0009.FRIENINF0.070.026.12.044.078.057.058-.048.274.223.3051.00010.CIJRRDIFF0.46020271.10021.115.177.098.082.074.023.031.029.0441.00011.GPA0.770.73754.500.73.054.199.091.049.023-.062-.064-.105-.034.3001.00012.SDHONOUR0220.1959.760.19-.026-.016.044.084.055.007.009.018.048.0130351.00013.TEACHINF0.130.0720.320.07.070.073.070-.064-.083.206.158.271.401.010.040-.0091.00014.COUNSINF0.00-0.020.00.008.001-.095-.079-.092.205.200.285.339.062-.048-.010.5761.00015.DISTIJ2-0.24-0.4172.56-0.40-.024.019.046-.052-.050-.041-.030-.020-.036.024.131-.499.001.0101.00016.DJSTCC0.060.404.930.40-.066-.059-.021-.078-.068.004.018.011-.030-.052-.046-.420.010.058.4321.00017.AWARDTOT0.160.0733.290.07.034.042-.026-.028-.030.070.040.079.162.073.053.056.206.190-.032-.0141.00018.BELIEF2-0.08-0.138.53-0.10.068.062-.040-.032.006.051.052.031.029.039.007-.041.082.073.057.037.0431.00019.BELIEF30.020.040.36.070.091-.012.004.030.036.028.039.040.035.026-.051.059.062.059.002.033.4791.00020.BELIEF60.060.045.28.073.077.019.056.048.079.101.074.087.050.023-.014.059.067.036.004.075.315.3641.000CanonicalREigenvalue0.59053194Table 25 contains the standardized canonical discriminant functioncoefficients. GPA makes the greatest contribution, followed by DISTU2 andDISTCC. Next in importance are EXPECT, CURRDIFF and SDHONOUR. Theother predictor variables appear to contribute considerably less to determining thediscriminant scores on this function.The structure matrix, displayed in Table 26 in descending order by size ofthe correlation with the discriminant function, shows that the discriminantfunction is most highly correlated with GPA (r.77), followed by CURRDIFF(r46). EXPECT (r.41), is moderately correlated with the discriminant function,as, to a lesser degree are DISTU2 (r=-.24), FATHED (r.23), and SDHONOUR(r.22).DISTU2 -.24FATHED .23SDHONOUR .22INTEREST .20MOTHED .19FATHOCC .18AWARDTOT .16TEACHJNF .13Table 26.Pooled Within-Groups Correlations (Structure coefficients) between Discriminating Variables andthe Canonical Discriminant Functions. Non-university and University Participants.GPA .77CUERDIFF .46EXPECT 41BELIEF2 -.08FRIENINF .07BELIEF6 .06DISTCC .06FATHINF .05FAMINF -.03BELIEF3 .02MOTHINF .00COUNSINF - .00195The three predictor variables most highly correlated with the discrirninantfunctions are, again, academic capital either as evidence of achievement or asconversion of cultural capital into achievement and expectations regardingeducational attainment One distance variable, one school environment variable, onecultural capital variable, and one disposition variable have moderately lowcorrelations with the discriminant function. Much lower correlations are obtainedbetween the remaining discriminating variables and the canonical discrirninantfunctions. It is noted that CURRDIFF has a relatively small standardizedcoefficient, but a large structure coefficient. This may be due to a moderatecorrelation (r=.30) between the GPA and CURRDIFF.The structure matrix and standardized coefficients indicate that variablesassociated with academic achievement, provide the most powerful predictors ofgroup membership. Participants attending university are more likely to havehigher grade point averages (rnean3.08) than non-participants (rnean2.25), havecompleted an academic program in high school (mean=.93) than non-participants(rnean.64), and expect to obtain higher levels of post-secondary education(mean4.43) than non-participants (mean3.67).University participants live closer to the nearest university (mean3.15)and farther from the nearest community college centre (rneanl.60) than non-university participants (mean=3.79 and 1.55, respectively). Fathers of universityparticipants have higher levels of education (rnean13.74) than fathers of nonuniversity participants (meanl2.73), and they were more likely to graduate fromhigh school districts with higher numbers of graduates on the honour roll(mean29.72) than non-participants (rnean27.72).Non-university and university participants do not differ on influence ofsignificant others, or social capital variables. Both groups report that they were196strongly influenced by their mothers and fathers (means3.87 and 3.86,respectively for university participants, means3.83 and 3.75 respectively for non-university participants). Teachers (mean=2.97 for university participants,mean2.73 for non-university participants), counsellors (mean2.43 for universityparticipants, mean2.43 for non-university participants), other family members(mean=2.91 for university participants, mean2.86 for non-universityparticipants), and friends (mean=3.19 for university participants, mean3.07 fornon-university participants) influence non-university and university participantsequally.ClassificationA classification matrix for this analysis is displayed in Table 27. Table 27reveals that 81% of the university participants and 75% of the non-universityparticipants are correctly classified. The total number of correct classifications is1863, or 77%.Table 27.Classification (Confusion) Matrix. Non-university and University Participants.Actual Group No. of cases Predicted Group Membership1 2Group 1 1484 1106 378Non-university participant 74.5% 25.5%Group 2 931 174 757University participant 18.7% 81.3%Percent of grouped’ cases correctly classified: 77.1%197The proportional error reduction statistic, tau, indicates that classificationmade on the basis of the discriminating variables made 54% fewer errors thanwould be expected by random assignment. That is, 552 actual errors, rather than1208 expected by chance, were made.Cross-validationA cross-validation analysis was carried out and the total sample of 2415was randomly split into 2 subsets. The first subset (n4204), comprised of 50% ofthe sample, was used to derive the classification functions. Using these functions,80% of the university participants and 74% of the non-university participants werecorrectly classified. The total number of correct classifications for this group was76%. When the classification functions derived from the first subset were used toclassify the 1263 cases in the second subset, 82% of the university participants and74% of the non-university participants were correctly classified. The proportionalerror reduction statistic, tau, indicates that classification on the basis of thediscriminating variables made 54% fewer errors than would be expected byrandom assignment. The results of the cross-validation procedure demonstratethat, in this sample, the classification functions are very stable.Stepwise Discriminant Function AnalysisA stepwise discriminant function analysis was also performed. Stepwiseinclusion of variables employed Wilks Lambda as the criterion for selection, with198the F-to-enter = 4.0, F-to-remove = 1.0, minimum tolerance level = 0.001. Table 28summarizes the F value for the change in Wilks Lambda when a variable isentered into the model. The upper triangle contains the F-to-remove for variablesentered into the model, and the lower triangle contains the F-to -enter for variablesnot yet entered into the model. The diagonal contains the F-to-enter for thevariable at the point it entered into the analysis.At the last step, 9 variables had F values of less than 4.0, and were notincluded in the model. These variables are: MOTHED, FATHOCC, MOTHINF,FATHINF, FAMINF, FRIENINF, COUNSINF, BELIEF3, and BELIEF6.Four variables-- grade point average (CPA), distance from nearestuniversity (DISTU2), expectations (EXPECT), and curricular differentiation(CURRDIFF), are important discriminating variables in both the direct analysisand stepwise analysis. Six other variables that were somewhat or lesser importantin the direct analysis were retained in the stepwise analysis. These variables were:number of graduates in the school district on the honour roll (SDHONOUR),fathers education (FATHED), the belief that post-secondary education isnecessary to become prepared for a job (BELIEF2), interest regarding level of post-secondary education attained (INTEREST), teachers influence (TEACHINF’), andnumber of awards received (AWARDTOT). One variable, distance from thenearest community college (DISTCC) was important as a structure coefficient butweak as a structure coefficient in the direct analysis, was extracted third instepwise analysis.Results of the stepwise analysis are generally consistent with the directanalysis, as demonstrated in Table 25. Table 25 compares the standardizedcoefficients and the structure matrix of the direct analysis with the standardizedcoefficients stepwise analysis.•NotenteT0.58CanonicalKChisquale(U’)0ThPorderp.nalyStseDISCSaflniNersitYpartiCtPtTable28.StePW.t5anduNon1Jflet5itYp1098TFJCI1kWP.WTOT6INT1EST13EL12pjwD32)G?ECtCUOLSTCCl,IST1JZIGP.£rLtere&477.3984615654.1217756174.2879.139.28GPPtISTU2 0STCCCUKKt)pjl-IEDBEU2INTEI9TTEACI1469.5100.9297.3553.7799.7399.0345.4936.2772,564,93211.77271.1059.76.5348.6720.3233.29459.6197.2899,4847,4837.2421.4256.7657.6434.17 7.348.81459.8295.051020337.1334.4922.712.554.6923.4230.23 4.6322.77.1951.7 6.5226.04 4.2519,07 8.1310,81453.0193.97100,8235.0734,7622.6713.808.586,68448.2993.0999.8034,7033.1721.5614.198.86 6.5525.2019.09 6.978.254.4513.04•kTIOC•MOT•AT1N•pMlN•COUNS1N•13EL1?3•BEUE639.28o.032,870.97 6.110.000.36 5.2824.192.649.1411.50 8.801.360.012.13iS.131.537,4410.56 6.587,720,243.1421.241.14 6.039.757,24 0,700.463,3914.50.43 4,276.913.88 0.51 0.001,500.173.06,06 2.801.050,020,9710,840.202.974,64 2.25o.930,000.932.96o,09 1.585.123.19o,00 0.633.170.191.96 5,423.392.03 2.102,883,20 0.161,674,783.151.92 1,912.53.800.02o.792.45 0.720,00 1,782,263,880,030,762.300.47o.07 1,721,921004,30p<.001200Table 29 displays the results of the classification procedure whenclassification coefficients are derived from 11 rather than the original 20 variables.Table 29.Stepwise Analysis Classification (Confusion) MatrixNon-university and University Participants.Actual Group No. of cases29 Predicted Group Membership1 2Group 1Non-university participant 1705 1271 43474.5% 25.5%Group 2 1051 202 849University participant 19.2% 80.8%Percent of “grouped cases correctly classified: 76.9%When Table 29 is compared with Table 28, it appears that classification of casesbased on 11 variables retained in the stepwise analysis, rather than the original 20variables, is almost as effective.A stepwise discriminant cross-validation analysis was carried out with a50% randomly generated subset of the sample (n1204), 7 variables remained inthe analysis at the last step. The following table compares the variables retainedand order they are entered in 1) the stepwise analysis conducted with the totalsample, and 2) the same stepwise analysis employing a cross-validationprocedure:29 Because fewer variables are employed, the number of cases classified increases by 341.201StepwiseStepwise Cross validationGPA 1 1DISTU2 2 2DISTCC 3 3EXPECI’ 4 5CURRDIFF 5 4SDHONOUR 6 6FATHED 7 7BELIEF2 8INTEREST 9TEACHINF 10AWARDTOT 11The classification coefficients, derived from 7 variables and used to classify 1635cases in the first subset, resulted in correct classification of 81% of the universityparticipants and 77% of the non-university participants. When the classificationfunctions derived from the first subset were used to classify the 1591 cases in thesecond subset, 80% of the university participants and 77% of the non-universityparticipants were correctly classified.Based on the results of the direct and stepwise discriminant analyses, giventhis sample of grade twelve graduates and the set of measures used, the followingvariables best predict group membership:1. grade point average2. curricular differentiation3. level of education expected4. distance from university5. distance from community college6. father’s education7. number of graduates in school district on honour rollThe remaining predictor variables appear to contribute little additionaldiscriminating power, or provide redundant discriminating information withthose variables retained in the analysis.202Gender DifferencesTable 30 displays the standardized discriminant function coefficients,structure coefficients, and the variables retained in a stepwise analysis, separatelyfor men and women.The canonical correlation for the male sample is higher (r.62) than for thefemale sample (r=.57), indicating that the degree of association between thediscriminant scores and the groups is stronger for males than for females. Thestandardized canonical discriminant function coefficients and structurecoefficients also provide somewhat different information for men and women.The structure coefficients reveal (Table 31) that grade point average, is byfar the most important discriminating variable. For men, however, the correlationbetween grade point average and the discriminant function is considerably higher(r.81) than it is for women (r.71). For men, the amount of education wanted(r=.24) is more important in determining choice of institution attended than it isfor women (r=.16). For women, the number of awards received and teachersinfluence are more important (r.22 and .18) than they are for males (r.11 and.07).CorrelationsofthepredictorTable30.DiscriminantFunctionAnalysisSummaryTable.Non-universityandUniversityParticipants -FemalesandMales.femalemalefemalemalefemalemale1234567891011121314151617181920variableswithStandardizedVariablesthediscriminantretainedinPredictordiscriminantfunctionstepwiseVariablesfunctioncoefficientsanalysisPooledwithin-groupcorrelationsamongpredictors*1.INTEREST0.280.290.120.03*.201.050.063.052.020.032.015-.004.124.043-.017.047-.026-.026-.101.036.079.091.0602.EXPECT0.560.600.300.30**.310.102.125.085.067.036.060.083.189.163-.022.066-.014-.005-.060.035.059.125.0943.MOTHED0.230.160.04-0.04*.000.103.537.301.113.069-.012-.075.121.086.040-.078-.139.050-.016.004.008.015.0184.FATHED0.230.250.040.06*.057.170.616.478.049.134-.020-.079.071.017.080-.036-.096-.083-.081-.019-.008.023.0335.FATHOCC0.140.200.030.04.016.119.360.505.050.090-.030-.074.071-.014.039-.082-.119-.064-.077-.033.029.061.0476.MOTHINF0.470.380.180.18.030.004.082.051.014.650.404.272.039-.045-.002.184.196-.004.031.038.047.071.0787.FATHINF0.470.370.230.16.071.025.041.131.082.655.389.190.046-.068.005.154.202-.007.031.027.052.045.0658.FAMINF0.310.230.000.05*.119.005-.046-.020-.051.369.345.314.033-.132.002.253.276.003.056.059.030.048.0719.FRIENINF0.330.240.11-0.07.102.081-.029-.022-.012.261.259.281.027-.036.019.373.315-.004-.003.125.007.038.05910.CURRDIFF0.620.650.380.38**.099.161.065.098.076-.001.009.022.066.280.018.006-.100.012-.058.077.019.026.02311.GPA0.500.640.260.34**.063.251.098.095.074-.089-.060-.065-.032.326-.057.036-.063.133-.032.050-.021.024.03312.SDHONOUR0.060.190.020.06**-.037-.009.049.087.076.024.016.044.092.006-.002-.015-.023-.495-.410.061-.080-.070-.03013.TEACHINF0.370.360.030.18.102.089-.057-.096-.083.229.160.289.434.017.051.002.580.001.046.185.064.041.05214.COUNSINF0.290.240.150.01.051.031-.033-.049-.053.205.192.289.364-.006-.025.010.568.004.089.155.038.047.04815.DISTIJ2-0.03-0.140.02-0.05**-.020.052.040-.010-.029-.091-.062-.054-.082.042.130-.504.000.018.443-.055.082.073.04716.DISTCC0.00-0.100.04-0.06**-.019-.056-.026-.071-.056-.037-.003-.062-.073-.042-.066-.433-.047.009.416-.057.053.015.02517.AWARDTOT0.440.410.280.24*.028.060-.064-.030-.027.089.047.087.195.066.058.052.225.226-.003.037.000.022.04218.BELIEF20.080.170.050.01*.051.067-.101-.059-.023.053.052.034.055.064.040.009.107.117.025.017.094.459.32219.BELIEF30.060.19-0.050.11.040.036-.054-.028-.016-.004.007.035.050.047.027-.021.093.092.039-.016.059.512.38520.BELIEF60.100.10-0.04-0.08.086.063.021.090.050.066.137.068.109.083.011.009.062.081.022-.027.101.309.349CanonicalREigenvalue0.570.620.470.63t’J c)*Correlationsformalesampleinlowertriangle,forfemalesampleinuppertriangle204Table 31.Pooled Within-Groups Correlations (Structure Coefficients) between Discriminating Variables andthe Canonical Discriminant FunctionsNon-university and University Participants.- Females and Males.Female MaleGPA .73 .81CURRDIFF .44 .48EXPECT .39 .41DISTU2 -.24 -.23FATHED .24 .20AWARDTOT .22 .11SDHONOUR .22 .21MOTHED .19 .19TEACHINF .18 .07FATHOCC .17 .18INTEREST .16 .24BELIEF2 -.12 -.03FRIENINF .10 .05BELIEF6 .10 .04DISTCC .08 .04FAMINF .07 -.01FATHJNF .07 .03COUNSINF .03 -.02BELIEF3 -.02 .05MOTHINT .01 .02Results of the classification matrix for each group are displayed in Table 32.205Table 32.Classification (Confusion) MatrixNon-university and University Participants - Female and Male Sample.Actual Group No. of cases Predicted Group Membership1 2FemaleGroup 1Non-university participant 905 664 24173.4% 26.6%Group 2 500 95 849University participant 19.0% 81.0%Percent of “grouped” cases correctly classified: 76.1%MaleGroup 1Non-university participant 579 443 13676.5% 23.5%Group 2 431 71 360University participant 16.5% 83.5%Percent of ‘grouped’ cases correctly classified: 79.5%Overall, the discriminating variables are slightly better at predicting groupmembership for the male sample. In both the non-university and universitygroups, women are slightly more likely to be misclassified.SummaryIn the first set of analyses, academic achievement variables and primary andsocial capital variables, accounted for most of the discrimination betweenparticipants and non-participants in post-secondary education. In this second set206of analyses, the same set of predictor variables was used to determine which linearcombination of these best predicted whether one attended a non-university oruniversity institution. Clearly, grade point average was most important, across allanalyses, in predicting group membership. Curricular differentiation, level ofpost-secondary education expected, distance from the nearest university andcommunity college centre, and father’s education contribute most to the predictionof group membership. These variables have a differential impact on males andfemales. Unlike the first analysis, social capital variables, both primary andsecondary, were not important predictors.Non-participation, Non-university Participation, or University Participationin Post-secondary EducationA third set discriminant function analyses were carried out to determinethe dimension or dimensions groups of non-participants, non-universityparticipants, and university participants differ, and which set of predictorvariables best predicts group membership.The grouping variable for these analyses, STATPS, consists of three groups:1) non-participants, 2) non-university participants, and 3) university participants.Of the total sample of 4818 high school graduates, 1252 reported that they had notparticipated in some form of post-secondary education, 2316 indicated that theywere non-university participants, and 1250 stated that they were universityparticipants.Of the total sample of 4818, the 1690 cases containing missing values weredropped from the analysis. Of a total of 3128 remaining cases, the number of nonparticipants is 713 (23%), non-university participants is 1484 (47%) and university207participants is 931 (30%). In the total sample, 1252 are non-participants (26%),2316 (48%) are non-university participants, and 1250 (26%) are universityparticipants. Thus, questionnaires completed by non-participants contain moremissing data, and those completed by university participants contain less. As inthe first analysis, however, missing data appear to be scattered over variables andgroups.Since the same 20 predictor variables used in the previous two analyses areused in this analysis, the previous discussion of multivariate normality is relevantto this analysis. In this analysis, the Box’s M test is again significant (F4.20, p<.001). It is assumed that the large sample size will ensure robustness with respectto heterogeneity of the covariance matrices.Direct AnalysisTable 33 displays the means and standard deviations for each of thegroups and the total sample. Table 34 provides a summary of the interpretationphase of this analysis.Significance tests for equality of group means was carried out for eachvariable and are displayed in Table 34. The F value, with 2 and 3125 df, for eachvariable indicates significant differences between group means (p <.001) for all butone variable, DISTCC.Two discriminant functions were calculated with a combined2(40)2099.0, p < .001, indicating a highly reliable relationship between groupsand predictor variables. After the first function was removed, there was still asignificant association between the groups and the predictors,Table33.MeansandStandardDeviations:Non-participants,non-universityparticipants,anduniversityparticipants.VariableNon-participantNon-universityUniversityTotalDescriptionmeans.d.means.d.means.d.means.d.INTEREST4.771.505.161.175.460.815.161.19HighestlevelofeducationwantedEXI’ECT2.791.573.671.334.431.093.701.45HighestlevelofeducationexpectedMOTHED11.992.2612.432.4513.152.5712.552.48MotherseducationFATHED12.082.7112.733.0313.742.9712.883.00FatherseducationFATHOCC47.8914.9450.2015.4154.2415.3950.8715.47Father’soccupationMOTFIINF3.131.353.861.063.871.043.701.17Mother’sinfluenceonpost-highschoolplansFATHINF3.001.363.751.153.831.113.601.24Father’sinfluenceonpost-highschoolplansFAMINF2.351.252.861.312.911.272.761.31Otherfamily’sinfluenceonpost-highschoolplansFRIENINF2.601.683.071.173.191.173.001.19Friends’influenceonpost-highschoolplansCURRDIFF0.330.470.640.480.930.260.660.47CurriculardifferentiationGPA1.870.742.240.773.080.642.410.86GradepointaverageSDHONOUR27.406.1627.715.9829.726.5528.246.27%Grade12graduatesindistrictgraduatingwithhonourTEACHINF2.111.232.731.292.971.252.661.31Teachers’influenceonpost-highschoolplansCOUNSINF1.911.142.431.302.431.312.311.29Counsellors’influenceonpost-highschoolplansDISTU23.761.673.791.703.151.963.591.80DistancefromnearestuniversityDISTCC1.711.671.551.621.701.621.631.63DistancefromnearestcommunitycollegeAWARDTOT1.131.221.761.082.021.061.691.15TotalnumberofawardsreceivedBELIEF23.490.803.650.633.570.693.590.70Beliefthatp.s.e.isnecessarytoprepareforajobBELIEF33.390.863.510.733.530.713.490.76Beliefthatp.s.e.willhelptoincreasemyincomeBELIEF63.420.823.510.753.580.723.510.76Beliefthatp.s.e.willleadtoawiderchoiceofjobsL’JTable34.DiscriminantFunctionAnalysisSummaryTable:Non-participants,non-universityparticipants,anduniversityparticipants.CorrelationsofthepredictorvariablesPredictorwiththediscriminVariablesantfunctionsStepwiseAnalysis:StandardizedStandardizeddiscriminantdiscriminantfunctionUnivariatefunctioncoefficientsF(1,3045)coefficients12212345678910111213141516171819200.250.510200240.180240260.170200.580.720.170270.15-0.160.010.320.030.07 0.090.110.090.010.190270.17-0.050.03-0.05-0.050.05-0.01-0.050.06-0.030.570.050370.510.140.180320.05-0.040280.030.000.180.29030-0.360.58-0.52-0390.13-0.160300.100.020360.030.180.27-0.220.43-0.160.20-0.430340.200240.29-0.070.250.130.04-0.040.040.00-0.1472.33311.5048.4468.4537.52117.30117.2047.5856.41398.60619.5038.4497.3646.0141.553.63135.8014.028.698.99.049-.017-.023-.040.431.084-.050-.050-.033.294.196.111.108.094.013.206.107.078.042-.048.000.010.086.072-.010.080-.055-.052-.085.251.021-.077-.067-.101.234.002.029-.072-.068-.027-.046-.018-.075-.074.024.067-.028-.033-.036.127.096-.020-.018.013.071.112.003.019.017.051.086.025.058.046.075Pooledwithin-groupcorrelationsamongpredictors0.100.000.280.161.0001.INTEREST2.EXPECT3.MOTtlED4.FATHED5.FATHOCC6.MOTHINF7.FATHINF8.FAMINF9.FRIENINF10.CURRDIFF11.GPA12.SDHONOUR13.TEACHINF14.COUNSINF15.DISTIJ216.DISTCC17.AWARDTOT18.BELIEF219.BELIEF320.BELIEF6.2311.000.035.1171.0000.10-0.07.055.158.5521.000.057.104.295.4691.0000.08037.045.065.081.044.0171.0000.150.19.056.067.044.118.065.6911.000.059.055030029.1070.58-0.54.0470.13-0.16-.0060.130.12(165.023-0.210.43-.0410.20-0.43-.0540.20023.060-0.050.19.117.087.087.3921.000.236.3201.000.022.017.0341.000-.051-.090-.039.3451.000.005.009.036.020-.0091.000.195.289.396.014.038-.0101.000.212.295.339-.049-.045-.013.5951.000-.021-.010-.032-.005.093-.486.005.0211.000.020.020-.018-.057-.036-.409.021.060.4131.000.093.095.176.074.034.036.207.199-.014.0121.000.072.041.027.061.006-.039.065.062.058.036.0601.000.043.044.041.040.008-.049.053.052.064.006.0354901.000.100.054.066.054.019-.026.051.064.043.000.070.3353781.000Canonical R0.65029Eigenvalue0.740.09I’J210x2 (19)281.44, p < .001, indicating that the second discriminant function is alsoreliable. The canonical correlation for the first and second discriminant function(.65 and .29, respectively), indicate a moderately strong relationship between thegroups and the discriminant function, with the first discriminant function overtwice the magnitude of the second. The eigenvalues associated with thediscriminant functions indicate that 89% of the explained between-groupvariability is accounted for by the first discrirninant function, and 11%, by thesecond.The mean discriminant scores for each group on a function, or groupcentroids, are displayed in Table 35 and plotted, in Figure 22, along thediscriminant function axes.Table 35.Canonical Discrinünant Functions Evaluated at Group Means (Centroids).Group Function 1 Function 21 -1.20 -0.372 - 0.15 0.323 1.16 -0.23The first discriminant function (X axis), which provides the best separation amongthe groups, separates the non-participant from the university group, with the nonuniversity group almost midway between. On the second discriminant function (Yaxis), which is orthogonal to the first, non-participants are separated from nonuniversity participants, with university participants located between the twogroups.2111.51.251.0.75(non-uniw rsity).50 -.25SecondDi scri mi na ntFurtion 0.-.25 (uniwrsity).-.50 -(non-participant)-.75-1.0 --1.25-1.5 I-1.5 -1.25 -1.0 -.75 -.50 -.25 0 .25 .50 .75 1.0 1.25 1.5First discriniinant furtionTiqure 22: Ptht ofgroup CeiitroidcIn this analysis with two discrirninant functions, the standardized coefficients andstructure coefficients are used to interpret which variables account for maximalseparation among groups on each function.The structure matrix is displayed in Table 36 in descending order by size ofthe correlation with each discriminant function. Table 36 shows that the firstdiscriminant function is most highly correlated with GPA (r=.72), followed byCURRDIFF (r.58), and EXPECT (r.51). INTEREST (r=.25), FATHED (r=.24), and212MOTHED (r=.20) have moderately low correlations with the discriminantfunction.Table 36.Pooled Within-Group Correlations (Structure coefficients) between Discriminating Variables andthe Canonical Discriminant Functions. Non-participants, Non-university Participants, andUniversity Participants.Function Function1 2GPA .72* -.36CURRDIFF .58* .18EXPECT 51* .19INTEREST .25* .11FATHED .24* -.05MOTHED .20* -.05FATHOCC .18* -.05BELIEF6 .09* -.04MOTHINF .24 57*FATHINF .26 .51*COUNSINF .15 .36*AWARDTOT .32 34*FAMINF .17 .32*TEACHINF .27 .30*BELIEF2 .03 .29*FRIENINF .20 .28*DISTU2 -.16 .27*SDHONOUR .17DISTCC .01BELIEF3 -.07 .13*The second discriminant function is correlated most highly with MOTHINF(r.57), FATHINF (r.51), followed by COUNSINF (r.36), AWARDTOT (r=.34),FAMINF (r.32), and TEACHINF (r.30). Less highly correlated are BELIEF2(r.29), FRIENINF (r.28), and DISTU2 (r=.27).The structure matrix suggests that the best predictors for distinguishingbetween university participants from the other two groups are of three types.Academic achievement variables, grade point average and curricular differentiation,are the most powerful, followed by expectations, and level of education desired.213Less powerful, but loading on the first function are all of the cultural capitalvariables, mother’s and father’s education, and father’s occupation. Universityparticipants have higher grade point averages (rnean3.08) than non-participants(rnean4.88) or non-university participants (mean2.25) and are more likely tograduate from an academic program in high school (mean.93) than non-participants (mean=.33) or non-university participants (mean=.64). Universityparticipants both expect and want to attain higher levels of education (rnean=4.43and 5.46, respectively) than non-participants (mean=2.79 and 4.77, respectively) ornon-university participants (rnean=3.67, 5.16, respectively. Mothers and fathers ofuniversity participants have aftained higher levels of education (meanl3.15 and13.74 respectively) than mothers and fathers of non-participants (mean41.99 and12.08, respectively) and parents of non-university participants (meanl2.43 and12.73, respectively). Fathers of university participants have a higher occupationalstatus (rnean54.24) than non-participants (mean47.89) and non-universityparticipants (mean50.20).The second discrirninant function, which separates the non-participantgroup from the non-university group, with the university group in between, isclearly dominated by social capital variables (influence of family and influence ofschool personnel) one belief variable (BELIEF2) and one evidence of achievement(AWARDTOT) variable. It is not readily apparent, upon examination of groupmeans on these variables, how non-university participants differ from the othertwo groups - university participants and non-participants, and what the latter twogroups have in common. Non-university participants reported that their mothers,fathers, and other family members influenced them slightly less (mean3.86, 3.75,and 2.86 respectively) than university participants (mean3.87, 3.83, and 2.91respectively), yet much more than non-participants (mean3.13, 3.00, and 2.35214respectively). Also, counsellors and teachers had slightly less of an influence onthe post-high school plans non-university participants (mean=2.43 and 2.73,respectively) than university participants (mean2.43 and 2.97, respectively), butmore than on non-participants (mean=1.91 and 2.11, respectively). Universityparticipants received more academic awards (mean2.02) than non-universityparticipants (meanl.76) and non-participants (mean4.13). Group means of non-university participants and university participants are very similar on thesevariables, compared with group means of non-participants.Group means of several other variables that load on this seconddiscriminant function may help to explain why the non-university group isseparated from the university and non-participant groups. Non-universityparticipants expressed a stronger belief that post-secondary education wasnecessary to prepare them for a job (mean3.65) than both the university group(mean3.57) and non-participant group (mean4.49). DISTCC (r-.16) has a weaknegative correlation with the discrirninant function. Group means reveal non-participants (mean4.71) and university participants (mean4.69) live fartheraway from community college centres than non-university participants(meanl.55). Thus, while non-university and university participants are morealike than non-participants on several variables, non-participants and universityparticipants are more similar than non-university participants on two variables.ClassificationA classification matrix for this analysis is displayed in Table 37. Table 37reveals that 81% of the university participants, 50% of the non-university215participants, and 67% of the non-participants are correctly classified. The totalnumber of correct classifications is 1960, or 63%.Table 37.Classification (Confusion) Matrix. Non-participants, Non-university Participants, and UniversityParticipants.Actual Group No. of cases Predicted Group Membership1 2 3Group 1 713 477 160 76Non-participant 66.9% 22.4% 10.7%Group 2 1484 378 734 372Non-university participant 25.5% 49.5% 25.1%Group 3 931 23 159 749University participant 2.5% 17.1% 80.5%Percent of grouped’ cases correctly classified: 62.9%The proportional error reduction statistic, tau, indicates that classificationmade on the basis of the discriminating variables made 25% fewer errors thanwould be expected by random assignment. That is, 1168 actual errors, rather than1564 expected by chance, were made. Of these errors, 48% were the result ofmisclassification of the 50% non-university group into either the university groupor non-participant group.216Cross-validationA cross-validation analysis was carried out to test the stability of theclassification procedure. The total sample of 3128 was randomly split into 2subsets, and the first subset (n=1565), comprised of 50% of the sample, was usedto derive the classification functions. Using these functions, 82% of the universityparticipants, 46% of the non-university participants, and 69% of the non-participants were correctly classified. The total number of correct classificationsfor this group was 62%. When the classification functions derived from the firstsubset were used to classify the 1566 cases in the second subset, 82% of theuniversity participants, 47% of the non-university participants, and 66% of thenon-participants were correctly classified. The proportional error reductionstatistic, tau, indicates that classification on the basis of the discriminatingvariables made 23% fewer errors than would be expected by random assignment.Results of the cross-validation procedure demonstrate that the classificationprocedure is quite stable.Stepwise Discrirninant Function AnalysisA stepwise discrirninant function analysis was also performed. Stepwiseinclusion of variables employed Wilks’ Lambda as the criterion for selection, withthe F-to-enter = 4.0, F-to-remove = 1.0, minimum tolerance level = 0.001. The Fvalue for the change in Wilks Lambda when a variable is entered into the modelis summarized in Table 38. The upper triangle contains the F-to-remove forvariables entered into the model, and the lower triangle contains the F-to-enter forTable38.StepwiseDiscriminantFunctionAnalysis:STEPNon-participants,non-universityparticipants,anduniversityparticipants.012345678910111213OrderVariablesEnteredCPAEXPECTMOTHJNFCURRDIFFDISTU2AWARDTOTDISTCCFATI-IINFTEACHINF5DHONOURFATFIEDBEUEF2INTERESTCanonicalR1. 2.1.Chisquare(26)2.ChiSquare(12)0.650.291987.5p<.001270.02p<.OO1GPA619.541619.54410.58418.28254.83270.30264.45270.30272.32266.62261.08255.14252.05252.39EXPECT311.54132.15132.15109.0677.4075.5368.0869.3266.6763.0663.5357.2057.4448.12MOTHINF117.27116.8093.9393.9386.0985.4667.4367.4813.9710.8910.8110.8510.6510.69CURRDIFF398.56127.3088.8181.0081.0077.6468.4069.2767.0867.9867.8965.2765.1962.61DISTU241.5555.6251.7050.7347.4347.4446.6572.9172.7072.6542.5641.3439.8438.73AWARDTOT135.8396.0176.8655.6246.1245.3345.3344.7144.0434.4333.3534.1334.0233.11DJSTCC3.634.795.135.355.6831.8031.2031.2031.0630.8538.3638.8939.0439.81FATHINF117.16115.6891.5116.2913.8513.7513.0912.9512.9512.1011.7710.1010.069.73TEACHINF97.3666.8050.1022.7722.8422.9112.8812.6511.8011.8011.8812.7912.8112.22SDHONOUR38.4429.8828.4128.5626.364.603.7711.3010.9711.0511.0410.1310.0010.51FATHED68.4529.21143112.599.336.397.708.606.957.916.996.996.686.46BELIEF214.0213.8510.638.288.086.105.906.176.176.206.045.735.736.20INTEREST72.3341.8114.5312.107.966.845.455.885.394.845.335.165.625.62!•MOTHED48.4413.576.604.723.333.874.514.915.075.884.940.930.850.83•FATHOCC37.5218.5410.369.786.874.565.566.455.586.766.152.112.232.06•FAMINF47.5860.6345.639.647.337.505.895.733.721.761.571.931.891.71•FRIENINF56.4155.4137.9512.7910.187.584.574.764.100.970.811.101.050.99•COUNSINF46.0148.6641.1417.4520.0320.5511.1911.109.512.962.993.002.892.93•BELIEF38.696.772.131.080.800.680.460.460.410.290.320.311.711.61•BELLEF68.984.951.470.490.220.610.520.660.710.740.780.712.752.70NotenteredL’3218variables not yet entered into the model. The diagonal contains the F-to-enter forthe variable at the point it entered into the analysis.At the last step, only 7 variables had F values of less than 4.0, and were notincluded in the model. These variables are: MOTHED, FATHED, FAMINF,FRIENINF, COUNSINF, BELIEF3 and BELIEF6.Table 38 compares the standardized coefficients and the structure matrix ofthe direct analysis with the standardized coefficients obtained in the stepwiseanalysis. Since most of the variables, both individual and institutional in nature,were retained in the stepwise analysis involving three groups, it supports the useof Härnqvist’s schema of determinants of educational choice as part of theconceptual framework for this study.Table 39 displays the results of the classification procedure whenclassification coefficients are derived from 13 rather than the original 20 variables.Table 39.Stepwise Analysis Classification (Confusion) Matrix. Non-participants,Non-university Participants, and University Participants.Actual Group No. of cases3° Predicted Group Membership1 2 3Group 1Non-participant 828 557 187 8467.3% 22.6% 10.1%Group 2 1697 466 810 421Non-university participant 27.5% 47.7% 24.8%Group 3 1047 30 179 838University participant 2.9% 17.1% 80.0%Percent of ‘grouped’ cases correctly classified: 61.7%30 Because fewer variables are employed, the number of cases classified increases by 444.219When Table 39 is compared with Table 37, it appears that classification of casesbased on 13 variables retained in the stepwise analysis, rather than the original 20variables, is almost as effective.A stepwise discriminant cross-validation analysis was carried out with a50% randomly generated subset of the sample (n4565), 9 variables remained inthe analysis at the last step. The following table compares the variables retainedand order they are entered in 1) the stepwise analysis conducted with the totalsample, and 2) the same stepwise analysis employing a cross-validationprocedure:StepwiseStepwise Cross validationGPA 1 1EXPECT 2 4MOTHINF 3 3CURRDIFF 4 2DISTU2 5 6AWARDTOT 6 5DISTCC 7 7FATHINT 8TEACHINF 9 8SDHONOUR 10FATHED 11 9BELIEF2 12INTEREST 13The classification coefficients, derived from 9 variables and used to classify 2029cases in the first subset, resulted in correct classification of 83% of the universityparticipants, 46% of the non-university participants, and 68% of the nonparticipants. When the classification functions derived from the first subset wereused to classify the 1966 cases in the second subset, 77% of the universityparticipants, 43% of the non-university participants, and 70% of the nonparticipants were correctly classified.220From the results of the direct and stepwise discriminant analyses, it may beconcluded that, given this sample of grade twelve graduates and the set ofmeasures used, the following variables best discriminate among the groups alongtwo dimensions. The first dimension is characterized by achievement, disposition,and cultural capital variables, and the second dimension is comprisedpredominantly of primary and secondary social capital variables.Gender DifferencesThe standardized discrirninant function coefficients, structure coefficients,the variables retained in a stepwise analysis, are displayed separately for men andwomen, in Table 40.The canonical correlation summarizes the degree of relatedness betweenthe groups and the discnminant function. For the first function, the canonicalcorrelation for the male sample is slightly higher (r.68) than for the femalesample (r=.64); for the second function, while less important for both groups, it isslightly higher for females (.30) than males (.28). Also, the two discriminantfunctions account for 91% and 9% of the explained between-group variability forthe male sample, and 87% and 13% for the female sample; thus, the seconddiscriminant function is more important for females than it is for males.The structure coefficients that load on a given function, for females andmales, are contained in Table 41. Males and females differ in two ways: thevariables that load on each discrirninant function, and the relative importance ofthese variables within each function.CorrelationsofthepredictorvariableswiththediscriminantfunctionsTable40.DiscriminantFunctionAnalysisSummaryTable.Non-participants,non-universityanduniversityparticipants-FemalesandMales.Standardizeddiscriminantfunctioncoefficients0.640.680.300.280.690.830.100.0887.0990.7512.919.25PredictorVariables11221122femalemalefemalemalefemalemalefemalemaleVariablesretainedinstepwiseanalysisfemalemalePooledwithin-groupcorrelationsamongpredictors*12345678910111213141516171819200.230.260.150.050.500.520.170.230.220.180.01-0.120.250.23-0.060.010.160.19-0.07-0.020.270.210.570.520.300.210.500.480.210.110.270.350.240.150.260,260.570.580.170.200.650.78-0.37-0.350.140.20-0.25-0.080.31)0.220.200.410.180.110.320.38-0.13-0.090.320.200.04-0.03-0.12-0.210.360.270.250.41-0.010.070.280.300.030.120.100.190.100.07-0.020.071.INTEREST2.EXPECE3.MOTHED4.FATHED5.FATHOCC6.MOTHINF7.FATHINF8.FAMINF9.FRIENINF10.CURRDIFF11.GPA12.SDHONOUR13.TEACHINF14.COUNSINF15.DISTU216.DISTCC17.AWARDTOT18.BELIEF219.BELIEF320.BELIEF6CanonicalREigenvalue%ofvariance0.120.270.050.080.070.020.170.050.110.300.540.130.080.08-0.200.26 0.25-0.06-0.030.030.070.260.020.020.050.100.090.04-0.040.280.630.110.12-0.03-0.240.140.14-0.090.130.05-0.070.170.210.00-0.14-0.060.10-0.07-0.010.390.240.200.22-0.090.030.04-0.100.270.34-0.51-0.550.210.08-0.07-0.050.220.090.440.38-0.42-0.440.170.300.250.21-0.050.02.177.064.069.074.036.045.022.012.111.023-.005.052-.010-.027-.077.053.118.089.085.300.124.140.094.079.065.075.071.196.186.006.073.001-.017-.065.048.058.108.090.002.106.533.293.104.059-.005-.069.132.101.029-.065-.117.038-.024-.016.033.027.046*.043.177.577.459.061.130-.011-.076.094.061.070-.032-.091-.085-.088-.022.009.031.052.035.118.298.454.035.076-.035-.062.075.015.058-.093-.133-.073-.086-.044.040.046.050**.049.056.057.033-.006.671.421.290.025-.036-.013.230.216-.005.019.089.062.053.075.068.071.024.106.052.717.379.205.040-.049.020.018.200-.015-.004.076.059.041.076.100.020-.032-.031-.048.437.406.329.043-.095.004.275.282.002.045.071.037.048.053*.103.108-.024-.012.002.289.269.300.014-.048.023.369.314-.006-.005.130.008.030.046**.100.196.083.127.118-.006.000-.1318.060.330.015.028-.080-.010-.077.071.055.039.025*.070.235.119.105.077-.069-.051-.084-.029.363-.038.036-.064.098-.1)35.020-.020.009.027-.007-.008.058.107.089-.005-.011.019.055.027,02S-.010-.021-.484-.398.031-.065-.065-(130*.081.095-1)39-.1173-.076.273.206.303.428-003.042-009.586.002.377.184.054.051.053•.061.055-.022-.031-.059.247.223.31)6.367-.006-.019-.002.604.020.081.175.035.045.051*-.056.027.014-.055-.060-.053-.029-.027-.066.002.090-.483.008.024.428-.033.077.073.047*-.1)26-.019-.012-.057-.055.023.049-.016-.039-.031-.034-.422-.005.028.392-.018.053.018.004**.065.101-.039-.036-.028.156.109.113.223.077.050.043.229.220.012.049.029.024.052.112.144-.077-.045-.020.079.088.046.047.067.032-.013.078.093.040.018.091.469.318.084.115-.027.002-.023.054.055.044.061.041.002-.032.061.065.048-.007.053.519.398-0.02-0.17-0.15.086.089.004.073.042.065.124.047.080.087.006-.024.044.072.041-.005.081.351.361*Correlationsformalesampleinlowertriangle,forfemalesampleinuppertriangle222Table 41.Pooled Within-Groups Correlations (Structure coefficients) between Discriminating Variables andthe Canonical Discriminant Functions. Non-participants, Non-university Participants andUniversity Participants - Females and Males.Function Function1 2female male female maleGPA .65* .78*CURRDIFF 57* .58*EXPECT .50* .52*AWARDTOT .36* .41*TEACHINF .30* .41*FATHED .25* .23*INTEREST .23* .26*MOTHED .22* .18*FATHOCC .16* .19*BELIEF6 .10* .07*MOTHINF 57* .52*FATHINF .50* .48*DISTU2 .32* .20*COUNSINF .32* .38*BELIEF2 .28* .30*FAMINT .27* 35*FRIENINF .26* .26*SDHONOUR .20*DISTCC -.12BELIEF3 .10* .19*For both men and women, achievement variables, along with expectations,load on the first function. While there is little difference in the magnitude of thecorrelations of curricular differentiation and expectations with the discriminantfunction for men and women, grade point average is more highly correlatedwiththe first discrirninant function for men than for women. For women, the totalnumber of awards received and teachers’ influence load on the first function, andboth have moderate correlations with the discriminant function.For both males and females, variables contributing the most to the seconddiscriminant function are mother’s influence and father’s influence. Next in223importance for males are total number of awards received and teachers influence,followed by the influence of family and friends. For females, distance fromuniversity and counsellors influence are moderately correlated with thediscriminant function.The classification matrix (Table 42) indicates that slightly betterclassification of cases is achieved with the male sample. For both males andfemales, the highest number of misclassifications occur in the non-universitygroup. While equal percentages of males and females are correctly classified asnon-university participants, female non-university participants are more likely tobe classified in the university group, and males in the non-participant group.224Table 42.Classification (Confusion) Matrix - Non-participants, Non-university Participants and UniversityParticipants. Females and Males.Actual Group No. of cases Predicted Group Membership1 2 3FemaleGroup 1 372 252 82 38Non-participant 67.7% 22.0% 10.2%Group 2 905 211 453 241Non-university participant 23.3% 50.1% 26.6%Group 3 500 13 85 402University participant 2.6% 17.0% 80.4%Percent of grouped cases correctly classified: 62.3%MaleGroup 1 341 231 77 33Non-participant 67.7% 22.6% 9.7%Group 2 579 162 286 131Non-university participant 28.0% 49.4% 22.6%Group 3 431 6 71 354University participant 1.4% 16.5% 82.1%Percent of grouped cases correctly classified: 64.4%Differences between males and females in the percentage of misclassification aresmall. However, the direction of the misciassifications suggests that nonuniversity institutions may serve to pull those male Grade 12 graduates whomight not otherwise participate in post-secondary education up to participantstatus, whereas for females who may have otherwise been university participants,they are pulled down to non-university status.225SummaryIn the third set of analyses, the same set of 20 predictor variables was usedto determine which linear combination of variables best predicted membership inthe non-participant, non-university or university participant group. Twosignificant discriminant functions were calculated, with the first maximallyseparating non-participants from university participants. The second discriminantfunction discriminates non-participants from non-university participants.This analysis suggests that the best predictors for distinguishing betweennon-participants and university participants, with non-university participantsfalling in between, are academic achievement variables and expectations aboutpost-secondary attainment. Level of education wanted and parents educationaland occupational status also contribute to discrimination among these groups, buttheir contribution is much less.The second discriminant function separates non-participants from nonuniversity participants. Primary and secondary social capital variables, andparticularly parental influence, along with total number of awards received bestdiscriminate between these groups. However, university participants and nonparticipants are more alike on two variables -- they hold less strong beliefs thatpost-secondary education is necessary to prepare for a job and they live fartherfrom nearest community college centre -- than non-university participants.226Destinations and Opportunity Sets- A SummaryIn Chapter 7, responses to a survey questionnaire sent to a sample of the1988 cohort of British Columbia Grade 12 graduates, along with matchingsecondary school transcipt and post-secondary institutional records, were used toexamine differences in opportunity sets possessed by non-participants andparticipants in post-secondary education. These opportunity sets were comprisedof both individual and institutional determinants of educational choice, asspecified by Harnqvist (1978).Employment of several discriminant function analyses in this chapterrevealed the dimensions on which the groups differed, the variables contributingto differences between and among the groups on these dimensions, and thedegree to which cases were correctly classified into their own groups. However,as Tabachnick and Fidell (1989) point out, while discrirninant function analysishas provided information on which variables predict group membership, or howgroups differ, it does not answer why group membership can be reliablypredicted, or what causes differential membership. The questions -- how is it thatindividuals come to possess different opportunity sets? or, what processes liebehind the decisions people make in choosing whether or not to pursue a postsecondary education?-- remain unanswered. Investigation of these processes iscontinued in Chapter 8. A discussion of post-high school destinations,opportunity sets, processes of choice, and perceptions of these processes isreserved for Chapter 10.Chapter 8A MODEL OF POST-HIGH SCHOOL STATUSFindings of the discriminant function analyses have illuminated thecombinations of individual and institutional determinants that constitute theopportunity sets of non-participants, non-university participants, and universityparticipants. These findings reveal the importance of academic capital, in theform of grade point average and curricular differentiation, primary andsecondary social capital, as well as other variables supporting rational choicetheory and Bourdieus Theory of Practice. Results of these analyses, as Bentler(1980) suggests, describe and predict, but do not explain or lead to causalunderstanding. This leads to the second question of this study: What processesunderlie the decisions people make in choosing whether or not to pursue a post-secondaryeducation? and more specifically, TA/hat is the relationship between the conceptsadvanced in rational choice theory and Bourdieu’s Theory ofPractice?The purpose of this chapter is to go beyond the findings of Chapter 7 bytesting the model of Post-high School Status, as hypothesized in Chapter 4. Thismodel postulates whether, when considered together, the processes leading tochoice of post-high school destination are best explained by rational choicetheory, Bourdieus Theory of Practice, or to what extent rational choice can onlybe explained within the framework of cultural and social reproduction as positedby Bourdieu.This chapter commences with a description of the hypothesized model ofPost-high School Status and related measures. Second, tests of model fit areprovided and adequacy of the measurement model is described. Third, the227228structural model is analysed. The chapter concludes with a discussion andsummary of the results.The LISREL Model of Post-high School StatusFor the following analyses, structural equation modelling, using LISRELVP oreskog & Sörbom, 1984) was used to estimate the model presented inFigure 11 (Chapter 4). The LISREL model consists of two parts. The first part, themeasurement model, specifies how the latent variables or hypothetical constructsare measured in terms of the observed variables, and it describes themeasurement properties (validities and reliabilities) of the observed variables.The second part, the structural equation model, specifies the strength ofrelationships among the latent variables and provides measures of explained andunexplained variance oreskog & Sörborn, 1989).Figure 23 presents the hypothesized model of Post-high School Statuswhere:31 A new version of the program, LISREL VII, has been released (Joreskog and Sörbom, 1989). Atthe time of writing, however, the new program was not available on the mainframe computer atthe University of British Columbia.e7NJNJSDt’2-85Figure23.PathdiagramforanhypothesizedmodelofPost-highSchoolStatus.Indic4afixiparan1&a230Notation used in the Model:? refers to the factor loadings of the indicator variables on the latent variablesrefers to an independent (exogenous) latent variablei refers to a dependent (endogenous) latent variabley refers to the regression of dependent on independent latent variables5 refers to the regression of dependent on dependent latent variables• refers to the covariances among the exogenous latent variablesô refers to measurement error in an independent manifest variablec refers to measurement error in a dependent manifest variable1 refers to residual variance in a dependent latent variableNotation Identifying Latent Constructs and Indicator Variables:CULTCAP indicates sources of cultural capitalPRIMCAP indicates sources of primary social capitalBELIEFS indicates beliefs about post-secondary educationACADCAP indicates academic capital113 SESOC indicates sources of secondary social capital94 DISPS indicates dispositions toward post-secondary education95 ENABCAP indicates enabling capitalPHSSTAT indicates post-high school status as of May 1989x1 MOTHED denotes mother’s educational attainmentFATHED denotes father’s educational attainmentFATHOCC denotes father’s occupational statusx4 MOTFIINF denotes mother’s influence on post-high school plansx5 PATHINF denotes mother’s influence on post-high school plansBELIEF2 denotes belief that p.s. education is necessary to prepare me for a joby2 BELIEF3 denotes belief that p.s. education is necessary to increase my incomey3 BELIEF6 denotes belief that p.s. ed. is necessary to give me a wider choice of jobsCURRDIFF denotes curricular differentiation (possession of prerequisites for university)y5 GPA denotes grade point average attainedFRIENINF denotes friends’ influence on post-high school plansY7 TEACHINF denotes teachers’ influence on post-high school plansCOUNSINF denotes counsellors’ influence on post-high school plansy9 INTEREST denotes level of education wantedy10 EXPECT denotes level of education expectedy11 AWARDTOT denotes total number of awards receivedSTATPS denotes p.s. status as of May 1989 (10 months after high school graduation)231In matrix form, the structural equations are:13T1 + + C1111 (0 0 0 0 O 1n1112 I II21 0 0 P24° 01 1112 I1113 I 10 0 0 0 0 01 In3 II T1. I = I P4 P42 p43 0 0 0 I I Iii 0 P52 P53 P54 0 0 n I) L0 P62 0 P64 P65 OJ 6 JIYii Y12 ‘I 1CIy21 0 ci+ IY3I “32 I + ciIy41 y42 I I4I10 I0 ciL° Y62 J IC6JThe measurement model for the y-variables is:y Ayllx=(xi 1A 0Ix2 I IA21 0 IIX3 I = l’31 0 I1X4 I 10 A42IX5 ) 10 A52J+ olb1 ‘+ Io31+ Sq(y1 ‘1 (A11 0 0 0 0 01y2 I A0 0 0 0 0Iy3 I IA30 0 0 0 0 I1y4 I 10 A42 0 0 0 01y5 I 10 A52 0 0 0 0I6 I 10 0 A63 0 0 01y7 I 10 0 A73 0 0 01y8 I = 10 0 A83 0 0 01y9 I 10 0 0 A94 0 0I10 I 10 0 0 A104 0 0Iy11 I 10 0 0 0 A115 0Y12 J 0 0 0 0 0 A126 J1E2 I€3 II4 IIE5 II6 II7 I+ II9 Ilelo Ii2In, ‘1III n3 I11141I 95 I96JThe measurement model for the y-variables is:232There are two exogenous variables in this model -- sources of cultural capitaland sources of primary social capital. The six endogenous variables include beliefsabout post-secondary education, academic capital, sources of secondary social capital,dispositions toward post-secondary education, enabling capital, and post-high sciwolstatus. Theoretical development of and justification for these constructs aredescribed in Chapters 4 and 6. Seventeen indicator variables (described inChapter 6 and portrayed in Figure 23) are used in the measurement model. Allbut two latent variables (post-high school status and enabling capital) are measuredby multiple indicators. The model includes a nonrecursive or reciprocal causalflow between two constructs, dispositions and academic capital, as hypothesized inChapter 4.Separate analyses were conducted for males (n1360) and females(n4793). Although Jöreskog and Sörbom (1989) advise that covariance matricesshould be analysed, in most instances the same goodness-of-fit values andstandardized maximum likelihood estimates are obtained whether correlation orcovariance matrices are used as input. (Analyses using correlation and covariancematrices as input revealed this to be the case for these data with these models).For ease of interpretation, results are reported with correlation matrices. Means,standard deviations, and correlations, for both the male and female sample, arereported in Table 43. Appendix D contains means and standard deviations byparticipant status for males and females.The approach adopted in this present work was to start by estimating amodel (see Figure 23) that includes all paths hypothesized in Chapter 4. Sewell,Tsai, and Hauser (1983) describe this type of model as “full” in the sense that all ofthe coefficients that might possibly enter a theoretically preferred model areTable43. Means,StandardDeviations,ProductMoment Correlations,andFactorLoadingsof theIndicator Variables-MalesandFemales.Factor loadingsoftheindicatorvariabless.d.(standardized)112212malefemalemalefemalemalefemaleProductmomentcorrelationsamongtheindicatorvariables*1234567891011121314151617TotalCoefficientof Determinationforthey- variablesTotalCoefficientof Determination forthex-variables1.000.999.964.973IndicatorVariablesMeans1ylBEUEF23.533.610.770.67.600.497.493.336.047-.006.043.066.047.079.093.055.012.037.026.036.088.0702y2BELIEF33.463.480.780.78.645.598.521.404.057.030.063.076.064.050.133.045.025.044.049.058.086.0663y3BELIEF63.423.520.820.74.587.675.351.379.076.062.072.077.086.090.117.112.082.064.069.050.104.0724y4CU1UIDIFF0.590.610.490.49.696.674.086.110.106.487.115.125.031.197.313.183.429.177.169.118.122.1525ySCPA2.262.330.870.85.794.717.084.095.055.550.043.158.018.136.321.133.476.168.157.083.066.0616y6FRIENINE2.943.081.231.21.631.626.062.080.094.093.035.399.353.052.121.181.180-.008-.017-.019.351.2867y7TEACHINF2.572.712.571.35.678.635.112.091.090.073.107.435.616.091.174.249.245-.003.020-.022.291.2578y8COUNSINF2.222.372.221.33.590.568.114.071.094.017.016.372.627.037.063.236.135-.063-.042-.082.271.2449y9INTEREST5.065.111.301.21.439.358.092.087.115.223.190.106.122.077.232.131.212.100.118.091.069.08410ybEXPECT3.743.671.481.49.750.633.136.161.113.339.365.122.153.079.321.146.363.175.201.135.157.13011yllAWARDTOT1.491.681.181.16.950.949.116.077.097.186.166.236.287.249.121.176.269.009.042.009.153.16112yl2STATES1.992.010.750.70.950.949.079.125.085.471.556.117.185.086.244.392.267.182.214.139.231.25913xlMOTHED12.5412.442.462.50.592.774-.039.034.044.144.175-.028-.036-.048.057.147-.017.147.534.311.142.10814x2FATHED12.9312.642.992.96.809.801.009.064.088.214.209.026-.033-.025.100.232.019.202.576.474.097.17915x3FATHOCC50.1450.2715.5715.40.631.590.003.019.047.180.165.027-.013-.042.082.168.002.165.329.512.072.12216x4MOTHINF3.573.781.211.17.895.852.095.089.100.103.033.315.296.276.077.134.183.204.046.047.025.66717x5FATHINF3.543.591.281.30.818.783.112.090.141.090.047.288.262.261.089.143.152.202.006.116.074.733*Correlationsformalesampleinlowertriangle, forfemalesampleinuppertriangle234considered. Woelfe (1985) asserts that it is better to include these paths in theanalysis than to make the strong assumption that the parameter is zero.Subsequent models are tested to determine the effects of alterations to the initialmodel, as guided by the modification indices, t - values, and normalizedresiduals, and within the limits imposed by theory.Tests of Model FitAccording to Jöreskog and Sörbom (1982), the goodness-of-fit of the wholemodel may be assessed by means of three measures of overall fit: 1) the overall x2measure, associated degrees of freedom, and probability level, 2) the goodness-of-fit indices (GFI and AGFI), and 3) and the root mean square residual (RMR).Goodness-of-fit evaluations are used to assess whether the hypothesized modelprovides a plausible representation of the data. Small x2 values in relation to thedegrees of freedom correspond with a good fit, and large x2 values indicate a badfit (Bentler, 1980; Joreskog and Sörbom, 1982). Beside the GFI, AGFI, and RMR,others (Bollen, 1989; Hayduk, 1987) suggest that x2 be considered relative to thedegrees of freedom by calculating X2/d.f. . Goodness-of fit measures of the initialand subsequent models are reported in Table 44 for males and Table 45 forfemales.The x2 and other goodness-of-fit measures are sensitive to sample size.Bentler (1980) states that in very large samples (which is the case for the analysespresented in this chapter) the presence of the most trivial discrepancy betweenmodel and data will result in rejection of a model by the x2 test. He asserts thatthe goodness-of-fit of a model to the data should be evaluated by other methodsbeside the x2 test, such as examination of the normalized residuals.235Male SampleThe initial model to be tested, Model I, is shown in Figure 23. In each latentvariable, one of the ?.. has been set to unity in order to define the unit ofmeasurement for each latent variable in relation to one of the observed variables(Jöreskog and Sörborn, 1989). In this initial model, error terms are assumed to beuncorrelated (constrained to be zero). The goodness-of-fit statistics are shown inthe first line of Table 44. The x2 value(2100) =220.91, p <.001), along with othergoodness-of-fit measures, indicate that the model provides a reasonable baselineagainst which to assess further models formulated in accordance with thehypotheses outlined in Chapter 4. All ? parameters were significant andnormalized residuals indicated a good fit.In Model I, it is assumed that measurement errors are uncorrelated. Giventhe nature of some of questions on the survey questionnaire (for example,questions about parents) it is reasonable to expect that response bias exists. Themodification indices suggest that allowing some correlations among errors wouldresult in an improvement of the fit of the model. Four O terms between a)mother’s education and mother’s influence, b) father’s education and father’sinfluence, c) mother’s education and father’s education, d) father’s occupation andfather’s influence, and three °E terms between a) the belief that post-secondaryeducation is necessary to prepare for a job and increase one’s income, b) the beliefthat post-secondary education is necessary to prepare for a job and was necessaryfor a wider choice of jobs, and c) teachers’ influence and counsellors’ influence,were freed in Model II. It was also assumed in Model I that two latent variables --enabling capital and post-high school status -- are measured with perfect reliability,since only one indicator was available for each construct. However, Joreskog andSörbom (1982) indicate that it is better to assign an arbitrary value of reliabilityTable44.StagesintheModificationoftheLISRELModelofPost-highSchoolStatus-Males(n=1360).x21Modelx2d.f.pd.f.GFIAGFRMSRAX2Ad.f.ModelI:Allpathsincluded,asdepictedinFigure1.Maximumlikeithoodestimates.220.91100<.0012.21.981.944.027ModelII:Errorcovariancetermsincludedbetweena)motherseducationandmother’sinfluence,b)father’seducationandfather’sinfluence,c)mother’seducationandfather’seducation,d)father’soccupationandfather’sinfluence,e)beliefthatpost-secondaryeducationisnecessarytoprepareforajobandtoincreaseone’sincome,f)belief thatpost-secondaryeducationisnecessarytoprepareforajobandtonecessaryforawiderchoiceinjobs,andg)teachers’influenceandcounsellors’influence.Reliabilityvaluesof(r)1and12setat0.90.‘135.7693.0031.46.988.970.02185.15-7ModelIII:Pathfrombeliefstoacademiccapitalremoved.136.0494.0031.45.988.969.0210.28+1ModelIV:Pathfromdispositionstoenablingcapitalremoved.136.5295.0031.43.988.969.0210.48+1ModelV: Pathfromprimarysocialcapitaltodispositionsremoved.136.9996.0041.43.988.968.0210.47+1ModelVI:Pathfromacademiccapitaltodispositionsremoved.137.9797.0041.42.988.967.0220.98+1ModelVII:Pathfromculturalcapitaltosecondarysocialcapitalremoved.141.0098.0031.44.988.966.0243.03+1ModelVIII:Pathfromprimarysocialcapitaltobeliefsremoved.144.6799.0021.46.987.964.0253.67+1ModelIX: SameasModelVIwithsamplesizesetat200.21.1899>99.987.964.025ModelX:SameasModelVI,estimatedwithpolyserialandpolychoriccorrelationsandmethodof unweightedleastsquares..992.977.030237than to assume an equally arbitrary, and less plausible, value of 1.00. Followingtheir advice, a value of .90 was assigned to y11 andy123.Model II provides a much better fit. That is, in Model II there is asignificant improvement in fit over Model I, with a 2(7) change of 85.15, p<.OOl.While the 2 value is significant (x2 (93) 135.76, p =.003), the ratio of x2 todegrees of freedom is a relatively low 1.46. Values2/d.f. of less than 2.00 areoften interpreted as being indicative of a reasonably good fit (Hayduk, 1987). Thegoodness-of-fit indices as reported in Table 44 suggest a good correspondencebetween the correlation matrix estimated by the model and the originalcorrelation matrix.Although Model II appears to provide an acceptable fit of the data,examination of the t-values reveals that some of the hypothesized paths are nonsignificant (t-value less than 2.0). These paths are removed, one at a time, and theresults of these alterations are summarized in Table 44 in Models III to VIII. Inmost cases the increase in x2 is close to the increase in the degrees of freedom,indicating that the change in fit due to inclusion of the extra parameters wasobtained by capitalizing on chance, and that they do not provide a significantcontribution to the model. In Models VII and VIII, the increase in x2 is slightlyhigher than the increase in degrees of freedom, but it is nonsignificant (p> .05).Following the deletion of 6 non-significant paths, Model VIII is accepted asproviding the best fit of the data to the model. The Total Coefficient ofDetermination for the overall model is .414.Two further investigations of Model IX were carried out. As suggested byHayduk (1987), rather than using the2/d.f. procedure to assess whether nonsignificant x2 values are due to a large sample size or an ill fitting model, that a32The specification of the reliability 0.90 is accomplished by assigning the fixed value of 0.10 tothe elements0(e)11 and 0(e)1212.238“critical - N” formula proposed by Hoelter (1983) be utilized. This is accomplishedby inserting a sample size of 200 in the LISREL program, thus eliminating theextra sensitivity resulting from the extra cases. When Model IX is estimated withthe sample size set at 200, a non-significant x2 (x2 (99) =21.18, p > .99) is obtained,which suggests a good overall fit.Jöreskog & Sörborn (1982) indicate that when some or all of the observedmeasures are ordinal, polychoric and polyserial correlations (rather than productmoment correlations) should be computed and then analysed using the methodof unweighted least squares (ULS). Since most of the observed variables in thismodel are ordinal, Model X is estimated with ULS and polyserial and polychoriccorrelations as input.Estimation with ULS in LISREL VI does not provide a x2 value ofgoodness-of-fit, t-values, or standard errors. The goodness-of-fit indices that ULSdoes provide -- GFI (.993), AGFI (.979), and RMR (.028) -- all suggest that themodel fits the data well. However, since maximum likelihood estimates areconsidered to be reasonably robust to deviations of multivariate normality, andML estimates are not unlike those produced by unweighted least squares, MLestimates are reported.Female SampleThe same procedure of model estimation, as described for the malesample, was followed for the female sample. In the initial model, Model I, errorterms are assumed to be uncorrelated. The goodness-of-fit statistics are shown inthe first line of Table 45. The x2 value(2100) =347.52, p <.001) is somewhathigher than the baseline model for the male sample, but the 2/d.f. ratio andTable45.StagesintheModificationoftheLISRELModelofPost-highSchoolStatus-Females(n1790).2Modeld.f.PGElAGFRMSRAd.f.ModelI:Allpathssupportingrationalchoiceandreproductiontheoryincluded,asdepictedinFigure1.Maximumlikelihoodestimates.347.52100<.0013.48.978.935.031ModelII:Errorcovariancetermsincludedbetweena)mother’seducationandmother’sinfluence,b)father’seducationandfather’sinfluence,c)mother’seducationandfather’seducation,d)father’soccupationandfather’sinfluence,e)beliefthatpost-secondaryeducationisnecessarytoprepareforajobandtoincreaseone’sincome,f)beliefthatpost-secondaryeducationisnecessarytoprepareforajobandtonecessaryforawiderchoiceinjobs,andg)teachers’influenceandcounsellors’influence.Reliabilityvaluesofo()and213.6593<.0012.29.986.965.023133.87-76’‘12,12setat090.ModelIII:Pathfromacademiccapitaltodispositionsremoved.213.6794<.0012.27.986.964.0230.02+1ModelIV:Pathfromprimarysocialcapitaltodispositionsremoved.213.7095<.0012.25.986.964.0230.03+1ModelV:Pathfromculturalcapitaltoacademiccapitalremoved.214.6896<.0012.24.986.963.0230.98+1ModelVI:Pathfromprimarysocialcapitaltobeliefsremoved.215.8297<.0012.22.986.962.0231.14+1ModelVII:Pathfromdispositionstoenablingcapitalremoved.217.9998<.0012.22.986.961.0232.17+1ModelVIII:SameasModelVwithsamplesizesetat200.24.2198>.99.986.961.023ModelVIII:SameasModelV,estimatedwithpolyserialandpolychoriccorrelationsandmethodofunweightedleast squares..991.974.031240other goodness-of-fit indices indicate that this model also provides a reasonablebaseline against which to assess further models (Table 45).In Model II, four O terms between a) mother’s education and mother’sinfluence, b) father’s education and father’s influence, c) mother’s education andfather’s education, d) father’s occupation and father’s influence, and three °Eterms between a) the belief that post-secondary education is necessary to preparefor a job and to increase one’s income, b) the belief that post-secondary educationis necessary to prepare for a job and was necessary for a wider choice of jobs, andc) teachers’ influence and counsellors’ influence, consistent with freed error termsin the male sample, were freed. As with the male Model II, a reliability value of.90 was assigned to y11 and y12.Model II provides a considerable improvement in fit over Model I (x2 (94)= 213.65, p < .001), with a2(7) change of 133.87, p<.OO1.The ratio of %2 to degreesof freedom is 2.28. Goodness-of-fit indices suggest that the correspondencebetween the correlation matrix estimated by the model and the originalcorrelation matrix is acceptable.In Models III to VII, the non-significant paths are removed and the resultsof these alterations, summarized in Table 45, indicate that initial inclusion ofthese parameters did not provide a significant contribution to the model. Thus,Model VII appears to provide the best fit of the model to the data. The TotalCoefficient of Determination for the overall model is .491.In Model VIII, the sample size is set to 200, thereby eliminating the extrasensitivity resulting from the extra cases. When Model VIII is estimated, a X2(98)= 24.21, p> .99) is obtained.Model IX is estimated with polyserial and polychoric correlations and themethod of unweighted least squares. Goodness-of-fit indices provided -- GFI,241AGFI, and root mean square residuals all suggest an acceptable fit. As with themale model, estimates obtained by unweighted least squares are very similar tothose produced by maximum likelihood estimates; thus, ML estimates arereported.Adequacy of the Measurement ModelLISREL VI provides squared multiple correlations for each observedvariable and coefficients of determination for all of the observed variables.According to Joreskog and Sörbom (1982), these measures assess 11how well theobserved measures serve, separately or jointly, as measurement instruments forthe latent variables11 (p.’4O7). The results of the measurement model are reportedin Table 43.For the x- variables the total coefficient of determination is .964 (males)and .973 (females), and for the y-variables it is 1.000 for males and .999 forfemales. These values indicate that, jointly, the variables serve well asmeasurement instruments for the latent variables. Separately, the squaredmultiple correlations for several of the variables range from modest to good. Onlyis a poor measure, indicating that the level of education wanted (INTEREST) isnot a good measure of dispositions toward post-secondary education.The squared multiple correlation for the dependent variable post-highsciwol status (PHSSTAT) is .582 for males and .541 for females, indicating that 58%of the variance in post-high school status for males and 54% for females is explainedby the model.242Analysis of the Structural ModelFour paths were non-significant for both males and females. They includethe path from 1) sources of primary social capital (PRIMSOC) to beliefs about post-secondary education (BELIEFS), 2) sources of primary social capital (PRIMSOC) todispositions toward post-secondary education (DISPS), 3) dispositions toward post-secondary education (DISPS) to enabling capital (ENABCAP) and 4) academic capital(ACADCAP) to dispositions toward post-secondary education (DISPS). Of the 16remaining paths, 15 were significant in the female analysis and 14 weresignificant in the male model.Figure 24 displays the significant parameters and their standardized pathcoefficients for males and females. Standardized parameter estimates aresummarized in Table 46. A complete account of maximum likelihood estimates ofboth standardized and unstandardized parameters, t-values, and standard errorsfor the male and female models of post-high school status is reported in Table IV,Appendix E.The direct effects of the antecedent variables on each endogenous variableand the indirect effects of the antecedent variables on post-high school status are ofinterest in this study. In the next sections, the direct effects of the antecedentvariables on each endogenous variable are considered, followed by a discussionof the direct, indirect, and total effects of the antecedent variables on post-highschool status.Beliefs about Post-secondary EducationThe first equation in the structural model examined the effects of the twoexogenous variables, sources of cultural capital (CULTCAP) and sources of primary£11€12Figure24.ParameterestimatesinamodelofPost-highSchoolStatus.•ledloateaafixedparameter.(Parametereztimateoforfemalesmpareetheam)Table46.PathCoefficientsinaModelofPost-highSchoolStatus-MalesandFemales(MaximumLikelihood,standardizedsolution).1919293949596R2MFMFMFMFMFMFMFMFMFExogenousvariablesiSourcesofCulturalCapitalSourcesofPrimarySocialCaptitalEndogenousVariables9.BeliefsaboutPost-secondaryEducation.087.123**.254.211.073.05792AcademicCapital.145**-.120.574.751.411.52693SourcesofSecondarySocialCapital*-.132.525598.276.35094Dispositions.333.388**.215.183**.237.308.257.30995EnablingCapital.184.169.399.332**.218.16496Post-secondaryStatus.143.158.628.522.110.164.085.101.582.541TotalCoefficientofDetermination.414.491Notes:(a)Pathsmarkedwithanasteriskarenotsignificant.SeeTable1(AppendixB)forunstandardizedestimates,t-valuesandstandarderrors.245social capital (PRIMSOC), and one endogenous variable, sources of secondary socialcapital (SECSOC) on beliefs about post-secondary education (BELIEFS). It can be seenfrom Figure 24 that the residual variance in BELIEFS is 93% for males and 94% forfemales. Two variables, CULTCAP and SECSOC, explain oniy 7% of the variancefor males and 6% of the variance for females in BELIEFS. The exogenous variablesources of primary social capital (PRIMSOC), was not significant for males orfemales. The standardized path coefficients reveal that the effects of CULTCAPare weak for both males (.087) and females (.123). The effects of SECSOC aresomewhat stronger for males (.254) and females (.211).Academic CapitalThe second equation in the structural model hypothesized that oneexogenous variable, sources of cultural capital (CULTCAP), and two endogenousvariables, beliefs about post-secondary education (BELIEFS) and dispositions QJISPS)would have direct positive effects on academic capital (ACADCAP). For females,53% of the variance in academic capital is accounted for by the predictorvariables; for males, this figure is 41%. For males, only CULTCAP and DISPScontributed to the variance in ACADCAP. For females, only BELIEFS and DISPScontributed to the variance in ACADCAP, and the effect of BELIEFS wasnegative. However, the effect of CULTCAP for males (.145) and BELIEFS forfemales (-.120) were small when compared to the effect of DISPS on ACADCAP(.574 for males and .751 for females).246Sources of Secondary Social CapitalThe third equation in the structural model examined the effects of the twoexogenous variables, sources of cultural capital (CULTCAP) and sources of primarysocial capital (PRIMSOC) on sources of secondary capital (SECSOC). Figure 24reports that the residual variance in SECSOC is 72% for males and 65% forfemales. In other words, CULTCAP and PRIMSOC explain 28% and 35% of thevariance in SECSOC, for males and females, respectively. The standardized pathcoefficients reveal that both predictor variables account for the variance inSECSOC for females and only PRIMCAP is significant for males. The effect ofCULTCAP on SECSOC is negative and weak for females (-.132). The effect ofPRIMSOC on SECSOC is strong for both males and females (.525 and .598,respectively).DispositionsFive variables -- sources of cultural capital (CULTCAP), sources of primarysocial capital (PRIMSOC), sources of secondary social capital (SECSOC), beliefs aboutpost-secondary education (BELIEFS), and academic capital (ACADCAP) werehypothesized to have positive effects on dispositions about post-secondary educotion(DISPS). The effects of both PRIMSOC and ACADCAP were non-significant forboth males and females. Thus, the hypothesized reciprocal path betweenACADCAP and DISPS cannot be demonstrated with these data. For males, 26%of the variance in DISPS is accounted for by the three predictor variables; forfemales, this figure is 31%.Significant effects of CULTCAP, BELIEFS, and SECSOC on DISPS werefound for both males and females. Of these, CULTCAP had the strongest effect.247The standardized coefficients for CULTCAP, BELIEFS, and SECSOC on DISPSwere .333, .215, and .237, respectively for males, and .388, .183, and .308 forfemales.Enabling CapitalThe fifth equation examined the effects of the three endogenous variables,academic capital (ACADCAP), sources of secondary social capital (SECSOC), anddispositions DISPS, on enabling capital (ENABCAP). The influence of DISPS onENABCAP is not statistically significant for males or females. Thus, ACADCAPand SECSOC account for 22% (males) and 16% (females) of the variance in thisdependent variable. The effect of SECSOC (.399 for males and .332 for females) isstronger than that of ACADCAP (.184 for males and .169 for females), and theeffect of both of these variables is stronger for males than for females.Post-high School StatusIn the sixth and final equation in the structural model it was hypothesizedthat one exogenous variable, sources ofprimary social capital (PRIMSOC), and threeendogenous variables including academic capital (ACADCAP), dispositions towardpost-secondary education (DISPS), and enabling capital (ENABCAP) would have apositive effect on post-high school status (PHSSTAT). Figure 24 reveals that, formales, this model of educational choice explains 58% of the variance inPHSSTAT; for females, 54% of the variance in PHSSTAT is explained.For both males and females, all hypothesized paths are significant. Formales, the effects of PRIMSOC, ACADCAP, DISPS, and ENABCAP are .143, .628,.110, and .085, respectively. For females, these values are: PRIMSOC (.158),248ACADCAP (.522), DISPS (.164), and ENABCAP (.101). For males, the effect ofACADCAP is considerably stronger than for females.Direct, Indirect, and Total EffectsThe direct, indirect, and total effects for the structural model are reportedin Table 47. The results indicate that two latent constructs had a signfficantimpact on the post-high school status of recent British Columbia Grade 12graduates. The total effect of academic capital (ACADCAP) on post-high schoolstatus (PHSTAT) was .644 for males and .539 for females, and the total effect ofdispositions toward post-secondary education (DISPS) was .479 for males and .569 forfemales. The effect of academic capital was mainly a direct effect. However, theeffect of dispositions toward post-secondary education was ameliorated when it wasmediated through academic capital. Whereas the direct effect of dispositions towardpost-secondary education was only .110 for males and .164 for females, the totaleffect (direct and indirect effects) was .479 for males and .569 for females. Theindirect effect of dispositions toward post-high school status is more than three timeslarger than the direct effect for males (.369) and two and a half times larger forfemales (.405).249Table 47.Direct, Indirect, and Total Effects of Antecedent Variables on Post-high School Status.(Standardized Coefficients).Direct Indirect TotalEffects Effects EffectsM F M F M FPost-high school statusCultural Capital * * .262 .203 .262 .203Primary Social Capital .143 .158 .091 .129 .234 .287Beliefs * * .104 .044 .104 .044Academic Capital .628 .522 .016 .017 .644 .539Secondary Social Capital * * .173 .217 .173 .217Dispositions .110 .164 .369 .405 .479 .569Enabling Capital .085 .101 ** ** .085 .101No direct path hypothesized.** No indirect path hypothesized.The impact of the two exogenous latent constructs -- sources of culturalcapital and sources of primary social capital -- on post-high school status, whilesomewhat less in magnitude, is important. The effect of sources of cultural capital,exclusively due to indirect effects, was .262 for males and .203 for females. Thetotal effect of sources of primary social capital on post-high school status was .243for males and .287 for females.To illustrate how the effects of sources of cultural capital and sources ofprimary social capital impact upon post-high school status, the direct effects of thesignificant structural paths in the model are traced in the next section.Female SampleAs hypothesized, the direct effect of sources of cultural capital on dispositionstoward post-secondary education was moderately strong for females (.388). That is,parents as sources of cultural capital as measured by mother’s and father’s250education and father’s occupation directly influenced the dispositions thatindividuals held toward post-secondary education, as measured by the level ofeducation wanted and the level of education expected. However, the direct effectof parents as sources of cultural capital on academic capital was not significant, andits effect of sources of secondary social capital was significant and negative (-.132).Hence, for females, while mothers’ and fathers’ education and fathers’occupational status did not directly affect the amount academic capital possessed,lower levels of parental cultural capital were related to the increased influence ofcounsellors, teachers, and friends. The effect of parents as sources of cultural capitalon beliefs about post-secondary education was significant but very small (.123) forfemales.The direct effect of sources of primary social capital on sources of secondarysocial capital was strong and positive for females (.598); thus, higher levels ofparental influence was related to higher levels of influence by counsellors,teachers, and friends. The direct effect of parents as sources ofprimary social capitalon beliefs about post-secondary education and on dispositions toward post-secondaryeducation was was not significant. Its effect on post-high school status was positive,but weak (.158).The effect of beliefs about post-secondary education on dispositions toward post-secondary education was positive, significant, and relatively small (.183) forfemales. However, the direct effect of beliefs on academic capital was significant andnegative (-.120). That is, girls who held stronger beliefs that post-secondaryeducation was necessary to prepare for a job, increase one’s income, and to have awider choice of jobs were more likely not to possess strong academic capital.The strong, positive direct effect of academic capital on post-high school statusfor females (.522) suggests that higher grade point averages and possession of the251prerequisites for university admission led to increased likelihood of universityparticipation. The direct effect of academic capital on enabling capital was alsoweakly positive and significant females (.169). Thus, while those with higherlevels of academic capital were more likely to receive a greater number ofacademic rewards, the effect was not strong.Counsellors, teachers, and friends as sources of secondary social capital had adirect positive effect on the dispositions toward post-secondary education held byfemales (.308) and beliefs about post-secondary education (.211). That is, the morecounsellors, teachers, and friends were reported to have influenced their plansfollowing high school, the higher were their reported levels of education wantedand education expected. Also, higher levels of secondary social capital led tostronger beliefs about the importance of post-secondary education as beingnecessary to prepare for a job, to increase one’s income, and to have a widerchoice of jobs. Sources of secondary social capital also had signfficant positive effectson the enabling capital of females (.332) as measured by the total number ofawards received. Students who reported stronger levels of influence bycounsellors, teachers, and friends also reported that they received more academicawards in the form of scholarships.The direct effect of dispositions toward post-secondary education on academiccapital is positive and very strong for females (.751). For females, this path is thestrongest in the model, superseding the direct effect of academic capital on posthigh school status. Higher levels of education wanted and expected affected thecurricular stream completed and grade point average earned. However, whereasthe direct effect of dispositions toward post-secondary education on academic capitalwas very strong, its direct effect on post-high school status is only weakly positivefor females (.164).252The direct effect of enabling capital on post-high school status was weaklypositive for females (.101). It appears that on its own, the number of academicawards received appears to have a minimal impact on post-high school status.Male SampleFor males, the direct effects of sources of cultural capital on dispositionstoward post-secondary education was moderately strong (.333). Also, a weak,positive, direct effect of parents as sources of cultural capital on academic capital wasdemonstrated (.145). Thus, for males, parents as sources of cultural capital asmeasured by mother’s and father’s education and father’s occupation directlyinfluenced the academic capital of their sons, as measured by curriculardifferentiation and grade point average. The effect of parents as sources of culturalcapital on sources of secondary social capital and on beliefs about post-secondaryeducation was non-significant.The direct effect of sources of primary social capital on sources of secondarysocial capital was strong and positive (.525), and its effect on post-high school statuswas positive and weak (.143). The effect of parents as sources of primary socialcapital on beliefs about post-secondary education and on dispositions toward postsecondary education was not significant in the male sample.The direct effect of beliefs about post-secondary education on dispositionstoward post-secondary education was positive, significant, and relatively weak (.215)for males. However, the direct effect of beliefs about post-secondary education onacademic capital was non-significant.The path between academic capital on post-high school status was very strongand positive (.628). For males, this path is the strongest in the whole model. Thatis, possession of the prerequisites for university admission together with higher253grade point averages lead to increased post-secondary participation, andincreased selectivity of post-secondary institution. The direct effect of academiccapital on enabling capital is also weakly positive and significant (.184).Sources of secondary social capital had a direct positive effect on beliefs aboutpost-secondary education (.254), dispositions toward post-secondary education (.237)and on enabling capital (.399). The direct effect of dispositions toward post-secondaryeducation on academic capital is strong and positive for males (.574). However, theeffect of this latent construct on post-high school status is only weakly positive(.110). As well, the direct effect of enabling capital on post-high school status wasweakly positive (.085).DiscussionThe model of Post-high School Status as hypothesized in Chapter 4 andestimated in this chapter provides promise in beginning to unravel how post-high school trajectories of non-participants, non-university participants, anduniversity participants are created and reproduced. This model explains 58% ofthe variance in post-high school status in the male model and 54% of the variance inthe female model. All of the latent constructs in the model contribute to itsexplanatory power.Central among the findings is the direct effect of academic capital on posthigh school status. While academic capital plays a critical role in ones decisionwhether and where to continue to college or university, it is a more importantform of capital for men than for women. In turn, it may be asked “Whatinfluences the amount of academic capital in one’s possession?” Here, the role of254parents as sources of cultural capital and as sources of secondary social capital arerevealed. In the previous chapter, it was concluded that variables measuringparental educational and occupational backgrounds were poor predictors ofwhether and where one participated in post-secondary education following highschool. However, through the use of LISREL VI, the moderating role of these twoexogenous latent constructs is demonstrated.First, the socio-econornic backgrounds of parents do affect the post-highschool status of their children. For females, academic capital is strongly affectedby the dispositions they hold toward post-secondary education which, in turn,are affected by their parents’ educational and occupational backgrounds. To alesser extent, dispositions are influenced by the beliefs that one holds about post-secondary education which, in turn, are affected by parental backgrounds. Formales, the path from parents as sources of cultural capital to academic capital is bothdirect and indirect via dispositions toward post-secondary education. The pathbetween parents as sources of cultural capital and dispositions toward post-secondaryeducation is also important for males. However, for males parental backgroundalso exerts a direct effect on the amount of academic capital possessed.Social capital, both as primarily supplied by parents and secondarilyacquired through counsellors, teachers, and friends also contributes todetermining one’s post-high school status. Youth who are encouraged by theirparents are more likely to seek advice and assistance from school personnel andfriends. Those who report that counsellors, teachers, and friends positivelyinfluence their post-high school plans are more strongly disposed toward postsecondary participation, hold stronger beliefs about the benefits of highereducation, and receive more academic awards. Counsellors, teachers, and255friends have a greater influence on females from lower socio-economicbackgrounds; this, however, does not appear to be the case for males. Given thegate keeping role of counsellors regarding scholarship application forms andinformation about the post-secondary system, as described in Chapter 6, theinfluence of school personnel on lower socio-economic females may be of criticalimportance.It could not be demonstrated that parents as primary sources of socialcapital directly influenced their childrens beliefs about or dispositions towardpost-secondary education. Rather, the results of both the female and maleanalyses suggest that a multiplex relationship among parents, school personnel,and friends affect beliefs about and dispositions toward post-secondaryeducation.Very little of the variance in the construct beliefs about post-secondaryeducation is explained by two antecedent variables in the model. Also, while thepaths leading directly from this construct to dispositions toward post-secondaryeducation and academic capital are significant for females, they are weak. Only theeffect of beliefs on dispositions is significant for males. It is not clear why thepath leading from beliefs about post-secondary education to academic capital forfemales is negative. Perhaps those with higher levels of job oriented beliefs aremore inclined to complete non-academic (e.g. career preparation) programs inhigh school.To what extent do individuals make rational choices regarding post-highschool destinations? Do the concepts of cultural capital, social capital,dispositions toward post-secondary education, as posited by Bourdieu, contributeto an explanation of choice regarding post-high school destinations? What is the256relationship between the concepts advanced in rational choice theory andBourdieus Theory of Practice?First, given the strong relationship between academic capital and post-highschool status, it could be argued that individuals make rational decisions aboutpost-secondary attendance or non-attendance based on their academic success orfailure in high school. It could also be argued that if dispositions toward post-secondary education are interpreted as desires, then the relationship amongdispositions toward post-secondary education, academic capital, and post-high schoolstatus supports a rational choice thesis. Beliefs about post-secondary education,specified by Elster as integral to the optimizing operations of practical rationality,explain only a modicum of the variance in academic capital and dispositions towardpost-secondary education.However, when this rational choice model is enveloped in a framework ofparental transmission of cultural and social capital, quite a different theoreticalinterpretation may be used to explain relationships among the various constructs.This model demonstrates that, in a sample of British Columbia Grade 12graduates from the 1988 cohort, parents from higher status backgrounds havebeen able to inculcate in their children stronger dispositions toward post-secondary attendance. In turn, these dispositions affect the type of curricularprogram completed and grade point average earned, and how accumulatedacademic capital is invested.Post-high school destinations are also affected by parental transmission ofsocial capital. Relationships in the home that encourage post-secondaryparticipation also result in secondary social relationships with school personneland friends. Social capital transmitted in primary and secondary socialrelationships enlightens individuals to the “field of the possibles”, resulting in257positive dispositions toward post-secondary participation and higher numbers ofawards received. In other words, the intersecting fields of family relationships,family socio-economic status, and relationships within the school environmentimpact on achievement. In turn, the amount of academic capital in one’s possessionaffects whether and where one participates in post-secondary education.Whereas discriminant function analyses used a set of predictor variables topredict group membership, the LISREL analyses in this chapter haveendeavoured to demonstrate the processes by which one becomes a member ofthe non-participant, non-university or university participant group. On the basisof the findings of this chapter, it seems more reasonable to conclude that“rational” choices regarding post-high school destination continue to beinfluenced by parental transmission of cultural and social capital. In Chapter 9,through interviews with Grade 12 students, this theme is further explored.Chapter 9GRADE 12 STUDENTS AND THEIR PERCEPTIONS OF THE TRANSITIONPROCESSIn each of the previous two chapters, different methodological approacheswere used to address the first two research questions in this study. Chapter 7sought to establish how well post-high school group membership could bepredicted from the individual and institutional determinants of educationalchoice, as specified by Härnqvist, and which set of predictor variables bestpredicted group membership. In Chapter 8, a model of Post-high School Status,which integrated concepts from rational choice theory and Bourdieu’s Theory ofPractice, was estimated using structural equation modelling (LISREL Vi). LISRELVI permitted the estimation of relationships among the underlying constructs inthe hypothesized model of Post-high School Status.Discriminant function analyses (Chapter 7) revealed that participantsdiffered from non-participants on academic capital variables, and primary andsecondary social capital variables. Also, participants wanted and expected higherlevels of education than did non-participants. University participants could bedistinguished from non-university participants primarily by the amount ofacademic capital in their possession, levels of education expected, and theirproximity to the nearest university. Whereas social capital variables were strongpredictors of whether one participated in post-secondary education, thesevariables were not useful in predicting where one participated.258259LISREL analyses (Chapter 8) reinforced the importance of academic capital,primary and secondary social capital on post-high school status. The latent constructdispositions toward post-secondary education was demonstrated to have strongindirect effects on whether and where one participated in post-secondaryeducation. In turn, the effect of parents as sources of cultural capital emerged asaffecting dispositions one held toward post-secondary education.Through statistical analyses, a detailed portrayal of the individual andinstitutional determinants of post-high school status was depicted. Relationshipsamong unobserved latent constructs based on rational choice theory andBourdieu’s Theory of Practice further revealed how parents as sources of culturaland primary social capital, teachers, counsellors, and friends as secondary sourcesof social capital, one’s beliefs about and dispositions toward post-secondaryeducation, academic, and enabling capital affect post-high school destinations.One dimension of the transition from high school to post-high schooldestination remains unaddressed. In the analyses conducted thus far, methods ofmultivariate analyses have been used to analyse responses by recent BritishColumbia Grade 12 graduates to a survey questionnaire in order to testtheoretically guided causal relationships. However, it has not been establishedhow those students actually experiencing the transition from high school perceivetheir situations. Hence, the third question of this study is: How do students perceivethe processes underlying their decisions regarding post-high school destinations?Denzin (1989) asserts that since “no single method can ever completelycapture all of the relevant features of an [empirical] reality” (p.l3), theemployment of multiple methods, or triangulation, to the study of particularphenomena is in order. Since the third question seeks to uncover different featuresof the decision making process from the previous analyses, a different sample andmethodological strategy was employed. Interviews were conducted with Grade26012 students, at two points in time during their graduating year, to explore howthey perceived and acted on the choices before them. This chapter endeavours touse first-order concepts used by the language of students everyday lives toprovide a rich, detailed description of the second-order concepts identified in themodel of Post-high School Status, as depicted in Figure 23 (Denzin, 1989). In thisway, the researcher learns the ‘everyday conceptions of. .. reality and interpretsthat reality from the stance of.. . theory” (p.9).A description of the schools selected for the study, students, interviewprocedure, representativeness of the interview sample, and preparation of theinterview data was described in Chapter 5. This chapter begins by describing theplanned and actual post-high school destinations of the 51 interviewees.DestinationsThe first interviews with Grade 12 students took place in late October 1989,approximately six months before high school graduation. Despite the imminentend of high school, for most students the transition process -- as an overt,conscious exercise -- had not formally commenced. The process of separation fromthe life that they had so long been a part was described as a future endeavour andnot a current concern.Carol: May... that’s when you’ll start thinking about it more. . . . Right now I do thinkabout it but it’s not in the planning stages quite yet.Conrad: It just feels like an extended Grade 11. I guess I really won’t feel it until nextyear, about Mayish, about March break.261Their sentiments were not without a sense of impending departure from theknown, but it was not quite real, and they were not quite ready for the next stageof their lives.Adrian: It’s hard to comprehend, well this is Grade 12 You know, ‘cause you’ve neverbeen in this situation before. You never will again, so, it’s kind of, caught in the moment.. . Idon’t think anybody’s ready for it. It just kind of happens. I might be. Maybe.Mike: It’s such a weird feeling. .. . you think of all the big decisions that you have to makeahead and all the ones that you’ve made so far and it seems like nothing really hashappened so far and the next 10 years is going to be what shapes the rest of your life.. . . justrealizing that it’s time, like it will take awhile to get used to that, but I’m sure that when thetime comes I’ll be ready to go.While they anxiously anticipated freedom from the rules, routines, and the lack ofautonomy that high school imposed, they remained firmly incorporated in theirfamiliar world. 1-ligh school, despite all its failings, was described as “safe” and“cozy” -- a “sheltered” environment. Anticipation of the unfamiliar world beyondhigh school resulted in feelings of “apprehension” and uncertainty.Leona: High school is your security, you don’t have to worry.. . too much about being onyour own. This is your little security blanket, but, so that part is scary.Yet, when asked in the first interview about their plans for the future, moststudents were able, with varying degrees of specificity and certainty, to articulatetheir post-high school intentions. A detailed account of stated and planneddestinations of interviewees in October 1989 and May 1990 in relation to theiractual post-high school destinations (as of October 1990) is presented indiagrammatic form in Figure 25. Figure 25 may at first appear to be a confusingarray of arrows; however, it is the origins and insertions of the arrows that are ofinterest.Unlike the concise categories of “university participant” “non-universityparticipant” and “non-participant” provided by the survey questionnaire and usedas the dependent variable in the quantitative components of my research, FigureOctober 1989(n49) • My 1990(n46)262October 1990(n44)Figure 25: Stated Post-high School Destination (October 1989 and May 1990)and Actual Post-high School Destination (October 1990).* The two students who were unavailable for the second interview are excluded.26325 portrays the complex of possible and actual destinations confronted by highschool students33.While there is considerable movement toward non-universityand work as post-high school destinations between October 1989 and May 1990,there is virtually no movement toward university. Between May 1990 and October1990, in all but one instance, movement occurred away from intended post-secondary participation and toward non-participant status.Figure 25 provides the first glimpse of the durable nature of some lifetrajectories. Those who indicated in October 1989 that they intended to continue touniversity following high school graduation were the most likely to followthrough with their plans. None of the students who were ‘undecided’ in October1989 went directly to post-secondary in the fall of October 1990. Only 1 of the 6students who planned to work after high school (and in this case work wasintended to be a temporary break before commencing university) carried on to apost-secondary institution. Of the 19 students who indicated, in October 1989, thatthey planned to attend a non-university institution, 7 entered the labour force, 1was unemployed, and none went to university.Figure 25 also depicts how plans change during the graduating year ofhigh school. Again, the most stable group were those who stated in the firstinterview that they were university bound.Why is it that students make the decisions they do regarding post-highschool destinations? What accounts for the durable nature of some students’ plansand labile nature of others’? How do they perceive the choices before them? Howare enabling and constraining forces perceived and acted on? Bourdieu (1990a)states that enlightenment about real causes or real modes of practices must beTo some extent, even this detailed portrait is deceptive. For example, it does not reveal thosestudents on waiting lists for entry into community colleges or those with definite plans to attend apost-secondary institution following a student exchange programs overseas (identified “other’).264sought be asking informants the question “why?”. Hence, throughout the twointerviews, students were invited to discuss ‘why?” -- regarding their dispositionstoward and beliefs about post-secondary education, their perceptions of parentsas sources of cultural and social capital, the role of counsellors, teachers, andfriends as sources of secondary social capital, the role of academic capital instructuring choices, and enabling and constraining factors regarding post-highschool destinations. In other words, whereas the LISREL analysis confirmed thatsignificant paths among the constructs presented in Figure 24 do exist, in thischapter the same model of Post-high School Status is analysed with interview datato illuminate why” these paths or interrelationships exist.Each student provided an inimitable account of how past and presentevents and conditions were linked to her or his future. The considerable diversityin interviewees’ aspirations, goals, and views of the “good life” suggestedheterogeneity within and between groups of non-participants, non-universityparticipants, and university participants. Of those intending to continue to post-secondary education, some students planned careers in areas such as medicine,law, court recording, legal secretarial work, acting, and dancing. Others soughtfurther education with the hope that career interests would emerge. Equallydiverse were the goals and reasons of those planning to enter the work worldfollowing high school. One entrepreneur planned to expand her company. Forothers who lacked the economic capital to continue directly into the postsecondary system, a temporary detour into the work world was simply anecessity. Yet, others faced whatever they could find in the work world “as longas I make enough to live on”. For a few students, their goals revolved aroundstaying off welfare, or not ending up on the streets.Visions of the “good life” were markedly similar in some respects, yetdissimilar in others. While almost all indicated that the “good life” included a “nice265home” “being happy” and “having a nice family”, additional ingredients were asvaried as “having everything I want” “having a family with both a mother and afather” “having enough money to eat” “staying at home full-time with mychildren” and “not having to worry about rent all of the time”.Yet, despite individual diversity there existed a regularity of “wisdom,sayings, and commonplaces” (Bourdieu, 197Th, p.77) that demarcated participantsfrom non-participants, and non-university participants from universityparticipants. In the remainder of this chapter, the interrelationships among beliefs,dispositions, cultural capital, and sources of primary, social, and academic capitalare elucidated in order to help explain how the processes of educational choice arecreated and reproduced.Throughout the interviews student participants were encouraged todiscuss their plans in their own ‘voices’ and within their own personal contexts.Thus, in reporting the interview findings, I have attempted to retain these voicesas much as possible by including an abundance of anecdotes.Dispositions Toward Post-secondary EducationAccording to Bourdieu (1984), movement by individuals within a socialspace does not occur in a random fashion. Rather, this movement is the result of adynamic relationship where individuals are subjected to the forces whichstructure the social space in question, and where individuals use their ownunique properties (e.g. in embodied form as dispositions, or in objectified form asin goods or qualifications) to resist the forces of the field. He asserts that socialposition and individual trajectory are not independent of one another, for “to agiven volume of inherited capital there corresponds a band of more or less266equally probable trajectories leading to more or less equivalent positions” towhich he refers as “the field of the possibles objectively offered to a given agent”(p.110). Hence, all destinations are not equally probable for all origins. He claimsthat for “given classes of existence” there is a modal trajectory, and that the socialpositions and the dispositions of the agents who occupy them are stronglycorrelated.The common social space for the students in this study was structured bythe British Columbia educational system (see Chapter 2). These students were allin their final year of high school after having completed their elementary andsecondary years in a common school system. Yet, despite thirteen years ofparticipation in an educational system in which the “field of the possibles” wastechnically the same for all, differences in dispositions toward post-secondaryeducation held by those intending to continue and those with no intention ofcontinuing were remarkable.Four types of students, according to dispositions, emerged. The first groupwas comprised of those who indicated that they “always” intended to continue tohigher education. The second group was characterized by those who “never”planned to continue. The third group consisted of those whose dispositionsconflicted with the expectations held for them by others, and the fourth group,while inclined toward post-secondary education, felt that they were on their ownin making this decision. Each group is presented separately.“I Always Planned to Attend Post-secondary”For one group of students, the prospect of attending a post-secondaryinstitution following high school was described as an habitual state or naturalway of being; in turn, this habitual state actuated a predisposition or proclivity267towards post-secondary education. No other future was pondered, or ponderable.Rather, continuing to post-secondary education was “always assumed” and thusnot a decision.Larry: I haven’t spent a lot of time, like what I want is just instinct, like it’s just - I’ve neverhad to sit down and decide between this or this. . . . It hasn’t been a decision [to go tocollege].Troy: College, well it’s not a big decision because I always planned to go to college. Ididn’t have to really decide, it’s just like I, I worked it out for myself that I was going tocollege. It’s not like “Should I go to college or shouldn’t I?”, it’s ‘I’m going to college’ - it’sjust a fact . . . No it’s not, it’s not a super, super big deal. . . . college, yeah, and thenwhich university I’m going to, not whether I’m going to university or not. So, like I’vealways planned it.For some, because action would soon be required, this non-decision began toemerge as a conscious choice.Susan: Well, basically my whole life, when I talked to my Mom and Dad, yeah I’ll go touniversity, I never really thought about it - I’ve always assumed that I would go. But thisyear I’m thinking “well” and sort of thinking for myself, ‘What do I want to do?” and Istill think I want to go. But this is the first time I’ve really thought about it, like, just interms of what I want to do not just what I was going to do.For many of those planning to continue to post-secondary education, thedispositions they held toward post-secondary education -- as a natural way ofbeing and as a predisposition or inclination -- were directly attributed to parentalinfluence, either as expectations, cultural capital, or both. Parental expectations,according to students, became organizing principles for their subsequent actions.Janice: I don’t know, I guess it’s been sort of drummed into my head that university is agood place to go. Like my Mom has always just said “When you go to university, whenyou go to university”. I mean it’s a habit, other people just assume that I’m going touniversity - so I assume it.Victor: Yeah, but I always decided to do that. I always wanted to [go to university] .‘Cause I, ‘cause my parents kept telling me, like, you know, you have to do this, but I likeit too.Others recognized the association among parents’ cultural capital in the form ofeducational qualifications, the expectations held for them, and their owneducational plans. It was naturally assumed that they would continue to higher268education because of parents’ educational backgrounds -- ‘ ‘cause my father ishighly educated. . . he’s got a masters in education” -- or parents’ experiences withthe post-secondary system.Clive: They want me to go to [university]. Both of them have gone there before . . . . Thepeople I hang around with have no intention of going to college or university. I thinkthat’s quite dumb. . . . My Mom and Dad have brainwashed me sort of thing. But I knowthat’s the best way to go.Parents’ familiarity with college and university, based on their own personalexperiences, bred in their children a level of comfort with the idea of post-secondary participation and served to dernystify the notion of higher education.Nora: My parents went to university right away and they, and a lot of people, like myfriends are in university this year or the year before, like they went right there, theydidn’t really have too much of an adjustment. . . I’d just rather you know jump right intoit. . . . both my parents went there [to this university] and they really liked it.Yet, other students ascribed the very lack of parental cultural capital as thedriving force behind the expectations held for them. Limited educationalopportunities in their own youth and dissatisfaction with their own career pathsled parents to encourage their children to use education to improve their futures.Jasmine: My Mom, since I don’t know when, she’s been like, “you’ll go to school after yougraduate” and I guess that’s kind of sunk in and it’s stayed there, so I’ve never reallythought about quilting after Grade 12. . . She expects me to do things that she couldn’t dolike because her family was poor so she couldn’t, I don’t think she went to university andmy Dad couldn’t go, so my Dad wants us to do things but he wants us to makesomething, like be someone, because he learnt the hard way and he wants us to takeadvantage of everything that’s offered to us.For the majority of students intending to continue to higher education, their“natural” dispositions toward post-secondary education were clearly perceived tooriginate within the family domain. Interviewees acknowledged that long-terminculcation of parental expectations resulted in the habitus of these students as asystem of congruous dispositions -- as the result of an organizing action, a way ofbeing or habitual state and as a predisposition or tendency (Bourdieu, 197Th). In269this way, as Janice’s comments illustrate, parental expectations, often togetherwith parents’ cultural capital, served as ‘structured structures’ which in turnbecame ‘structuring structures’ and dispositions imposed within the family settingwere incorporated to the extent that they were “internalized as second nature andforgotten as history” (Bourdieu, 1990b, p.56).Janice: Well, my mom’s in university right now.. . . And, yeah, my step-dad has and myDad has and my step-mother have [graduated from university]. . . There’s also parentalpressure, there’s your friends are going and you should go because you get good marksand you’re wasting it - I don’t know, just a whole bunch of things. But mostly I want togo. Like, there’s never been any question, I’m not doing this because my parents or myfriends.Despite acknowledging the role of parental expectations and cultural capital, theindividualistic nature of comments such as Janice’s lend credence to Bourdieu’sclaim that as such, incorporated dispositions give practices their relativeautonomy.“It’s Notfor Me”For the second group of students, post-secondary attendance was describedas not within their “field of the possibles”. They asserted that intended nonparticipation was indeed “self-elimination “ (Lamont & Lareau, 1988) -- for thischoice was perceived to be both elective and desired.Celia: Um, it’s not for me, because I don’t even like high school, and I don’t think I couldhandle college or anything. . . . It’s not for me, I don’t, I just never think about it ‘causelike I’ve known pretty much all my life that I’m not going to go, you know.Karen: I don’t have the exact academic courses required [for university] anyway, so.Yeah, but I wouldn’t really want to either. It’s just the fact that 12 years is enough, I think.The connection between parental expectations and their own dispositions towardpost-secondary education was also evident to this group of students. These270expectations, however, sharply contrasted with those held by the group who were‘naturally” inclined to attend a post-secondary institution following high school.Mort: It’s like, nobody expects me to go on to post-secondary.. . my Mom doesnt. She’sknown for years that I’m not going. That’s been my plans. .. [my Mom expects] nothingreally. She basically, once I leave the house, I’m on my own. That’s just the way it’salways been. It’s an understanding.Jane: [My parents] . . . want me to get a job. It doesn’t matter if I don’t go to school.They’ll stifi charge me rent.Unlike the long-term imbuement of parental expectations acknowledged bythose “naturally” disposed toward post-secondary education, the habitus ofstudents not intending to continue to higher education was portrayed bystudents as either a long-standing distaste toward school which remained largelyuntouched by parental expectations, or as torpid attitudes toward schoolingstructured by a perceived lack of parental direction in their educational lives.Mort: I don’t like school. . . Mandatory learning is not my - I just don’t like it No, I’mnot one for school. I really, I don’t enjoy school. I don’t even, even the social aspect to meis not that great.Matt: [My parents want] to get me out of the house. Get luggage for my graduationpresent. My Dad doesn’t even think I’m going to graduate, so he hasn’t really put muchinto my education. . . . It’s my choice what I want to do, they really don’t get in the way ofwhat I want to do.Ivan: So it’s like my choice, you know. [My parents] said... “hey, you make the decision,you know, you’re going to have to live with it, we’re not”. So that’s what it was, it was,you know, there was no pressure from them it was totally what I wanted.Inevitable post-secondary participation was not embodied as an habitualstate, a predisposition or tendency, or as an organizing action. Nor was there atradition of post-secondary experience by the parents of this group of students.Almost all of the parents of this group of students had attained high schoolgraduation or less.John: No. From the first day I started school I never wanted to go any farther than highschool. That was it. My parents were just happy if I could graduate, ‘cause they didn’tmake it. My Dad was Grade 10, my mother Grade 11.271Thus, parental transmission of cultural resources, in the form of impartingfamiliarity with the post-secondary system, was absent for these students.Bourdieu’s notion of hysteresis of habitus may help to explain thediscrepancy between dispositions toward post-secondary attendance and actualopportunity to participate in post-secondary education. Hysteresis of habitus,according to Bourdieu, is a structural lag between opportunities and thedispositions to grasp them which causes opportunities to be missed (Bourdieu,1990b). Thus, while the “opportunity’ to attend some post-secondary institutiontechnically exists, the dispositions held by this group of individuals did notcoincide with these “opportunities”.“I Know I Should Continue to Post-secondary, but...The distinctive nature of those who ‘always intended to attend post-secondary” and those who “never intended to continue past high school” was quiteeasily discernible. However, it would be misleading to generalize these two typesof dispositions to all participants and non-participants. Not all students’dispositions matched their parents’ expectations or parents’ educationalbackgrounds. Of particular note were a third group of students who, in theautumn of their graduating year, tended to fall either in the “undecided” group orwho expressed vague plans to attend a non-university institution following highschool.According to this group of individuals, parents’ expectations exceededstudents’ own dispositions toward post-secondary education.272Sara: I think that’s my Dad. He went to college, and just thinks that we should all go tocollege, he’s a psychiatric nurse, and he thinks that that’s the way to go. He’d be reallyquite disappointed if I didn’t, so that’s a big part of it too. . . . I can’t say that my Mom andDad are pressuring me, I just can say what I know that they want and I always did whatthey wanted me to do and I just think, even if it is for a year.. . . I just think if I don’t gonow, if I don’t go right after I graduate, I might not go back, ‘cause I really, really don’tlike school. And if I have the chance to go out and work in this and that, well I just mightnot go back.Kevin: [My parents] want me to go straight to school. Urn, I just don’t feel like doing thatso they making me pay money if I don’t go straight to school.Rather than possessing a congruous system of dispositions, the facets were inconflict. While on one hand dispositions toward post-secondary educationbordered on being a natural way of being, on the other hand students’ own ownunique properties, despite high parental expectations, resisted embodiment ofdispositions as a predisposition or tendency. Thus, parental expectations, asorganizing actions, failed.“It’s LIp toMe”For a small number of students, long-term inculcation of dispositions wasnot expressed as the case; yet they planned to continue to higher education. Theyclaimed that the decision to attend was their own.Joni: No, it doesn’t matter. So it’s totally up to me. Like, [my parents] would prefer it‘cause you know there’s more job opportunities and stuff to you know go on to somekind of post-secondary education or whatever, but if I don’t want to, I don’t have to.Mike: I’ve got two brothers and a sister and none of them have gone to university. .[My parents] think it’s just great, that I could have the ambition to go and the grades todo it and I’m trying to. . . I’m serious enough about it to save up enough money and that’spart of the reason why they don’t - why they’re saying they’re not going to help me withmonies. Just to make sure I’m serious enough to go through with it.Unlike those who were “naturally” inclined to continue to higher education, thisfourth group was predisposed to post-secondary participation, but it was not ahabitual state. Nor were parental expectations perceived to serve as organizing273actions. These students did, however, appear to have one common attribute - theywere enrolled in academic programs in high school. The relationship betweenacademic capital and dispositions toward post-secondary education is explicatedin the next section.Bourdieu (1990b) asserts that native membership in a field implies a “feelfor the game in the sense of a capacity for practical anticipation of the ‘upcoming’future contained in the present” (p.66). He argues:The earlier the player enters the game and the less he is aware of the associated learningthe greater is his ignorance of all that is tacitly granted through his investment in thefield and his interest in its very existence and perpetuation and in everything that isplayed for in it, and his awareness of the unthought presuppositions that the gameproduces and endlessly reproduces, thereby reproducing the conditions of its ownperpetuation. (Bourdieu, 1990b, p.67)For those “naturally” inclined to continue to higher education following highschool, the “feel for the game” -- that is, the post-secondary game -- wasintroduced by parents at a very early age. As a result, the habitus or system ofdispositions held by these students included embodiment of the educationalgame; the intent to participate in post-secondary education appeared to be indeedsecond nature. Those not “born into the game, with the game” were required toconstruct the game if they planned to participate in post-secondary education.Those, for whom participation was “up to me” succeeded, and those who “neverplanned to continue” didn’t even try. The few who indicated that they “shouldcontinue, but” appeared to reject the game that they born into and with.274Academic CapitalIn the LISREL analyses presented in the previous chapter, one of thestrongest direct paths contributing to the variance in post-high school status wasthat of academic capital. That is, the higher the level of academic capital (in the formof credentials for university entrance requirements and grade point average) inone’s possession, the more likely the individual would participate in post-secondary education. A similar relationship between academic capital and post-high school status can also be demonstrated with interview sample data. As Table48 reveals, despite the fact that all of these students were eligible for admission atsome post-secondary institution, only 2 of 15 students without the requirementsfor university entrance continued to some post-secondary institution, comparedwith 20 out of 27 students with university entrance requirements. Also, the higherone’s grade point average, the more likely the individual was to continue tohigher education.Interviewees’ participation patterns, by curricular differentiation and gradepoint average, corroborate the findings of the discriminant function analysesreported in Chapter 7 and support Tinto’s (1975b) conclusion that rather thanincreasing participation rates among those without the prerequisites for universityattendance, community colleges functioned as a redistributive mechanism amongthose most qualified to participate by altering the type of post-secondaryinstitution attended. That is, the most academically disadvantaged Grade 12graduates were not continuing directly to community colleges.Of students from the remote and metropolitan schools, those with gradepoint averages of 3.00 or greater were more likely to attend university over a nonuniversity institution. Of those in the urban/rural sample, only 1 out of 6 studentswith university entrance requirements but with GPA’s in the borderline (2.50 -2752.99) category, continued to university. Decisions by this group are exploredfurther in the section on enabling and constraining forces.Table 48.Post-high School Destination by GPA, Curricular Differentiation and Geographic Location.Non-participantNon-universityUniversityColumn Total8 0 0 81 0 0 10 0 0 015 0 0 151 0 0 11 0 0 10 0 3 37 9 11 27Missing cases 2.* These students were participating in educational exchange programs, and all had definite plansto enrol in a post-secondary program upon their return.Also, LISREL analyses demonstrated a strong positive effect (for bothmales and females but stronger for females) of dispositions toward post-secondaryeducation on academic capital. These results also concur with the interview data.According to the group of students who were ‘naturally” disposed toward post-secondary education, decisions regarding level and type of course workundertaken in high school were made to ensure that the route to a future was leftopen. Were they limited by their choices?GPA< than 2.502.50 to 2.994 00 00 03.00or>000No requirements Requirementsfor university for universityGeographicLocationRemoteNon-participantNon-universityUniversityUrbaWruralNon-participant 1 0 0 1 2 1* 1* 4Non-university 1 0 0 1 2 5 1 8University 0 0 0 0 0 1 1 2RowTotal400104MetroRowTotal215276Clive: Limited no. I’ve opened most of my doors. By taking all the hard courses, it opensme - by just taking marketing or foods or something, it doesn’t - most of my doors wouldbe locked and. . . . I’m getting all A’s and that.. . . I’m doing 8 [courses]. Not a spare.Kirsten: No! No, I think I made pretty good decisions. I did it so I’d have lots ofopportunities. I left it totally open. Biology and chemistry, I have that in 12, and I havephysics 11, and the algebra 12, I have that, so if I wanted to do something like medicineor something like that, that door is open.Rather than “self-relegation” as defined by Bourdieu and Passeron (1979) andLamont and Lareau (1988), curricular and course choices for this group ofstudents assured the possibility of future “self-advancement”. If limitations didexist for the post-secondary bound, they were expressed as interest-related ratherthan route-related. Limitations regarding particular courses were perceived asdesired, elective “self-elimination”.Janice: I mean I don’t really regret anything I’m taking and I don’t wish that I had takenanything else. .. . I have limited myself, because I haven’t taken physics 12 and stuff likethat so I couldn’t be an engineer, but I never, ever wanted to be, something to do with thesciences, its just not what I wanted to do, so I don’t think of it as limiting myself.Curricular choices by those intending to continue to higher education wereoriented to future opportunities in the post-secondary sector. Their choicesensured that exclusion from future desired paths were minimized and theireducational investments were maximized. Curricular routes and course selectionwere portrayed as conscious, door opening strategies which resulted in inclusionin, rather than exclusion from further education.However, curricular choices for those who claimed to have no intention ofcontinuing, rather than being future oriented were described as anything theyhad to do to get through high school. These individuals described their choices asself-relegation into less demanding routes. Were they limited by their choices?Celia: Oh no, I think I made the right decisions. ‘Cause I knew they’d be easy classes....Well, I want to at least graduate . . . . the only reason I’m taking business courses isbecause it’s easy. You know, I’ll graduate with that, but, I’m not really into it.John: No. I just did ‘em, it didn’t matter. I just did what I had to do, what I had to take Itook or I followed somebody else I knew. It didn’t matter, as long as I got through. . . . I277needed a math and English and science, and I just took whatever ones I had to take andjust filled in the other ones, I guess with the easiest ones I could find.Rather than curricular and course selection as a rite of passage to furthereducation, the goal for these students was high school graduation. Futurelimitations ensuing from “self-relegation” into less desirable positions were eitherunrecognized or unacknowledged, or recognized but curiously not perceived asconstraining. For example, Leona did recognize the constraining nature of herchoices.Leona: Well, the courses that I’m taking now is not going to help me in my careers I don’tthink They’re quite mickey mouse I think, the courses I’m taking, but I need it tograduate. But I haven’t been one to really focus on my grades that much Familymanagement, acting, vocal jazz. I’m taking socials, math, English and p. e.She was aware that she had eliminated the possibility of attending university,“but you know, I just felt that this is the way I wanted it, you know”. Despite the“mickey mouse” nature of her courses, she was content with them. Truncatedroutes were not perceived as problematic.For Vivian, her experience in a business career preparation program taughther that secretarial work was precisely what she did not want as a career.Vivian: It really made me know that I want to have a job that I like because I didn’t reallylike where I went. . . . I was just doing secretarial work. . . . all I did was filing andtyping. I didn’t really like it that much.Yet, when asked whether her choices for the future were limited by her highschool curricular and course selection, she replied “No”.Others (all of whom became non-participants following high schoolgraduation) lamented their curricular choices. Choices for this group were alsoperceived to have been self-relegation, but were now considered to be a personalshortfall in judgment, made at a time when “I just wanted the easy way out, I just278wanted to graduat&. For these students, choices were also oriented towardgraduation, rather than further education.Roy: Well, I think I [made good choices], but I should have actually tried harder andpassed them, this way I wouldn’t be where I am now. I’d be a little further ahead.Well, the ones I picked in Grade 11 were good, but Grade 12 I had to sort of change, youknow, in order to graduate, I had to accept a few of the bad ones I didn’t really want -mechanics and cafeteria. I could live without them easily but seeing it will get me tograduate, I’ll take it.Students readily linked the dispositions they held toward post-secondaryeducation to the expectations and cultural capital of their parents, yet discussionsurrounding curricular choices was markedly devoid of the parental connection.Rather, curricular choice was described as an individual endeavour. Implicitly,however, the connection was present. Those individuals for whom post-secondary participation was “natural” were all participating in academicprograms -- programs that were clearly delineated by structured choices and thatarticulated with the next stage of life. In contrast, those who described post-secondary attendance as “impossible” and those whose parents’ expectationsexceeded their own almost exclusively participated in non-academic programs --programs that by design, led to nebulous destinations. Those who leaned towardpost-secondary attendance, but perceived that their future was up to them, wereall enrolled in academic programs.Beliefs about Post-secondary EducationRational choice theory posits that in order for an action to be rational, theaction should be the best way of fulfilling an agents’ desires, given her or hisbeliefs. Desires and beliefs must be both rational in themselves and internally279consistent. In addition, beliefs should be optimally related to the evidenceavailable to the agent (Elster, 1989b). Yet, as Elster concedes, while what explainsa given action is the persons desires together with her or his beliefs about theopportunities, it is not clear how subjective elements -- beliefs and desires -- andobjective elements -- evidence -- interact to produce an action.For Bourdieu (1990b) belief is ‘an inherent part of belonging to the field”(pAW). He asserts:To move to the decision to believe, which reason can induce, to a durable belief that canwithstand the interrnittences of consciousness and will, one has to invoke other powersthan those of reason. This is because reason, which we are supposed to believe capable ofleading to the decision to believe, can in no way durably sustain belief. (p.48)Rather, he expounds:the habitus produces strategies which, even if they are not produced by consciouslyaiming at explicitly formulated goals on the basis of an adequate knowledge of objectiveconditions, nor by the mechanical determination exercised by causes, turn out to beobjectively adjusted to the situation. Action guided by a ‘feel for the game’ has all theappearances of rational action that an impartial observer, endowed with all the necessaryinformation and capable of mastering it rationally, would deduce. And yet it is not basedon reason (Bourdieu, 1990a, p.11)In Chapter 2, it was argued that higher levels of education are associatedwith higher incomes, more prestigious positions in the work force, lowerunemployment, and increased general wellbeing. In other words, there appears tobe overwhelming evidence to support the claim that it would be rational to believethat the route to the “good life” is most likely to be aftained through post-secondary education.What is it that students believe about their future life chances with orwithout a post-secondary education? Are these beliefs based on prevailingevidence? Do all students hold the same beliefs? What is the relationship betweenbeliefs and dispositions or the habitus of the individual?280For the most part, regardless of intended post-high school destination,almost all students expressed the belief that without a post-secondary educationtheir lives -- in terms of employment, quality of life, and future career advancement--would be compromised. However, substantial differences are evident in the waythese beliefs are incorporated into ones intended practices for participants andnon-participants.“I Have to Go to Post-secondary to Get Ahead HFor those intending to continue to post-secondary education, belief in thenotion of “human capital” was firmly entrenched. Schultz (1960) defined humancapital as an investment in oneself, for “by investing in themselves, people canenlarge the range of choice available to them. It is one way free men can enhancetheir welfare” (p.3l4). For the majority of those planning to continue to the post-secondary system, the prospect of directly entering the work world -- that is, notattending a post-secondary institution at all -- was “unthinkable”.Troy: Ever? No, God, I couldn’t, can’t imagine doing that.. . because it sort of cuts youoff from doing a lot of things. You got your high school diploma yeah, but you could...work at Eaton’s or something. . . , but for the real, like for the really important - like, thehigher paying jobs and the - you need the college and university education. Like it’s hardto go anywhere if you’ve just got high school.Marcus: No. That’s not possible. I wouldn’t be able to get anywhere in this world. I needpost-secondary education to allow me the career, lifestyle, opportunities that I want.Belief in the concept of human capital was expressed as strongly by the women inthis sample as by the men. That is, they believed that self-investment throughpost-secondary participation would ensure that they too could enhance theirwelfare and expand their range of choices.Lisa: No. Definitely not.. . I just don’t think that the jobs that you’d get right out of highschool would be - this may sound arrogant - worthy of myself.. . . I don’t think I coulddeal with just getting out of high school and going on to a job, because I don’t think you281could really get one that had a really good future in it, and I want something better formyself.Elaine: I have to go to university. . I just don’t want to be a clerk or a - not make money,but I want to be in a profession that I like and I don’t think that there’s too many outthere that I would like to be in that I don’t need a university degree.Again, beliefs toward post-secondary education were associated with theeducational background of their parents.Patti : No, I’ve never, that’s never been a possibility [not go on to college and university].‘Cause, just ‘cause my parents both work and have gone to university and all that and it’salways been to go to school and get an education.Not all students were as definite. Rather than “unthinkable”, the possibilityof not attending a post-secondary institution existed. However, when weighedagainst the alternative -- a dead end job and low wages -- post-secondaryparticipation was deemed to be more likely to lead to better life.Joni: I’ve thought about it, but I don’t really know what else there is, you know, ‘causelike I don’t want to just like be a grocery clerk or something like that. You know, like Ican’t really think of anything else to do.Linda: Well, in the younger grades I thought so, but I think to succeed you sorta needmore education and that now, but I think it would be more beneficial if I did go on to dosomething.For the majority planning to attend either community college or university, lifewithout a post-secondary education was anticipated to be unchallenging,repetitive, unstimulating, and unsatisfying.Nora: Ummm, low paying job, or a job where you don’t use much brains in. . . Not reallyrewarding probably ‘cause I don’t really like to do things like you don’t have to thinkabout.. . Like I have a job right now at the mall, I just work in a sports store and like Ilike it for just working for now but I know I wouldn’t want to do that for my life. Liketaking stock and, I don’t know, helping people, that’s okay but I like to help people withsomething more useful than just selling them clothes.Trudy: I’d probably just get a full-time job that only pays $5.00 an hour and just living athome until I - I don’t know, I don’t know what I’d do without college. I wouldn’t have, Idon’t think I’d have much of a future.282The possibility of advancement in a career was not viewed as necessarilyimpossible, but aleatory at best. With the aid of “luck” “winning the lottery” or“connections” a reasonable future might possibly be secured. By “applyingyourself” and “really working at it” an individual might be able to transcendlimitations imposed by a lack of educational credentials; however, the threat ofbeing “up against people who have gone to post-secondary education” would beomnipresent. The route to a career via post-secondary education was perceived tobe easier, involved less risk, and provided more guarantees.Victor: Oh, you can’t do much, or else, if you have good connections, maybe you couldwork in your parents’ company or something, but my parents, they don’t have acompany, or they don’t have friends that have like major corporations or things like that,so there’s not much to do.Carla: Oh, well, I’m sure it would if I was, you know, extremely talented or I got a luckybreak, or I was a really really hard worker, but I would probably rather just get a degreeand then look for a job. Do all my work and then look for a job, rather than have to tryand ‘make it’ from bottom working up to- the top of a company or something like thatover some years. I’d rather just have a degree.Acquisition of a post-secondary credential was seen, as Collins (1979) asserts, ascultural currency to purchase desired occupations in an era of competitiveness.Moreover, a post-secondary credential was perceived as “a piece of universallyrecognized and guaranteed symbolic capital, valid on all markets. As an officialdefinition of an official identity, it releases its holder from the symbolic struggleof all against all by imposing the universally approved perspective” (Bourdieu,1990a, p.l36) Again, the perceived value of an academic credential was held asstrongly by the young women in the sample as it was by the young men.Lisa: I think I can get a really good job, and make a very substantial, well, make it, makemy life really what I’m worth with a post-secondary education. I can get really good jobs,like well I’m not saying I can necessarily get them, but I have the chance. I’ll be qualifiedto get the jobs if they’re out there.Marcus: A university degree provides a guarantee that I’ve accomplished something. Anemployer knows that I’ve gone through a specific program. Without it, I would have toprove myself, with testing or something. Yes, a degree shows an employer that I’ve metthe requirements.283The benefits of higher education were also described in relation to learningand education for itself. Post-secondary education was envisioned as the route toa good life, not only in terms of employability and marketable skills, but also interms of self-actualization. Further education was perceived as an individual‘choice’ of a better future.Sally: Offering me a chance to succeed in life. All the opportunities are there, it’s just theindividual has to decide that they want that out of life and if they want it then they’ll gofor it and they will get it. . . it’s the individual’s choice to succeed.Intended action was not simply based on desires and beliefs in relation toevidence. As Larry’s comments illustrate, beliefs were formulated in light ofevidence and in relation to long-term instillation of dispositions:Larry: My uncle who was somewhat my idol, never went to school, and he’s a successfulbusinessman. I thought about that, but then the more I think about what it’s like todayyou don’t get anywhere without - my chances are better going to university and collegeand everything. So, though I’ve thought about it but I’ve never thought it really practicalfor me. I’ve always expected myself to be going to university, and everybody, my parentsand everybody expects me to. It’s never been a question of “Oh do I want to go, or don’t Iwant to go”, it’s always been “I want to go” so I’ve never really thought about it. Well, Iguess I did a long long time ago. It was just pushed into my brain. . . It’s just what’sexpected of me, and what I expect of myself. Although I’m sure if I said “I don’t want togo” it’s not like I’d be forced to go but, you know maybe they’d be disappointed, like myparents. . . No they didn’t [go to university or college]. . . Yeah, it’s like [my Dad has]always seen university for me and I’ve never said ‘No, I don’t want to go to university”so it’s always been expected of me, yeah.In the discriminant function analyses presented earlier in this paper, it wasdemonstrated that beliefs about post-secondary education were not gooddiscriminators of post-high school status. That is, according to results of thesurvey questionnaire, non-participants also held the view that post-secondaryeducation was necessary to be prepared for a job, increase one’s income, and havea wider choice of jobs. Neither was the construct beliefs about post-secondaryeducation very strong in explaining the variance in dispositions toward postsecondary education or academic capital.284At one level, the interview data corroborated the findings of the surveyquestionnaire. Those not intending to participate in post-secondary educationindicated that they also had incorporated the “human capital” view that post-secondary education was important for self-advancement.Karen: If I would be better off [to go to post-secondary]? Oh yeah, I know I would be!Anyone would be! . . It would give me more education and give me more I don’t know,choices of things.Roy: I have 2 older brothers who. . . actually they haven’t graduated and they’re notgetting very far,. . . well they’re both just working full-time and they’ll never really getreal good jobs ‘cause they don’t have the education to get it.The contrast between participants’ and non-participants’ beliefs surfaced when thenotion of post-secondary attendance was transferred from an abstract, generaldiscussion of the benefits of post-secondary education to a concrete, personaldiscussion of “what it would dofor me”.“Sure, Post-secondary Education is Important, It’s Just Notfor Me”Whereas participants viewed post-secondary attendance as an avenue to“achieve whatever I want in life” “provide a credential to get a job” “help me reachmy full potential” and “make me more interesting”, non-participants emphasizedthat without a reason, purpose, or goal, post-secondary participation would be anugatory exercise.Ivan: Urn, it matters what you want to do. For - if you want to be a teacher or something,it would be really important that you go, but if you were just going to do little things,urn, to the point of general knowledge, I don’t think you’d have to go to university oreven college or some post-secondary because most of it’s covered, the generals stuff’scovered at school so you have your basic understanding. To do - you could always go tocollege I guess for upgrading or something like that, and maybe that probably would bethe maximum a general person would have to do for like general jobs. So, but other thanthat, I don’t think post-secondary education is too important. [There’s no reason to go]unless you really know what you want to do.285Without a definite reason to attend, post-secondary education was as akin to highschool attendance -- purposeless, unenjoyable, meaningless -- another way to driftand not excel at anything.Mort: If I was set on what I wanted to do and knew what I wanted to do, then I couldfocus in on that, like a lot of people I know are going to college and their first 2 years arespent trying to find out what they want to do and all they basically do is hop aroundfrom course to course seeing what they like. To me, that’s a waste of time and money.And if I knew what I wanted to do, I guess I’d do it. I guess, a lot of reasons, like a lot ofproblems with my high school, I don’t really, I don’t know what I want to do in highschool.Celia: I’m not very good at anything, that’s why. Like I’m not really good in art, science.Rather than opening doors, further education was perceived as constraining.Post-secondary participation, in these students’ eyes, was seen as postponementof the inevitable -- the establishment of a position in the work world.Karen: It’s kinda always external forces, pressures, that like I don’t want to, I want tomake something of myself now instead of, you know, like 5 years down the road afteryou have a high school break and you’re still not into anything and you don’t want tobecause you’ve had too big of a break and it’s kind of enjoyable and you’d want to go onwelfare and all that. I’d just rather get started, something started, even if I can’t for awhileat least I’ll still have my mind set on something. Hopefully it turns out to be enjoyableI’ve thought about it but I don’t think [post-secondary] would help me go anywhere.Like what happens if you spend four years in college or university and you decide on acareer and you have to go for another four years?While incumbent participants were convinced that post-secondary education wasthe minimum requirement for success, non-participants emphasized theimportance of high school graduation.Mort: I don’t like, like I don’t like school, but you do need it. You can’t get anywherewithout Grade 12. I don’t care what anybody says. People say, oh yeah, people makemillions and only have Grade 9. Those are exceptional people. Chances of you being oneof those people is like one in how many, one in 25 billion people. So I - and I’m not, I’mnot interested in pumping gas for the rest of my life either. That’s basically all you can dowithout a grade - actually you need a Grade 12 to do that now.. . I’ll definitely completehigh school. That’s the one thing you can’t do without. I mean if you don’t have yourhigh school, you basically you’ve ruined your life.. . . high school is like you can’t get ajob without it. It’s like a prerequisite for almost every job.286Celia: Well, I want to at least graduate. . . . it wouldn’t feel right dropping out of highschool, ‘cause a lot of my friends have, and they regret it. One of them was living on thestreets for a couple of years, so I don’t want to do that.The necessity of a high school graduation certificate was not merely recited as therhetoric of the day. Experience, both lived and vicarious, had already informedthem that symbolic capital in the form of a graduation certificate was currently aminimum. This minimum was not only required, but it was sanctioned by thesestudents as a legitimate screening mechanism.Mort: You know, and I mean there’s no way you’d ever get a decent paying job withoutfinishing high school.. . . You can never be a manager without the high school degree...Even if you were good. ‘Cause I mean how can they trust you’ how can they trustyou if you can’t finish high school? How can they trust you in a restaurant? Like if you’renot smart enough or whatever, you don’t have enough commitment to finish high school,well like this is a real job that people are actually depending on you. You have to be ableto manage money, manage your time, manage like the back scenes of a restaurant.These students recognized that a high school graduation certificate was beingrapidly replaced by the need for higher credentials, credentials that wereperceived to be associated with skills and knowledge rather than credentialinflation. As Ivan concluded “it’s just like so overwhelming what you need foreducation just to have a liftie job”.Ivan: Post-secondary too, that’s getting more and more important. ‘Cause urn, even to bea labourer like my Dad is, you have to have your Grade 12 and some of them have tohave, what was it, first year of college engineering to know how things work, to - howthings are designed, to read the blueprints and that. They have to know what theengineers mean when they put something down so they have to have a first year ofengineering at the college level.Whereas a discrepancy (or structural lag) between their dispositionstoward post-secondary attendance and opportunity to attend post-secondaryeducation existed for the group who perceived post-secondary participation to be“impossible”, strong beliefs about high school graduation, their dispositionstoward high school completion and the opportunity to do so were harmonious.287In their study of working class youth, Gaskell and Lazerson (1980) reportedthat youth who entered the work force directly from high school described theirjobs as boring, low status, and with little in the way of opportunities foradvancement. For the youth in my study who were headed for the work world,this reality was not something to be discovered -- it was expected.Mort: I think it’s going to be a real shock going into the work world. Like I’m not lookingforward to that. I can honestly say, I think I hate school now, but I know I’m going tohate work worse. ‘Cause monotony, just monotonous. I don’t like monotonous things. It’slike here, I can just pick up and go if I want to, like if I want to this afternoon, like who’sgoing to care, no big deal. You can’t do that at work. You can’t just - they care here but Imean you can still do it, but at work you can’t, right. There are people counting on you,people watching you.Stan: Well, from what I’ve seen, people graduate in our village, like,. . . about 3 or 4 outof 10 of them do something with their life. The rest of them, just siffing around workingin the sawmills. So I guess it’s just do what you have to do. Do whatever you want. Idon’t’ know how to explain it. . . . you finish school and you’re supposed to be happy,and when you go home, you either sit at home or work in the sawmill. There’s nothinghappy about that. . . No. Sawmills, you just get something like 5 bucks an hour to startwith.These students may indeed have “refused what is anyway refused”; however,their remarks did not suggest that they “love the inevitable” (Bourdieu, 197Th,p.77). The future was not described as rosy or bright. Rather, chronic employmentlimitations were perceived and anticipated with dread. Resistance of theinevitable, however, appeared to be minimal. In particular, the one form ofresistance that was available to them -- that is, post-secondary participation -- wasnot perceived to be a solution.Despite ubiquitous beliefs about the importance of higher education andinsights into what life would be like without it, non-participants had noteliminated work as a legitimate post-high school destination. Whereas the workworld was either not within participants’ repertoire of possibilities or was“possible, but I don’t want to”, non-participants were willing to at least give work288a try; only upon failure in the work world would they consider post-secondaryeducation as an option.Matt: Well, it depends if I get a good job, a steady job, I’ll keep that. If it looks like it’sgoing to turn into something. If it’s not, I’ll go back to school. . . . something paying lotsof money with benefits and it looks like it’s going to go somewhere.Karen: I don’t want to go [to college] but if I had to go I would. Like if there was reallynothing available without it. Like graduation doesn’t mean anything.. . . because it’s allpost-secondary now. I mean ten years ago if you had Grade 12 you could get intoanything. Now it’s “yeah you’ve got Grade 12 now you need post-secondary” so Iprobably will have to go for some course or other.. . . I’d rather do it on my own thanthrough a community college.These students were aware of the risks of having to compete with those whopossessed post-secondary credentials. Yet, despite conceding that the competitionwould “have the security of a post-secondary education, which is more beneficialto a job”, attempting to establish oneself in the work world was worth the risk. Ifall else failed, they could return to school.“I’d Probably Succeed, But I’ll Be Better Offwith Post-secondary”For a third group of students who intended to postpone entry into the post-secondary system, eventual participation ranged from “probable” to “inevitable”.The beliefs held by this group were a sort of hybrid between those “naturally”inclined to attend and the ardent non-participant view.Hal: Yeah, I’ve thought about it, but then I didn’t think there’d be much of a chance. Like,I would like to do that [go straight to work], like that’d be great if I could do that, but Idon’t think it’s very realistic. Especially for an architect, like you need a lot of training inthe sciences and a lot of artistic talent, so I think you’d have to develop it a while first.But if it would happen, I’d love it, but I don’t think it would.Linda: Urn, it probably would be fine for me [if I didn’t go to post-secondary], but I don’tthink I could go as far as I wanted to. I don’t think I could succeed as well, you know....I think if there’s a will, there’s a way. So, if I really wanted to succeed without going on topost-secondary education I believe I could, but I think it would just be easier with someother kind of, or more formal education. I think it would just be more of a guarantee.289The message “If you Iave it in- you to tiream, you nave it in- you to succee& orvariations thereof, was the most common theme expressed in posters that paperedhigh school walls. This message was reflected in these students remarks;however, the ‘dream” was deemed more achievable through post-secondaryparticipation.Primary and Secondary Sources of Social CapitalThe role of “significant others’ -- parents, teachers, counsellors, friends, andsiblings -- has long been recognized as influences on post-secondary participation(Bratlinger, 1985; Breton, 1982; Olson, 1981; Porter, Porter, & Blishen et a!., 1982).Most often, however, studies (including the quantitative analyses in my research)are limited to measuring whether significant others influence participation (seeHauser, Tsai, & Sewell, 1983; O’Neill, 1981). As Lareau (1987) asserts, very littleresearch has been carried out on the processes of family influence in creating andreproducing educational patterns. The concept of social capital, as explicated byBourdieu (1984) and Coleman (1988, 1990) allows for an exploration of howparents as primary sources of social capital, and counsellors, teachers, and friendsas secondary sources of social capital, influence educational choice.According to Coleman (1988), relations between parents and their childrenconstitute social capital. He claims that unless the cultural capital34 possessed byparents is complemented by the social capital incorporated in family relations,Coleman (1988) uses the term ‘human capital’ to refer to parents’ education which “provides thepotential for a cognitive environment for the child that aids learning” (p.S109). To be consistentwith Bourdieu’s terminology, I have replaced his references to ‘human capital’ with ‘culturalcapital’.290cultural capital alone may be insufficient; it is through social capital of the familythat children are able to gain access to the cultural capital of parents.What is it that parents, as primary sources of social capital, do to influencetheir children? What role do secondary sources of social capital -- counsellors,teachers, friends -- play in relation to and independent of the primary sources ofsocial capital?According to post-secondary participants, parents served as sources ofprimary social capital in three ways: 1) as information channels, 2) as supportsystems, and 3) as suppliers of economic capital.Parents, and mothers in particular, act as information brokers andenvironmental scanners, thereby establishing channels of information about thepost-secondary system. They were willing and able to assist in the search andchoice phases of post-secondary choice (see Hossler, Braxton, & Coopersmith,1989) by sifting through the myriad of available material, interpretinginformation, and by actually assisting with application procedures.Clive: My Mom has done a lot of research. She knows.Patti: No I haven’t [gone to the college to seek out information]. But my Mom has, just forcourses that I needed for university, since my Mom works there, like about French 12,like I didn’t know if I, like I didn’t want to take French 12 but I didn’t want to be stucktaking it in university. So my Mom checked with the counsellors there and decided that Ineeded it and all that, so I’ve used it in that way.Other students emphasized the importance of parental support, in the form ofencouragement, interest, and even by the imposition of sanctions forunacceptable choices.Trudy: My Mom. And she’s always encouraging me to, like I said, get better grades andshe’s always helping me with what choices I want to make and she’s always on the sidewhere you’ve gotta make money and you want a job that you’re going to enjoy but you’regoing to make lots of money at it as well. So I mostly talk to her about it.Kevin: Who do I talk to? My best friend, my Mom mainly, my Mom and my Dad. They’reharshly interested in it right now, you know, they’re always pushing me a lot to get good291grades. I don’t know, that’s about it, just my parents.. . . They would like me to go on, goto post-secondary school, which is fine. I don’t mind it. Just like, we have a thing, youdon’t go to college, you have to pay to live in the house, but if you go to college or anypost-secondary school, they pay your way, and you just gotta pay for book fees and stuff.So it’s pretty good. [They’re supportive], if you go the right way. If you don’t, they’re notreally behind you. . . if you go the way they don’t want, you gotta be by yourself.Parents, and mothers in particular, helped their children to clarify the rules of thepost-secondary entrance game, and to maximize investment of existing capital.Or, to use Bourdieu’s (1976) metaphor of a card game, mothers helped theirchildren recognize the hand dealt to them, then instructed them to shrewdly playtheir hand. Parents as both sources of cultural and primary social capital helpedto construct and develop the hand.In the LISREL analyses reported earlier, the path between sources ofcultural capital and secondary sources of social capital, only for females, wassignificant and negative. This finding was supported by interviewees’ comments.For individuals whose parents acted as strong sources of primary social capital,the need to seek secondary sources of social capital -- from high schoolcounsellors, teachers, and friends -- was diminished.Patti: No. I.. . myself, I haven’t talked to a counsellor really about my career choices. I’vejust kind of done it up with my parents ‘cause they kind of know what courses I shouldtake and everything. But I will be talking to a counsellor from the college that will helpme.Clive: Myself, not very often, but I know some people that do and they got a lot ofinformation from [counsellors]. Like their parents haven’t gone to university or anythinglike that and they have no background in university or anything like that, so they go tocounsellors here, and they do a good job.The volume and quality of social capital as information channels was largelycontingent upon the level of cultural capital, in the form of educationalqualifications, possessed by parents. However, when parents were perceived topossess inadequate amounts of cultural capital to help their children negotiate the292transition from high school to the post-secondary system, counsellors andteachers were promoted to the position of primary supplier of social capital.Lisa: Urn, well at home, like I’ll discuss like what I want to do. Mom and Dad will giveme suggestions, but they really dont know what the colleges and universities can offerso I usually go to Mr. [counsellor] the counsellor, and he helps me with that. . . . Mr.[counsellor] being a counsellor, he’s always really helpful. Well, all of the counsellors are,as far as thats concerned. They really know what they’re talking about.Roshne: Well, for one, I talk to my career prep teacher. I also go to Mrs. [counsellor], ourcounsellor. She gives a lot of good advice, she’s a lot of help. My parents don’t help muchBut when I discuss my plans for a career, it’s mostly to teachers, because I guess Ican relate to them better because you know their careers or what they’ve experienced..Well, my parents haven’t had that much education and my mother just stays at home,and my dad’s a mechanic.Reliance on counsellors by those who are dependent on their advice was notalways ideal. Without the ‘feel for the game’ instilled by parents and without thebenefit of ongoing discourse about post-secondary education with parents, somestudents were mystified by what they needed to know and they were limited bytheir inability to formulate salient questions which would allow them to pursuethe necessary information. Assistance by school personnel, particularlycounsellors, took the form of unidirectional dissemination of information, ratherestablishment of a network of social capital.Jeremy: Yeah,.. . [the counsellor] does give me some information. I don’t, I think it’s beenmy fault that I haven’t asked him quite enough. And he’s been sort of busy, but if he cangive me a lot of information about you know, just the usual information on how to dostuff. He’s helping me with some of my courses and deciding, but, but I have more of adetermining part in what I’ve been doing over Mr. [counsellor] but he’s there at least togive me some information that helps.When both primary and secondary social capital were wanting, negotiating theway through the maze of information and procedures was an overwhelming andalmost insurmountable task. Mike (below) describes the difficulties in overcomingthe effects of “overselection” (Larnont & Lareau, 1988) or limited capital.293Mike: It’s been kind of a struggle, I’ve had to help myself quite a bit really. . . . just, there’sthe information that’s available in the counsellors’ office, talk to various people. One ofthe counsellors is new here so she doesn’t know as much about universities and gettingin and all that’s involved in that which is, maybe she could so, you got to look out foryourself. And as far as scholarships go, you’ve got to keep your eyes open and look afterthat kind of thing yourself too.. . . Yeah, I didn’t know how to fill out some things on myapplication and [the counsellors] couldn’t help me so I filled it out myself and askedaround. . . . Well like I didn’t know what a faculty was or what department but thefaculty of Arts and Sciences, which degree I was after or anything like that. .. Well Ijust had to read through most of the calendar before I found what I was after and I sentin an application, well I didn’t send it in, but I filled out an application for IJBC to applyto the Faculty of Rehab. Medicine but you’re not even supposed to apply until the secondyear so. It was just things like that. So a bit confusing.Yet for Janice, with access to the same counsellors but with the benefit of social(and cultural) capital provided by her parents, negotiating her way through thesystem of procedures proved somewhat more agreeable:Janice: I rely an awful lot on myself I think just to figure things out but my Mom and mystep-Dad have helped quite a bit. they’re, they’re not directly involved so they can sortof not get all panicked about it and see it more objectively . . Trying to fill out theseapplications and scholarships things you can get really “Oh my God I’ve, like if don’t fillthis one in right they’re just going to throw it out!!The presence of parents as sources of primary social capital and teachers,counsellors, and others as sources of secondary social capital resulted in whatGluckman (1967) refers to as multiplex relations which, according to students, dofacilitate their actions. The multiplex nature of social capital was depicted bystudents as a nexus of the type social capital available (as information channels,support and encouragement, norms and expectations, and connections) and thesources of social capital (parents, siblings, counsellors and teachers, andinfluential others). The following rather lengthy excerpts illustrate the multiplexnature of social capital.294Conrad: Well, my parents have a good friend in Victoria who helped set up the CoastGuard College in Sidney and he’s told me a lot about it so I went down to Victoria thissummer and stayed with him for awhile. He’s a retired naval officer and he’s beenthrough it all and he’s enjoyed it and he’s given me tips and things to remember, so I’vetalked to him. . . Well, he gave me a little booklet and I went over it with my mother andfather and my brother and my sister and they’ve all helped me out because they’ve allgone through college so I’ve basically done it all right.Trudy: I guess at the end of last year. . . I went up to the counsellors about my grades,and I was talking to my parents, and my parents kept telling me, well they’ve alwaysbeen telling me that “you should think about what you want to do and then put yourcourses, even in high school, towards what you want to do” and I never - I thought ‘Ohno, that’s too far away, and then when I went and talked to the counsellors, they said“that’s pretty close, you’ve got a year, and you’ve got to pull up your grades and decidewhat you want to do the rest of your life, so that’s when I started to think what I reallywanted to do. Well I knew, I knew what kind of, well I’ve always wanted to work withchildren, like I love babysitting and things, so I always wanted to work with children, butI just didn’t think I was smart enough to do that, the teaching part of it. . . . I was realfortunate that a lot of my teachers took a real interest in me because I was, because I wasurn, they knew I could do better than I was and everything. So a lot of them know mequite well. They know my parents and stuff.That certain types of students seek advice was acknowledged by thecounsellors. One counsellor remarked that it appeared that there were two typesof student -- those who visited the counselling area for information on colleges,universities, and scholarships, and a second group who did not seek such help.Both of these types of students continued to post-secondary education. Heneglected to mention those students who did not continue to post-secondaryeducation. However, when asked he stated:You mean those who are absorbed by the work force directly? No, we really don’t seethose students - it’s a shame. We’re here for them, but they don’t use us, and we don’tknow how to reach them. We would have to take them by the hand, and we can’t do that.By the time they reach Grade 12 you would expect them to be responsible.For this latter group of students, a sense of ongoing dialogue with parentswas lacking, or if it did exist, the direction of the conversation was student-initiated, rather than parent-initiated. Whereas students with strong primarysocial capital used information and knowledge acquired within the family settingto establish recursive multiplex relations, those lacking primary social capital wererequired to decipher what information they could from other sources (primarily295the school), which they then may or may not have shared with and interpreted fortheir parents.Roy: Oh, [I talk with my parents] here and there, not too often. Just occasionally I tellthem what I want to do.Saphia: Well, my Mom and I, well she doesn’t really, I’m my own person I guess, so it’smostly just me. I’ll listen to her but, she’s not pushing me anywhere, she’s encouragedme, she’ll encourage me anywhere I’d like to go. I really don’t have much decisionmaking from her, just me, but she supports me.Nor were counsellors or teachers identified as sources of secondary social capital.Social capital in multiplex form, did not exist for some students. Even if theavailability of several resources was acknowledged, they remained disparaterather than interconnected in a multiplex sense.Karen: I really don’t want to ask for help unless I know exactly what I want to do. And Idon’t know, I want to say “Well, I need help”. I want to find out all about this and I reallydon’t even want to do that. . . . I don’t know. I just, I don’t know what I’m thinking about.I just get confused. I never thought I would be one of these people in Grade 12 that don’tknow what they want to do.While a multiplicity of resources and sources of social capital wasidentified by students as important in shaping their decisions regarding post-highschool destinations, the role of parents was regarded by many as paramount.Parents’ influence clearly surpassed that of friends, counsellors, and teachers.Claire: Parents are big, a big factor. If your parents are supportive then - everyone lovestheir parents. Even the ones who say “I don’t like my parents, my parents suck” and allthat. That’s not true. Your parents have a lot to do with what you decide to do next. [Myparents] are the best parents in the whole world... . They’re harsh... . I have my parents[to help me].Students with parents as strong sources of primary social capital recognized itsimportance not only for themselves, but also for those who lacked it. In theabsence of primary social capital, students signalled the need for substitution ofother sources of social capital.296Anne: I think [counsellors] should talk, and try to convince you more to like try everyway possible to help kids graduating to go to college. So really just to talk to you moreabout it. Kind of pushing you and convincing you, ‘cause some kids don’t even hear it athome. So they don’t really care, they think that working will be good for them, but Ithink that the counsellors should push harder towards the kids. Say “okay, after school,what are you going to do? Go to college, or do this or do that? This is what I can do tohelp you, and this is what it’s like”. This is what it should be like.Primary social capital in the form of parental support and assistance wasnot the exclusive possession of those planning to continue to higher education. Inparticular, non-participants who actively planned to postpone entry into the post-secondary system were the most likely to stress the presence of parents as sourcesof primary social capital and of others as sources of secondary social capital.Support was expressed as unconditional encouragement in a passive sense ratherthan the proactive approach taken by parents of those planning to continue tohigher education.Thus far, dispositions toward and beliefs about post-secondary education,academic capital, parents as sources of social capital, counsellors, teachers, andfriends as sources of secondary social capital have been discussed largely asindependent of one another. However, as students comments have revealed,these constructs are closely connected with each other. In the foregoingdiscussion, for instance, it was not possible to engage in a discussion of the role ofcultural capital on educational choice without considering it in relation to theformulation of dispositions and beliefs and to the role of social capital. In otherwords, vivification of each construct in the model is revealed through itsinterrelations with other constructs.One way of illuminating how some or all of the constructs in Figure 23(Chapter 8) operate in an harmonious or discordant fashion was to explore with297students their perceptions of the enabling or constraining forces whichcontributed to their choices regarding post-high school destinations.Enabling and Constraining Forces and Post-high School DestinationsFor the majority of those planning to continue to higher education,enabling forces included moderate to high levels of primary social capital,cultural capital, academic capital, and economic capital, accompanied by strongpositive beliefs about and dispositions toward post-secondary education.Claire: My grades and knowing that I have money to go and people who., that I havesupport.Kirsten: Basically just wanting to further. . . to go further than high school. I don’t know.Like my sister again but I don’t know. I’ve always just gone through life thinking that’swhat I want - to go further than graduation.Victor: Yeah, my parents. They’re helping me. They help me study, they use lessons tohelp me. They want me to study as much as I can.For others, a high level of academic capital superseded an overall low volume ofcultural, social, and/or economic capital.Mike: Mostly what other people have told me, like what I’ve heard about the places andwell actually that’s just about all of it and the fact that I’ve been doing well in schooltoo. I’m sure if I’d been getting bad grades I’d be a lot more discouraged. Probablywouldn’t even apply for university or consider it.For some students with a low volume of academic and economic capital, butstrong primary social capital in the form of parental encouragement and thedisposition to continue to higher education, virtue was made out of necessity(Bourdieu, 1977b).Hal: I guess just the fact that I can’t expect to have everything all at once. I can’t expect tograduate and be accepted into the school of technology, graduate and then again rightaway be making money. . . . Waiting a year in between there I don’t really think it will298affect my plans. It might just take longer but I think the same outcome would beachieved. . . . I just learned to have patience I guess that’s what helped me make mydecision.In the urban/rural sample of students another force, perceived as enabling,emerged. For the large majority of students in the urban/rural sample, theexistence in the community of a “structured structure” in the form of a satellitebranch of a community college acted as a structuring structure which served toeliminate all other alternatives from the “field of the possibles”. Dispositionstoward higher education were formulated in light of this structure, accumulationof economic and academic capital and the nature of social capital available wereinfluenced by its presence. Hence, all decisions were “structured” by thisstructure.Patti: Like I couldn’t just go straight off to university ‘cause I don’t have any money in thebank ‘cause I haven’t been able to work during the school. . . . that’s never really been anoption, like if I just went straight to university. . . ? I think if I got a big scholarship thathelped pay and, you know, brought that opportunity but it hasn’t really been apossibility.. . . Just ‘cause it’s kind of it was set out [by my parents] that we should go tocollege first and then go to university just kind of work our way into it. . . . Yeah. But alsoI don’t want to go to university first year anyways. Just ‘cause it’s so big and a it’s a bigstep out of high school.Lisa: I think that it’s always been assumed all along and my brother, he went to a year toa college and then transferred to university. . . . so I’m just pretty well following thesame plan - a year or two at college and then going on to university, but that’s just the wayit’s been and that’s the way we want to keep it.Bourdieu (1977b) argues that when dispositions are durably instilled by objectiveconditions they generate aspirations and practices which are objectivelycompatible with those objective requirements. For these students, aspirations andintended practices were admittedly structured by the presence of the communitycollege. Whereas university attendance for many was not impossible (given theirgrade point averages and curricular stream), it was excluded from their repertoireof choices. As Bourdieu (1990b) explains, being the product of a particular class ofobjective regularities, the habitus of these students:299tends to generate all the ‘reasonable’, ‘common-sense’, behaviours (and only these) whichare possible within the limits of these regularities, and which are likely to be positivelysanctioned because they are objectively adjusted to the logic characteristic of a particularfield, whose objective future they anticipate. At the same time, ‘without violence, art orargument’, it tends to exclude all ‘extravagances’ (‘not for the likes of us’), that is, all thebehaviours that would be negatively sanctioned because they are incompatible with theobjective conditions. (p.56)Because of the presence of this institution, the transition for the urban/ruralstudents took on quite a different meaning than it did for the remote ormetropolitan sample of students. Commencing post-secondary education at auniversity -- which would require the individual to leave the community -- wasperceived as far too large a transition. It was much more “sensible” to begin post-secondary studies at the local college.Larry: Well, you know it just gives me a place to start. It gives me a place to get my ownfeet wet, type thing. You know it’s simpler living here. Like, I can walk to college I livethat close. And money, and all those options, you know, and starting off slowly, I - ratherthan just getting thrown in to the university situation. It seems so much more practicalfor me with money and everything, and location. . . . If I went into university I’dprobably be forced into making decisions on what I wanted to do right away, and youknow, fear that I’d make the wrong decision and being stuck with it.Sally: University in first year though seems to be so scary to go from like a little school tolike a whole campus. Yeah, whether, you know, going from school to college is a stepand then going to university.In turn, students constructed their lives in such a way as to reinforce thesealready durably instilled dispositions.Troy: I can stay here and keep my job here and secure my money base before I startgoing off to paying university rates and rent and everything and I’ve got a, like, plans tostay here, so it won’t really cost me very much, so I can go to school and get some moneyfor when I go to university.Almost all of those in the urban/rural sample who intended to attend the localcommunity college were enrolled in academic programs in high school. However,in some instances, academic capital in terms of courses selected and grade pointaverages earned, was influenced by the presence of the college.300Carla: My grades this term are really low. I think if you’re, I don’t know if it’s true, but ifyou go from [high school] to the college, and then college to university your gradeaverage can be lower, but if you go straight from high school to university your gradeshave to be higher. Like A’s and B’s, but you can probably get in on a C+ and stuff, lowerfrom college. So, that’s why I was thinking I’d just go and take a year there and then seehow my grades are.A year of community college attendance was also perceived as a year ofexploration -- a testing ground -- rather than a year toward degree completion.Larry: The money, like money is a factor, really, you know - if you waste a year atuniversity it’s also all that money, and college, you know, it’s only, it’s not such a moneything, it’s just the time. I wouldn’t care so much going one year extra, one year ofuniversity extra because I went to college here - like 5 years instead of 4, whatever,because I started at college and not university. That doesn’t really bother me.Admission and selection policies at the local community college potentiallyexacerbated lower achievement in high school. By the May interview, all of thosewho applied had already received letters of acceptance. According to students,admission was conditional only upon high school graduation. Grades, theyasserted, were relatively unimportant because “everybody gets in”.Commencing studies at the local college was also perceived byurban/rural students as an opportunity to improve their high school academicrecords before they attempted to tackle the rigours of university.Lisa: I know definitely I wouldn’t get accepted right away [at a university] because I’mnot pulling off straight A’s and I know when they look at their applicants anything lowerthan an A you get a mark against you, so hopefully it’s what I want to go into the collegefor, to improve my standings.Students held inflated perceptions of university standards, and these perceptionsserved to reinforce the notion that their “decision” to attend the local college wasthe “right decision”. Commencing at the local college would afford them theopportunity to “upgrade” their marks. However, those most limited in terms ofacademic capital -- that is, those without the prerequisites to attend university301and low grade point averages -- were not more likely to attend the localcommunity college.The decision to attend the local satellite of the community college wasstructured over the long term by money saved, curricular decisions made,dispositions instilled, and nature of information provided by both primary andsecondary sources of social capital. Students were constrained by structureswhich they perceived and, as Troy’s remarks illustrate, these structures were self-determined (Robbins, 1991).Troy: I think I’d probably be more comfortable if I went to just like college and the wholething is probably, is a little bit like frightening, like because you’re out of the old safesecondary school with grades and teachers and break and lunch and everything andlike I know [this town] really well and I know my way around and everything, and Ithink I’d feel safer going into a new environment that is potentially, you know, sort offrightening, like unsure, and be able to come home to a place that I’m safe in. You know,so I can not wonder, rent rent rent’ or something. Just good, I’ve come home and can sitdown and relax for awhile, you know, and just the whole atmosphere of being in [thistown] and like going to the college here. It would just make it a lot easier, and once I’mused to the whole bustle of people and the different schedules and everything, then I’ll beready to say “university ho!!” and off I go.Whereas the transition from high school to university was “practically”anticipated by those intending to begin studies at the college, problems inherent inthe transfer from community college to university, as outlined by Dougherty(1987), were not acknowledged. Knowledge about attrition during the first twoyears of community college attendance, difficulty in the transfer process (related tothe need to move to a new institution, and difficulty in gaining admission touniversities, transferability of credits, and obtaining financial aid), attrition aftertransfer (associated with declines in grades, lack of financial aid, and the difficultyof social integration into the new institution) were not expressed. The very lowincidence of successful degree completion by community college transfer studentsin British Columbia (Ministry of Advanced Education and Job Training, 1987) wasnot mentioned. Nor were limited program and course offerings at the community302college (which incidentally enrolled fewer students than did the secondary schoolattended by these students) considered problematic.In contrast, in the remote sample, students indicated that participation inany type of post-secondary education required the individual to leave thecommunity. Thus, a completely different set of dispositions regarding choice ofinstitution were in place. In all but one case, those with the academic capital toattend university did so.Carol: Here university is seen as the place where you should go and colleges are if youdon’t get into university. . . . Colleges are said to say that you can get your first year ofuniversity and transfer into a university after that. And you know that you can do, youdo the same work, the same thing is being taught and you’ll just do fine, university afteryou go to college, but still people see you as if you go to a college instead of a universitythat you just weren’t, you just couldn’t make it in a university, you just couldn’t get intoone, or you, they just don’t seem to be the same.Elaine: I just wouldn’t think that the education [at a college] would be at the same level,but I don’t know that, it’s just from my understanding.. . . because anyone that I knowthat is intelligent goes to a university first. I have never met anybody that goes to acollege because they want to. It’s usually because they have to. But I don’t know that for afact.For the remote students who intended to continue to post-secondary education,lack of a community college was not perceived as a barrier. Choices werestructured, over the long term, to accommodate the move to Vancouver orVictoria. Advice given, grades strived for, money required, and positivedispositions and attitudes such as “getting out of this town” “leaving my parents”“living in the city” and “being on my own” reinforced the move away from thenorth.Those planning on continuing to post-secondary education eagerlydescribed the forces enabling them to pursue the next stage in their lives. Incontrast, those who did not plan to continue were noticeably reticent. When askedwhat was facilitating their plans for life after high school, those “never” intending303to participate in post-secondary education asserted that nothing that was enablingthem to work or to post-secondary -- simply “nothing”. The need to take a breakfrom school was also cited as an enabling force.Matt: I just wanna take a break. I dont want to take another two month break and thengo back to school. I want to, just want to stay out of school for a while. Twelve years of it,I’ve had enough. I need a break I think.In comparison, while those “naturally” disposed toward post-secondaryeducation may have also wanted a break, their “better judgment” led to carry outtheir original plans.Janice: It would be ideal to travel next year.. . . but, I don’t know - it just would seem notvery good to go off hopping in Europe while your parents are trying to scrimp and saveto put you - for you to go to university. It seems not too, it doesn’t connect. I can travellater.Short of an unexpected disaster, there was little in the way of perceivedconstraints for those with “everything in place” to attend post-secondary, and thistended to be consistent across geographic regions. When I attempted to determinethe constraints they confronted, student after student with plans to participate inpost-secondary education turned my question around and cited enabling factors -enabling factors that in many cases required years to establish. Grades and thepost-secondary selection and admission process were the only wild cards.Urban/rural students:Paffi: No. No. ‘Cause my grades are up and like I don’t have any fear right now of failing,you know, like failing Grade 12, so, no, and parents - no, friends - no. No. For sure I’mgoing to go to college.Lisa: I can’t see any problems money-wise, it’s set, ‘cause I have my funds that Mommyand Daddy have been saving away for a long time and I have my own money that willhelp out, and I don’t see anything that could get in the way.304Metropolitan students:Claire: Urn, not unless I die. Or my parents die or my sister dies. But its the truth. But no.Unless I don’t get in. . . . No [money’s not a problem]. My parents already have it allfigured out.Victor: Other than marks? No. Not much. Well, if my parents moved or something, I’dprobably go somewhere else. . . Money? No. ‘Cause my parents say, if you can make itinto a good university they’ll support me.Remote students:Susan: Not really. It’s pretty well, it’s pretty well set out. Like my parents are going tohelp me basically no matter what so. I don’t really think there is. And if I don’t get intothe University of Victoria I’ll just go to college for the first year or so maybe, bring up mymarks a bit. Like whatever it takes to get in [to university].Tina: No, not as of now. Nothing. My grades have kept up. .. . For the last few years...I’ve put money into bonds and then my dad’s just met whatever, like if I put $500 thenhe’ll put $500 in as well, we’ll just put that in and it just collects interest for the year andthen for the next year I put however much money I made for that year and he matches it.So he’s just paying for half my tuition and financially I’m fine - I have plenty.While strong academic capital was cited as an enabling force for somestudents, it was not enough to counteract the lack of economic capital. ForMarcus, Saphia, and Mike, all with grade point averages greater than 3.00,academic capital without economic capital posed a real constraint.Marcus: Money. Money’s always the problem. I want to be a full-time student. I’ll applyfor scholarships, but in year 3 and 4 if they run out, money will be a problem.. . .Yes, I’llhave to [apply for loans]. But I’m kind of allergic to loans. I’d rather not have one.Saphia: It seems, well, it just costs so much. Not so much tuition but living expenses. Still,wherever I go, and, it’s - I’ll be able to get the grades.Mike: The cost of the university will be hard to manage.While Mike and Marcus found the means to attend university, the lack ofeconomic capital proved to be an impenetrable barrier for Saphia. The Octoberfollowing high school graduation, she was employed full-time at the Zellers storein her community. She hoped to save enough money to attend a communitycollege the following year.305Lack of economic capital was not the only constraint encountered. Anabundance of cultural and social capital, and firmly entrenched dispositionstoward and beliefs about post-secondary education did not compensate for thelack of academic capital. For Elaine, this lack was devastating:Elaine: Well I just never thought I’d have a problem getting into a university and I neverwanted to go to a college just because of, not the education part but just because thesocial part, but now I think that might be what I have to do. . . because of how mygrades have been this year and because of how I found school really hard and I just feel Ineed a break and urn, I don’t know, I just don’t really want to go and the fact that I can’treally. . . . it would be tough getting in, which I never thought would be a problem.So disposed was she toward university attendance that, despite the slim chance ofbeing accepted, Elaine applied to all of the universities and resisted the inevitable- facing the prospect of attending a community college.Elaine: I’m going to have to start applying to colleges ‘cause at the time when we filledout applications I didn’t want to go to a college but now I might have to.... [My parentsiare pretty upset. You know, they both graduated from university and my brother andsister are geniuses- I wonder what happened. They’re really upset about it. Yeah. Itreally - it’s hard with the teachers all know everyone. They always say “Well, why aren’tyou like your brother and sister?” and they have all their big lists on the wall that say alltime highs and “well, look your sister’s in university there, you’re failing’.For those not planning to attend post-secondary institutions, constraintsregarding post-high school destination were perceived somewhat differently.Some voiced constraints in relation to post-secondary attendance.Matt: Probably because I don’t have the money. If I had the money I might go to school,but its tough because I don’t have money its kinda tough to tell.Faith: Urn, just not finding what I want right away. It could take awhile. But I’m not in ahurry. I’ve got the rest of my life.Others voiced their community and the lack of employment opportunities asconstraining.Karen: This town is holding me back is what it is. There’s nothing in this town. Like youcan’t start a career here. Well I can’t anyways, maybe other people can. I just can’t seemyself living here in this town forever.306Yet others blamed themselves for not continuing to post-secondary education.Not pursuing what was expected was self-diagnosed as a personal weakness ofwill.Sara: I think the only thing that will get in my way is myself. Get in the way of going tocollege is me, ‘cause my Mom and Dad really want me to go. . . Money-wise they woulddefinitely pay for it ‘cause they want me to go so bad. That’s not a problem. It’d just beme, if I decide I’m not going and break their hearts. . . . Well, I’ve always done whatthey’ve wanted me to do, with the exception of a few things and I don’t think it’s toomuch to ask to say “go try”, you know, when they’re going to support me and the wholebit.Those postponing entrance into the post-secondary system expressed optimism.The delay was temporary and “nothing that I couldn’t overcome”.It is clear that enabling forces extended far beyond what was included inthe model presented in Figure 24 (Chapter 8). Enabling forces were described byinterviewees as the culmination of the various forms of capital relevant to the fieldof secondary and post-secondary education, transition, and choice. That is,enabling capital was comprised of academic capital in terms of grade pointaverage and curricular stream, primary social capital in the form of parentaldirection and encouragement, economic capital consisting primarily of parentalfinancal assistance, and depending on the geographic region, the presence of apost-secondary institution. As well, positive dispositions toward post-secondaryeducation and beliefs about its benefits fostered the accumulation of requiredcapital.Those who “never” planned to continue to post-secondary education wereconstrained more by the absence or limited perceptions of enabling forces ratherthan the presence of overwhelming constraining forces preventing postsecondary participation.307Perceptions of interrelationships among beliefs about and dispositionstoward post-secondary education, sources of cultural capital, primary, social, andacademic capital by Grade 12 students have been elucidated to help explain howthe processes of educational choice are created and reproduced. However, inChapter 3 it was pointed out that students decisions about post-high schooldestinations are often assumed and expected by researchers, educators, and policymakers to be “rational’1 decisions. Do individuals perceive that they have maderational decisions regarding their planned post-high school destinations?Rational Choice and Post-high School DestinationsThe students who participated in these interviews were asked simply“Have you made a rational choice regarding your plans for next year?”, “Why is(or isn’t) it a rational choice?” and “What does the word “rational” mean to you?”.Interestingly, almost all students, regardless of their planned post-high schooldestinations, asserted “yes” -- that they had, in fact, made a rational decisionregarding their futures. Why was this decision rational?Rationality, for these high school students, took on a variety of meanings.Some students explained that their plans were rational because they were desired:Vivian: Yeah. Because it’s what I want to do.For other students, their planned actions were deemed rational according to aperceived normative component.Clive: You have to go to university these days if you want to go anywhere. And so I feelI’m making a rational decision.Others described their plans as rational because it was the natural route to follow.308Claire: Because it’s something I’ve never really considered not doing. It’s what I’vealways considered doing.Yet for others, because their plans were realistic they were also rational.Victor: Because I’m not making some - that’s unreachable, right. It’s not somethingbeyond my ability but it’s not like low, something that’s too easy for me either.Parental influence also was attributed to the rationality of one’s plans.Jasmine: It’s all kind of centred around my parents. . . . what mostly counts is how I, likewhat I want to do next year, but I think the heavy influence is like my parents. So, acompromise between me and my parents would be rational for me.For some, the decision was rational because it was pragmatic.Carla: Because, just ‘cause, of the money. And ‘cause I won’t have to be out living on myown, supporting myself.Plans were also deemed rational if they were anticipated.Toni: Urn, well because I’ve thought about it and I’ve thought about my future and how itwill affect it. Like the courses I choose will all be university transferables and I thinkthat’s rational.Having afisture plan constituted rational action for a few students.Lisa: Well, I have a set plan. . . . its not something totally off the wall that might nothappen. If I put my mind to it, it can happen and its not that hard to grasp. So I thinkthat’s rather rational.Finally, plans following high school were viewed as rational because they were ameans ofexploration.Kirsten: I just guess the- it will lead to me to what I want to do. Well hopefully I’ll figureout what I want to be by going away.What was deemed to be desirable, realistic, pragmatic, normative, oranticipated was not determined simply by acting on desires, given certain beliefs,and based on the evidence. That is not to say that beliefs, desires, and evidencedid not play a role in decisions. However, when describing why their decisionswere rational, students grounded their responses in relation to the long-term,309deeply instilled dispositions that they held toward post-secondary education. AsTroy’s and Paths comments illustrate (below), post-high school plans were notjust a choice of what one can do. Rather, what one can do, and will do, was theresult of long term structuring processes that facilitated a given action.Troy: Rational is sitting down and thinking about things. Like well I actually shouldn’tsay that because I didn’t really make a conscious decision to go to college I just, like Isaid, it was just where I was going to go. It was understood, but like if I was sitting herenow and didn’t know what I was going to do then I’d want to just sit down and go “okaywhat are my choices?”.Notions of rationality were structured by embodied history in the form of longterm dispositions, which were in turn structured by objectified history. In Path’scase, the financal assistance available (and made available), attitudes toward thetransition to university from high school, parental expectations, and the presencein the community of a satellite community college, led her to conclude that, ofcourse, her choice was rational.Patti: Well I think it’s more rational than if I went right to university just for all thereasons that it will be cheaper, it’s not such a big step yet it’s a step and uh, it’s sort ofbuilding up and I’ll be more ready for university. I can pick up my grades a little moreand financially like it wouldn’t be smart of me because where would I get the moneyto go off to a big university right now? And I don’t want my parents paying for it all.Students were also asked whether a technical account of rationality playeda role in their decisions regarding post-high school destinations. When askedwhether they calculated the cost of post-secondary attendance and and comparedit with foregone earnings and whether they anticipated the salary differencesbetween level of education attained and earnings, for most students the answerwas “no”. Limited knowledge of salaries in relation to careers and their ownunclear career directions precluded this type of approach to decision making.Susan: I’m still not really aware of what careers offer, what rewards, so I’m still trying tofind out. So that’s partly why I haven’t really made any concrete decisions as far as thatgoes.310For others, the notion of expected rate of return on investment was completelyirrelevant.Janice: No. No I haven’t done that. It wouldn’t matter what the results were really. Pd stillwant to be in university. [Why?] ‘Cause I don’t want to work.Expected lifestyles, however, were based on what had been experienced up untilthis point in their lifes. Those who described their backgrounds as “middle class”“well off” or “white picket fence sort of thing” intended to maintain or reproducethis lifestyle, and hopefully enhance it.Clive: I want to be better than my parents. That’s what I’m basing myself on. My Dad, hewent to university, he makes a good living now, has a nice house, nice cars and I look atthat as being if you go to university then you can get those things. You can achieve thosethings and that’s what I base my future on. I want to be like my Dad or better.It is difficult to disagree with Bourdieu (1990b) that in the case of decisionsregarding post-high school destinations, “the habitus makes questions of intentionsuperfluous, not only in the production but also in the deciphering of practicesand works” (p.58). He maintains that the conditions under which rationalcalculations could take place very rarely exist in real life decision makingsituations. Yet, “agents do do, much more often than if they were behavingrandomly, ‘the only thing to do” (Bourdieu, 1990a, p.11).Bourdieu suggests that rather than following the prescriptions of rationaldecision making, individuals instead follow the intuitions of a ‘logic of practice’.This logic of practice is the product of an enduring exposure to conditions notunlike those which individuals are born into. In these conditions, individuals“anticipate the necessary immanent in the way of the world” (Bourdieu, 1990a,p.11). The art of estimating and seizing the “potential opportunities” that aretheoretically available to everybody requires the possession of the necessarycapital and dispositions related to a given field.311DiscussionThe Grade 12 students who participated in the two sets of interviews inOctober 1989 and May 1990 occupied a unique position in the social space.Although fully incorporated in the practices, routines, and rules of the secondaryschool system within the educational field, the time had arrived for them to beginto separate from this familiar world. This transition point is one of a very few inlife’s way that is both predictable and involuntary.The predictable nature of the transition from high school permits certainstrategies to be undertaken, over the long term, to prepare for adult life. Asstudents vividly described, dispositions toward post-secondary aftendance wereinstilled by family and reinforced in school. These dispositions, or habitus,according to Bourdieu (1990) are the embodiment of the social game in questionas a ‘feel for the game” that occurs in childhood. He asserts that “nothing issimultaneously freer and more constrained than the action of a good player”(p.63). Those planning to continue to post-secondary education, by doing whatthe game required, were indeed good players. Curricular choices made and gradepoint averages earned led to the next step in life, a step that had been envisionedfor years and one that opened the way to the future.Those who lacked a “feel” for the post-secondary game were left notknowing how to play it or even that they had a place in the game. Yet, theyappeared well aware of the consequences. They held few pretenses about the lifethat awaited them. Limited job opportunities, monotonous work, and bleakfutures were anticipated. Escalating credentialism would continue to limit theirfutures. The group of students who “never” planned to continue to postsecondary education recognized the importance of further education; however,without positive dispositions toward post-secondary participation, they were312unable to translate their beliefs into action. As such, their dispositions obfuscatedthe ability to recognize the chances offered to them through the non-universitysystem. The most disadvantaged -- because of limited cultural, social, andacademic capital -- maintained that their curricular decisions were the “right”choices. Minimal anger was expressed nor was a sense of injustice perceived.Of all of Bourdieu’s work, the concept of cultural capital has received themost attention. In this study, however, the concept of social capital plays anequally and perhaps more important explanatory role. Students highlighted therole of parents as sources of social capital. Mothers, in particular, createdinformation channels which facilitated decision making and minimized thereliance of school personnel as sources of social capital. Discourse in the homefostered information seeking behaviour of students.Did students make rational decisions about their futures? According to thetenets of practical rationality as espoused by Elster, it could be argued that somestudents did make rational decisions based on the what they desired, given thebeliefs they held and based on the evidence that was available. For others,inconsistency among desires, beliefs, evidence, and action could lead to theconclusion that decisions regarding post-high school destinations did not meetthe requirements of rational action. But what does this tell us? It is far moreenlightening, through the use of concepts of habitus, cultural, social, andacademic capital, to uncover why certain beliefs are held, how desires (ordispositions are formed), and how evidence is amassed, and hence what action istaken.In Chapter 3, I stated that admission to the system of post-secondaryeducation is dependent only upon the possession of academic capital in the formof academic achievement and, in some cases, curricular differentiation. Therequirements of participation, however, are more extensive. At minimum,313participation depends on the acquisition of three forms of capital -- academic(grades and appropriate prerequisites), economic (tuition and living costs), andsocial (information necessary to actuate plans). A final requirement of post-secondary education is the disposition (habitus) to attend. How these forms ofcapital are acquired and how dispositions are developed has been the purpose ofthis chapter.SummaryIn this chapter, two sets of interviews with Grade 12 students who were inthe process of making decisions about post-high school destinations wereanalysed. In Chapter 10, these findings, along with those of Chapter 7 and 8 areconsidered together to address the original purpose of this study -- to explicatehow and why individuals choose various post-high school destinations.Chapter 10CONCLUSIONS AND DISCUSSIONInterest in post-secondary participation has been a recurring theme insuch fields of inquiry as history, sociology, counselling, economics, and publicpolicy. An array of theories, perspectives, and models including human capital,status attainment, and equality of opportunity have been used to address whoattends post-secondary institutions and why. Post-secondary participation andits consequences have also been linked to issues of global competitiveness andeconomic prosperity. Two recent policy documents released by the Canadianfederal government and initiatives by several provincial governments in relationto human resource development continue to emphasize the importance of aneducated and skilled work force as the “key to prosperity, competitiveness, goodjobs, and quality of life” (Learning Well. . . Living Well, 1991, p.1-3).This study investigated how and why students in their final year of highschool and recent high school graduates chose various post-high schooldestinations. Theoretical frameworks based on Härnqvist’s (1978)conceptualization of the determinants of educational choice, rational choicetheory as depicted by Elster (1986; 1989a, 1989b), and Bourdieus Theory ofPractice 1977c, 1979, 1986, 1990b) were used to examine 1) the complex ofindividual and institutional influences of educational choice, 2) the processesunderlying the decisions people made in choosing whether or not to pursue apost-secondary education, and 3) how students in the midst of the transitionfrom high school to various post-high school destinations perceived theseprocesses.314315This research, conducted in British Columbia, has undertaken two kinds ofexamination: 1) the exploration of choices made by a large sample of recent highschool graduates, as reported on a survey questionnaire and enriched bycorresponding Ministry of Education linked data and 2) two sets of intensive,focused interviews conducted with a sample of Grade 12 students who were inthe process of making choices about post-high school destinations. Hence,through theoretical and methodological triangulation I have been able to capturethe choices, and processes behind these choices, of a range of participants, non-participants, and potential participants in the post-secondary system.Three different types of analyses were undertaken to explore the choiceprocess. First, discriminant function analyses were carried out to determinewhich individual and institutional determinants of educational choice, asdepicted by Härnqvist, best predicted post-high school group membership (nonparticipant, non-university participant, university participant) of a sample ofBritish Columbia 1988 high school graduates. Second, structural equationmodelling using LISREL VI was employed to unravel the processes, as depictedin a theoretical model of Post-high School Status, that led to differential groupmembership. Finally, interviews with Grade 12 students were conducted toexplore students perceptions of these processes. In the following section, thefindings central to each analysis are summarized.Central Findings of the StudyIn the discrirninant function analyses reported in Chapter 7, it wasdemonstrated, using variables specified in a framework of the determinants ofeducational choice as advanced by Harnqvist, that post-high school group316membership could be reliably predicted. Curricular differentiation in the form ofpossession of the requirements for university entrance was the most powerfulpredictor of whether or not one participated in any form of post-secondaryeducation. This predictor was followed in importance by level of educationexpected, total number of academic awards received, and primary social capitalor parental influence variables. Parental background or cultural capital variables,beliefs held about post-secondary education, and distance from the nearestcommunity college centre and university were not useful predictors of whetherone attended some post-secondary institution following high school. Based onthe variables included in Härnqvist’s framework, 74% of non-participants and79% of participants could be correctly sorted into their respective groups.In a second discriminant analysis with non-university and universityparticipants as the grouping variable, high school grade point average moststrongly differentiated non-university participants from university participants.To a lesser extent, curricular differentiation and level of education expectedpredicted group membership. Distance from the nearest university, fatherseducation, and percentage of students graduating with honours in the schooldistrict also contributed to the prediction of group membership. However,neither primary nor secondary social capital variables had an impact on type ofinstitution attended. Based on the same set of predictors as in the first analysis,the type of post-secondary institution attended was correctly predicted for 81%of university participants and 75% of non-university participants.In a three group analysis (non-participant, non-university, university), thefirst discrirninant function distinguished participants from non-participants onacademic achievement or academic capital variables, disposition variables (levelof education expected and wanted), and parents as sources of cultural capital.The second discrirninant function demonstrated that, for both non-university317and university participants, the influence of others in the form of primary andsecondary social capital and the number of academic awards received washigher than for non-participants. As well, non-participants and universityparticipants differed from non-university participants in the following ways.Non-participants and university participants lived slightly farther from thenearest community college and held less strong beliefs that post-secondaryeducation was necessary to prepare them for a job than did non-universityparticipants. The strength of these latter two variables as predictors, however,was minimal. Based on the same 20 predictors employed in the previous twoanalyses, 81% of university participants, 50% of non-university participants, and67% of non-participants could be correctly classified into their actual post-highschool groups. Of the non-university participants, 26% were incorrectlyclassified as non-participants, and 25% were misclassified as universityparticipants. Of the non-participants, 23% were misclassified as non-universityparticipants, and 11% were misclassified as university participants. Of theuniversity participants, 17% were misclassified as non-university participants,and only 3% were misclassified as non-participants.The results of the discriminant function analysis lent support for a secondtype of investigation. After determining how non-participants, non-universityparticipants, and university participants differed on a set of individual andinstitutional determinants of educational choice, the second question in thisstudy sought to reveal the processes underlying the decisions that people madein choosing whether and where to pursue a post-secondary education.A theoretical model of Post-high School Status was tested in Chapter 8.This hypothesized model sought to determine the extent to which rational choicetheory, in concert with Bourdieus Theory of Practice, explained the post-highschool status of Grade 12 graduates. By employing structural equation modelling318with LISREL VI, causal relationships among cultural capital, primary andsecondary social capital, beliefs about and dispositions toward post-secondaryeducation, academic capital, enabling capital, and post-high school status weredemonstrated. In these analyses, 58% of the variance in post-high schooldestination for the male sample and 54% of the variance for the female samplewas explained.The paths identified in the model predicted the direct effects of one latentconstruct on another. Also, of interest were the indirect effects of the twoexogenous latent constructs which indicated the degree to which parents assources of cultural and social capital influenced the post-high school status oftheir children. Not all hypothesized paths in the model were realized. In thefollowing section, each hypothesis is addressed separately.Hypothesis One: The first hypothesis predicted that two exogenous variables,sources of cultural capital, and sources of primary social capital, and one endogenousvariable, sources of secondary social capital, would have positive effects on beliefsabout post-secondary education.While the effect of sources ofcultural capital was significant and positive formales and females, this effect was very modest. The effect of sources of primarysocial capital was not significant for males or females. The effect of sources ofsecondary social capital was positive and moderate for both males and females.Hypothesis Two. It was hypothesized that one exogenous variable, sources ofcultural capital, and two endogenous variables, beliefs about post-secondaryeducation and dispositions toward post-secondary education, would have positiveeffects on academic capital.319The effect of sources of cultural capital on academic capital was nonsignificant for females and only weakly positive for males. The effect of beliefsabout post-secondary education was non-significant for males, and significant butnegative and weak for females. The effect of dispositions toward post-secondaryeducation on academic capital was very strong and positive. In the femaleanalysis, this path was the strongest in the model.Hypothesis Three. It was hypothesized that the two exogenous variables --sources of cultural capital and sources ofprimary social capital --would have positiveeffects on sources ofsecondary capital.The effect of sources of cultural capital was non-significant for males andsignificant and negative for females. The effect of sources of primary social capitalwas positive and very strong for both males and females.Hypothesis Four. The two exogenous variables -- sources of cultural capital andsources of primary capital -- and two endogenous variables, sources of secondarysocial capital and beliefs about post-secondary education were hypothesized to havepositive effects on dispositions toward post-secondary education. Also, academiccapital was predicted to positively affect dispositions toward post-secondaryeducation, resulting in a non-recursive or reciprocal path between these twovariables.The effect of sources of cultural capital was positive and moderate for bothmales and females. The effect of sources of primary social capital and academiccapital was not significant for either males or females. Thus, the claim that a nonrecursive path exists was not demonstrated. Positive effects of sources of secondarysocial capital and beliefs about post-secondary education on dispositions toward postsecondary education were demonstrated for both males and females.320Hypothesis Five. Three endogenous variables, academic capital, sources ofsecondary social capital, and dispositions toward post-secondary education werepredicted to have positive effects on enabling capitaLFor both males and females, the effect of academic capital was positive andweak and the effect of dispositions toward post-secondary education was nonsignificant. However the effect of sources of secondary social capital was positiveand moderately strong for both males and females.Hypothesis Six. It was hypothesized that one exogenous variable, sources ofprimary social capital, and three endogenous variables including academic capital,dispositions toward post-secondary education, and enabling capital would havepositive effects on post-high school status. Furthermore, sources of cultural capitaland sources ofprimary social capital were predicted to have a strong indirect effecton post-high school status.The effects of sources of primary social capital, academic capital, dispositionstoward post-secondary education, and enabling capital all had positive effects on 05thigh school status. The magnitude of academic capital on post-high school status wasone of the strongest direct effects. For males, it was the strongest path in themodel.The indirect effects of the latent constructs on post-high school status werealso of interest. Indirect effects of sources of cultural capital and sources of primarysocial capital on post-high school status were demonstrated. The indirect effects ofsources of cultural capital were stronger for males, and the indirect effects ofsources ofprimary social capital were stronger for females.The force of these findings, and non-findings, are best discussed in thecontext of the theoretical frameworks employed. Did the constructs specific to321rational choice theory explain educational choice? That is, did individuals act ontheir beliefs and desires, in light of the available relevant evidence, as Elsterclaims? What did the concepts of cultural capital, social capital, dispositionstoward post-secondary education, as posited by Bourdieu, contribute to ourunderstanding of choice regarding post-high school destinations? Are thesetheories competing, or are individuals’ “rational’ choices framed by reproductiveforces transmitted through social and cultural capital?Clearly, a strong relationship between academic capital and post-high schoolstatus, as demonstrated in the LISREL analyses, exists. This suggests thatindividuals, did in fact, make rational decisions about post-high schooldestinations based on the amount of academic capital at hand. Also, asdemonstrated by the strong indirect effect of dispositions toward post-secondaryeducation on post-high sciwol status, the more disposed an individual was towardpost-secondary education, and the higher the academic capital in her or hispossession, the more likely she or he was to participate in post-secondaryeducation. The relationship among beliefs about post-secondary education,dispositions toward post-secondary education, academic capital, and post-high sciwolstatus, for both males and females, supports a rational choice thesis. Beliefs aboutpost-secondary education, however, was a weak construct in this model.Rational choice theory does not deny that constraints affect what and howdecisions are made. To use Simon’s (1957) term, rationality is “bounded” by theabilities of individuals as information processors and problem solvers. However,rather than accepting that, given certain constraints, individuals will act in arational manner, this study sought to explore how individuals occupying thesame social space came to hold different preferences and beliefs, and howevidence was amassed and utilized in the decision making process.322This was accomplished by enveloping the choice process in a frameworkof parental transmission of cultural and social capital. To the extent that sourcesof cultural and social capital did not influence one’s beliefs about anddispositions toward post-secondary education and the amount of educationalcapital in one’s possession, the tenets of rational choice theory could beconsidered necessary and sufficient for explaining choices about post-highschool destination.The models of Post-high School Status tested in Chapter 8 revealed that,in a sample of 1988 British Columbia Grade 12 graduates, parents as sources ofcultural and social capital did influence the post-high school destinations of theirchildren. The relationship between parents as sources of cultural capital and thedispositions of their children toward post-secondary education suggests thatparents from higher status backgrounds have been able to cultivate in theirchildren stronger dispositions toward post-secondary participation. In turn,these dispositions influenced whether academic capital, in the form of curricularprogram completed and grade point average earned, was invested in furthereducation.Parental transmission of social capital also influenced post-high schooldestinations. Relationships in the home that encouraged post-secondaryparticipation also resulted in the development of secondary social relationshipswith school personnel and friends. Social capital transmitted in primary socialrelationships and through secondary social relationships led to strong positivedispositions toward post-secondary participation and to the receipt of highernumbers of academic awards. It appears that a multiplex relationship amongparents, school personnel, and friends had a positive impact on post-high schoolstatus.323The model of Post-high School Status postulated in this study illustrateshow the intersecting fields of family relationships, families as sources of culturalcapital, and relationships with school personnel and peers influence the amountof academic capital in one’s possession. In turn, based on academic capital asevidence, and given one’s beliefs and dispositions, “rational” decisions regardingwhether and where to participate in post-secondary education were made.As reported in Chapter 9, the processes of educational choice were furtherexplored through interviews with Grade 12 students. While multivariateanalyses in the previous two chapters provided a detailed account of thedeterminants of post-high school status and the relationships among unobservedlatent constructs based on rational choice theory and Bourdieu’s Theory ofPractice, the third dimension of this study sought to establish how a sample ofstudents in their last year of high school perceived the transition process.Specifically, through the use of interviews, students’ perceptions of theinterrelationships among beliefs, dispositions, and cultural, social, academic, andenabling capital, and their effects on post-high school status, were explored.Several salient findings emerged from the interview data. First, the long-term, durable nature of dispositions toward post-secondary education wasreinforced by those intending to continue to post-secondary education, as well asby those planning not to participate. The decision to participate in post-secondary education was not simply a choice made at the end of high schoolbased on evidence including academic success, the ability to pay for furthereducation, and proximity to a post-secondary institution. Most of those planningto continue directly to higher education recounted that, because of parentalexpectations and long term strategies, post-secondary participation was alwayswithin their “field of the possibles”. The importance of primary social capital, inthe form of 1) creation of information channels (particularly by mothers), 2)324assistance with post-secondary selection and admission procedures (again,particularly by mothers), and 3) adequate provision of the economic capitalrequired to participate in post-secondary education (by parents), wasemphasized by interview participants as critical in enabling them to formulateplans to participate in post-secondary education. Those who claimed thatparents were strong sources of primary social capital were more likely todevelop multiplex relationships with school counsellors and other individualswho, together with parents, guided the way to post-secondary education.The beliefs that student interviewees held about post-secondary educationwere particularly revealing. Both those intending to participate and those withno intention of continuing to higher education claimed to recognize the benefitsof furthering one’s education beyond high school. However, despite theirawareness of evidence of grim employment prospects, low wages, unstimulatingwork, and the constant threat of unemployment, a certain group of students didnot view post-secondary participation as a viable alternative. Without the longterm influence of parental expectations, and without enabling mechanisms inplace, a “feel” for the post-secondary game was non-existent.For the majority of those planning to continue to post-secondaryeducation, enabling forces were in abundance. The right curricular choices hadbeen made, post-secondary selection and admission processes had been decodedby parents and/or school personnel, and these students’ beliefs about anddispositions toward post-secondary education served to reinforce, and in turnwere reinforced by the accumulation of cultural, social, academic, and economiccapital.Conversely, those who were the most disadvantaged in terms of cultural,social, and academic capital were the least likely to intend to participate, andultimately participate, in post-secondary education. Beliefs about and325dispositions toward post-secondary education, together with limited capital -- inthe form of low parental expectations, minimal support and assistance bysignificant others, and the absence or scarcity of the economic capital required toparticipate in further education-- served to prevent them not only fromembracing the opportunities offered to them through non-university institutions,but also from recognizing that these opportunities were available. Whereas theroute to the future was clearly signposted for those heading to the post-secondary sector, the route to the future for those not intending to participateremained obscure.Since the statistical analyses in this study were conducted by gender, andinterviews were conducted with both males and females, similarities anddifferences in the results merit comment. First, results of the discriminantanalyses concur with findings of other studies (Anderson, 1988; Rosenfeld &Hearn, 1982; Turrittin, Anisef, & MacKinnon, 1983) that examine genderdifferences in relation to post-secondary participation. Grade point average wasa more important determinant of post-secondary participation and type ofinstitution chosen for men than it was for women. For females, the level ofeducation expected, influence of social capital variables, and the number ofacademic awards received more strongly influenced the type of institutionattended than they did for men. The analyses using LISREL VI concurred withthe discriminant function analyses. Stronger relationships between academiccapital and post-high school status were demonstrated for men while therelationship between dispositions toward post-secondary education andacademic capital was stronger for women. The indirect effect of dispositionstoward post-secondary education on post-high school status, while strong forboth men and women, was stronger for women. As well, the indirect effect of326cultural capital on post-high school status was stronger for men and the indirecteffect of primary and secondary social capital was stronger for women.In the discrirninant analyses, the overall relationship between thepredictor variables and the dependent variables was stronger for males than itwas for females. The model of Post-high School Status, tested in Chapter 8, betterexplained the variance in post-high school status for males than it did forfemales.Consistent with the conclusions of other studies (Alexander & Eckland,1974; Anderson, 1988; Turrittin, Anisef, & MacKinnon, 1983), these resultsindicate that the ability of males to convert academic capital into post-secondaryattendance continues to be greater than it is for females. For females, signals inthe form of positive influencing forces of parents, school personnel, and friends,together with the positive influence of parental educational and occupationalbackgrounds on the formation of positive dispositions toward post-secondaryeducation, appear to be additional catalysts required to convert the academiccapital at hand into post-secondary participation.Interview data were not particularly enlightening regarding the genderdifferences revealed in the statistical analyses. That is, when asked similarquestions about post-high school plans, perceptions, and strategies, no glaringdifferences by gender were noted. It is important to emphasize, however, thatwomen in the interview sample who planned to pursue a post-secondaryeducation expected the same returns from their investments in education as didmen. They believed that post-secondary participation would improve their lifechances in terms of career opportunities, future earned income, the ability tocompete for good jobs, and general quality of life. Also, males as well as femalesstressed the importance of parents in their post-high school plans.327Significance of the ResearchA study is deemed to be significant if it contributes to or extends existingknowledge of a particular phenomenon. This study does so in several ways. Ingeneral, the theoretical frameworks adopted and developed for this study holdpotential in revitalizing the investigation of equality of opportunity at a time inour history when educators, policy makers, and economists strongly emphasizethe need to develop a learning society.First, Härnqvists framework of the determinants of educational choiceprovided a systematic, comprehensive way of examining the factors influencingeducational choice. When this framework is used in its entirety, as in this study,the usefulness of both individual and institutional variables specified in theframework as predictors of post-high school group membership can be assessed.Equally important in these analyses were those variables that were not usefulpredictors. For example, distance from the nearest community college centre andnearest university were not good predictors of post-secondary participation. Yet,major initiatives to increase post-secondary participation in British Columbiahave tended to focus on geographic expansion of the system.In this study, analyses were based on survey questionnaire data providedby a sample of Grade 12 graduates. In future studies, Härnqvist’s frameworkcould be used to identify, prior to high school departure, those students likely tocontinue or not continue to higher education.Second, a model of Post-high School Status was advanced. This modeland related analyses extend the theoretical and empirical work of others(Coleman, 1988, 1990; Gambetta, 1987; Hindess, 1988; Rehberg & Rosenbaum,1978) by treating two disparate strands of thinking -- rational choice theory andBourdieu’s Theory of Practice -- as complementary rather than competing.328Insights into the choices that individuals make about post-high schooldestinations, and the processes underlying these choices that extend beyondthose provided by analyses adopting a single approach, are provided by thismodel.Third, the inclusion of interview data allowed for a thorough examinationof the micro-processes of choice regarding post-high school destinations byindividuals who were in the process of leaving high school. Whereas thestatistical analyses in this study examined responses provided through thesystematic collection of data from a large sample of recent high school graduates,interviews with Grade 12 students were intended to provide a rich, detailedportrayal, in students’ own voices, of the process of transition and choiceregarding post-high school destination. Furthermore, interviews with Grade 12students highlighted how dispositions (habitus) toward and beliefs about post-secondary education were formulated; how cultural and social capital wastransmitted by parents and others; how enabling and constraining forcesinfluenced post-high school destinations; and how dispositions, beliefs, and theforms of capital relevant to post-secondary participation were interrelated.Through the examination of choices made by samples of British ColumbiaGrade 12 enrollees and graduates, and the employment of theoretical andmethodological triangulation, this study contributes to an understanding of thedecisions made by non-participants, as well as participants at university andnon-university institutions. Considerable insight into how early and distantprocesses and decisions constrain or extend one’s range of future choices, andtheir subsequent influence on rational choice processes, has been revealed inboth the qualitative and quantitative analyses. Of particular note were students’descriptions of the long term development of dispositions toward post-329secondary education and the processes of capital transmission, accumulation,and conversion into investments in post-secondary education.Implications for Future ResearchInclusion of both quantitative and qualitative analyses in this studyserved what Bourdieu refers to as a “process of reciprocal verification” (Robbins,1991, p.24). That is, “the intuitive interpretations of interviews will generatequestions which elicit formal statistical data, or the emergence of unintuitedpatterns from statistical data will lead to further elucidation and verification inconversations”(p.24). The interview data in this study have provided a wealth ofinformation from which to refine existing approaches and generate newquestions on survey questionnaires in future research on post-secondaryparticipation. Conversely, patterns demonstrated in statistical analyses (such asgender differences, the relationship between primary and secondary sources ofsocial capital) could serve as focal points in future qualitative analyses exploringdecision making processes of high school students.Informed by the findings of this study and the theoretical explorations asdescribed previously, an ameliorated model of Post-high School Status, depictedin Figure 26, could provide the basis for future investigations of the processes ofeducational choice. This model incorporates the findings of three types ofanalyses in this study, and as such, provides guiding questions for thedevelopment of survey instruments and direction for future qualitative analyses.Articulation of this model with that advanced by Tinto (1975a; 1987), togetherwith longitudinal data, may provide insights into retention, transfer, and degreecompletion.LabourMarketandtheEconomy_________Social andCulturalConditionsIPeichcounsellors[DegreetoIOfDoseFriendsassistedwithwhichcounsellorIContinuingtoflgIP1tinaridIadmissioninfo.FMother’sEducationFather’s HH’ LDegreetowhichaencouragesp.oplansDegreetow]fatherencossragesp&IptansSThqure26:Ameuiora.teJ!Uo64offPost-IiigII Sclwo(Status.03 03 C331Further investigation of the experiences of non-participants in post-secondary education is also warranted if “the competitive economy of the futurewill need the full contribution of as many skilled workers as possibl&’ (LearningWell. . .Living Well, 1991, p.111-6). Do non-participants perceptions of post-secondary participation change over time? Do work place demands oremployment limitations result in the eventual entry of non-participants into thepost-secondary system? What enabling and constraining forces do theyencounter as adults trying to enter the formal post-secondary system? Whatother avenues are utilized to develop skills and increase educational levels? Dothose who temporarily plan to leave the educational system following highschool eventually continue with their studies? A second follow-up study of theGrade 12 students interviewed in this study would provide answers to some ofthese questions. Analyses which link Bean and Metzner’s (1985) model of nontraditional college attrition with the model of Post-high School Status asconceptualized in this study may further extend our knowledge of adultparticipation and retention in formal post-secondary education.Rigorous investigations of all aspects of post-secondary education requirethe availability of longitudinal data sets and comprehensive banks of surveyitems that span a period of time from primary and secondary education tolabour force participation. As Hogkinson (1985) asserts, in order to anticipatefuture demands on the post-secondary system “we need to begin seeing theeducational system from the perspective of the people who move through it”(p.l). In Canada, there is a dearth of theoretically grounded, empirical studiesbased on national longitudinal data sets such as those found in the United States(e.g. studies based on data sets such as High School and Beyond (see Jones et al.,1982)). The establishment of such a data set in Canada would go a long way332toward enhancing our understanding of the progression of individuals throughthe educational system and into the work force.Implications for TheoryWhile the forms of capital and concepts of habitus and field specified inBourdieu’s writings provide a rich frame for analysis, studies using his workhave focused almost exclusively on the concept of cultural capital. Moreover, themeasurement of cultural capital in many studies has been quite limited.Typically, these studies have defined cultural capital as “status cultureparticipation” and used self-reports of involvement in art, music and literature asevidence of its existence (see DiMaggio,1982; DiMaggio & Mohr, 1985; Katsillis &Rubinson 1990).Lamont and Lareau (1988) questioned whether participation in highstatus culture constitutes an appropriate measure for North America. They arguethat high culture traditions in American society, in contrast with Europeansociety, are relatively weak. Lareau (1987) suggests that it would be useful tomove from studies of elites, and direct attention toward the cultural capital (andits value in relation to the dominant culture) of all social groups. She states:The concept of cultural capital may help by turning our attention to the structure ofopportunity and to the way in which individuals proceed through that structure.... Classprovides social and cultural resources, but these resources must be invested or activated tobecome a form of cultural capital. Analyzing the role of cultural capital in structuringfamily-school relationships, particularly parental participation in education, provides arich setting for analyzing the linkages between micro and macro levels of analysis.(Lareau,1987, p.84)This study has been one attempt at analysing how social and cultural resourcesare developed and structured within the family-school setting, and how theseresources are converted into post-secondary participation. However, this study333has gone beyond the recommendations of Lareau by attempting to incorporatethe concepts of cultural capital, social capital, dispositions or habitus, and fieldinto the analysis of choices regarding post-high school destinations. Explorationof these concepts, and in particular differences in dispositions toward and beliefsabout post-secondary education and the role of social capital in decision making,has been fruitful in enlightening our understanding of these choices.Bourdieu (1990b) asserts that when choices are cast in the framework ofhis Theory of Practice, the question of rational choice, or intention, is‘superfluous”. Critics of rational choice theory (Hindess, 1988; Levi, Cook,O’Brien, & Faye, 1990) argue that while rational choice theory provides atheoretically parsimonious explanation of action, in doing so it “clos[es] offimportant areas of intellectual inquiry concerning the forms of thoughtemployed by actors and the social conditions on which they depend” (Hindess,1988, p.8).Is rational choice theory of minimal use in our further understanding ofthe processes of educational choice? I agree with Hindess that when rationalchoice theory is treated as descriptive — that is, by presuming to describe howindividuals actually do act when making decisions regarding post-high schooldestinations -- it does obscure both the forms of deliberation undertaken by thedeciding individual and the relationship between social structure or socialrelations and actors and their actions. This study demonstrated the significanceof both in relation to choice.However, the use of rational choice theory as prescriptive or normative --as an analytical tool for optimizing decisions by prescribing how an individualshould act in a given circumstance -- would help to teach skills andcompetencies which would enable those with limited capital and negativedispositions toward post-secondary education to make more informed decisions.334Rational choice theory could be used, not simply to identify given constraints,but to transcend them. By making explicit the relationships between individuals’beliefs, desires, evidence and intended action, the obscure could be clarified andone’s vision of the “field of the possibles” could be extended. Mistaken beliefs,misinformation regarding evidence, preferences contrary to beliefs, evidence,and/or intended action could be addressed to improve the decision makingprocess. Elster’s model of rational choice provides one potentially useful methodfor empowering decision makers. Other approaches, such as Tversky’s (1972)“elimination by aspects” or Janis and Mann’s (1977) “conflict-theory model ofdecision making”, could be used to make constraints and enabling forces explicit.As Bourdieu and Passeron (1979) claim, even in the worst choice situation,adoption of the tenets of rational calculation should improve the choices madeby guiding individuals in how to shrewdly invest the capital at hand.Implications for Policy DevelopmentKarabel (1986) maintains that community colleges are dumping groundsfor the least advantaged students. This study demonstrates that the leastadvantaged-- in terms of cultural, social, and academic capital -- do not attendany type of post-secondary institution within one year of graduation from highschool. It appears that, while non-university institutions claim to provide analternate route for those who lack the requirements for university attendance,those who are the most disadvantaged are not participating in the postsecondary system. If “we can ill.. . ignore the potential of social consequences ofa generation of young people ill-equipped to face the challenges of the future”335(Prosperity through Competitiveness, 1991, p.8), the fate of these studentsshould be of central importance.According to the Report of the Provincial Access Committee (1988):Insofar as some groups are under-represented in the whole of, or in certain sectors of,advanced education and job training, deliberate strategies aimed at increasing theparticipation of such groups, at all levels of education, should be implemented. (p.11)While this report identifies a number of under-represented groups (see Chapter2, Table 3), the disadvantaged who graduate from high school each year -- thevery group according to Coleman and Husén (1985) who will comprise the “newunderclass” -- are not included. It appears that accessibility provided in a passivesense through open door policies is not enough to attract those with the least inthe way of academic, cultural, or social capital.Why don’t community colleges and other non-university institutionsattract the least advantaged students? What is their role in doing so? Hatton(1991), in a minority report of the Task Force on Entry-Level Training (Report ofthe CLMPC Task Forces on the Labour Force Development Strategy, 1990),argues that recognized public educational institutions rarely offer entry-levelprograms that are specifically targeted to disadvantaged groups. He contendsthat group-oriented rather than individual-oriented approaches to teaching andlearning, an emphasis on the acquisition of credentials rather than the “actualneeds of the individual”, together with individuals’ past failures in theeducational system account for the lack of success of community colleges inmeeting the needs of the disadvantaged.As some community colleges change from that of multi-purpose nondegree granting institutions to university-colleges, the effects of these changes onthe participation of the least advantaged who do actually make it to postsecondary education would be interesting to monitor. As university-colleges336increasingly adopt strong academic personae, how will participation by the leastadvantaged be affected? For example, to what extent will name changes (e.g.from community college to “university-college”) and changes in symbols (e.g. thechange from friendly, popular logos to academic crests) that reinforce anacademic focus further alienate those who already believe that post-secondaryeducation is not for me’7Post-secondary education may not be the answer for these students.However, alternatives for this group of graduates do not appear to be verypromising. The Report of the Task Force on Entry-Level Training describesentry-level training options in Canada as:too few, often badly conceived, poorly monitored, narrowly focused, insufficientlyresponsive to potential trainees’ needs, not well advertised, and inconsistently availablefrom region to region and province to province. (Report of the CLMPC Task Forces on theLabour Force Development Strategy, 1990)Furthermore, the Report of the Task Force on Apprenticeship reports that highschool leavers rarely choose apprenticeship as a form of post-secondaryeducation (Report of the CLMPC Task Forces on the Labour Force DevelopmentStrategy, 1990).Each year, a sizable number of high school graduates do not continue toany form of post-secondary education. Explorations with high school studentsregarding their perceptions of post-high school routes other than those providedby the formal post-secondary system, and follow-up studies of high schoolgraduates who do not continue to post-secondary education that monitor theirsuccesses and difficulties in securing employment, locating trainingopportunities, seeking counselling, and utilizing agencies of employmentassistance, would be enlightening.Action research projects of the sort promoted by Kemmis (1983) may beparticularly appropriate as a research methodology for the study of non-337participants. Kemmis describes action research as “a systematic process ofcollaborative review and improvement of educational or social policies,programs, and practices. It is participatory, collaborative, practice-based andaction-oriented, concretely critical, self-reflective and emancipatory” (p.146) (seealso Crysdale, 1975). By combining analyses of the problems surroundingtransition from high school with a participatory approach to the development ofstrategies for action, our understanding of transition difficulties will beenhanced, while at the same time meaningful programs and policies aredeveloped to counter the problem.Another area of interest in policy exploration is around the issue oftransfer from non-university to university institutions. Why are transfer rates solow (24% in 1988 and 25% in 1989) among those who begin their education innon-university institutions (British Columbia Research Corporation, 1990b,p.25)? Are individuals commencing at community colleges really “latentterminals” as Clark (1960) suggests? That is, do those who arrive at college haveminimal academic ability and thus require “cooling out” by “gently” encouragingstudents to lower their aspirations? It would be revealing to conduct a secondfollow-up of the sample of 1988 Grade 12 graduates used in this study, giventhat 59% of those who continued to non-university institutions had completedacademic programs in high school, and of those with academic credentialsattending non-university institutions, 44% had high school grade point averagesof 2.50 or greater. The interview data in this study reported that students withacademic credentials who commenced their education at community collegesexpected to raise -- not lower -- their academic standings before enrolling inuniversity. Students claimed that smaller classes, better teachers, and morepersonalized instruction offered at community colleges would help them achievethis goal.338Rather than Clark’s interpretation of “cooling out”, does “cooling the markout” in the spirit of Goffman’s (1952) original definition provide a more aptdescription of what happens to students who begin at community colleges? Thatis, are students who have completed academic programs lured into believingthat college is a preferable (i.e. easier, less stressful, more economical) route touniversity, only to discover the problems with transfer as outlined by Dougherty(1987) (see Chapter 2)? Confronted with unanticipated obstacles, such asdifficulty in obtaining credit for courses taken and quotas on the number oftransfer students accepted at universities, does the non-university collegestudent, or “mark”, leave the system “a little wiser and a lot poorer” (Goffman,1952, p.451)?What is the role of the community college in the transfer function? Whatpolicies are, or could be, in place to facilitate transfer? The transfer process fromcommunity college to a degree granting institution merits further investigationfrom the perspective of students’ experiences, instructors’ attitudes toward theirrole in the transfer process, whether and how classroom instruction fostersfuture success at university studies, and the actual mechanisms of transfer.This study highlights the importance of school personnel in guiding theway to post-secondary education. When primary social capital is limited, the roleof counsellors and teachers as brokers of information, support and assistance,and financial resources, is critical. The role of school personnel in guiding theway to post-secondary participation for females from low socioeconomicbackgrounds requires particular attention. The findings regarding the influenceof school personnel are not new. Turrittin, Anisef, and MacKinnon (1983), in ananalysis of a longitudinal sample of 1973 Grade 12 Ontario students, reportedvery similar results to those reported in this study. Recommendations advanced339by the Report of the Royal Commission on Education (1988) and the Ministry ofEducation (1990) regarding student support also warrant serious consideration.Finally, probably the most important issue facing policy makers is a cleardefinition of “who should attend post-secondary education”. While the Report ofthe Provincial Access Committee (1988) claimed that “there is an urgent need tofurther expand accessibility [and that there] is a clear need for greater equity ofaccess to advanced education and job training” (p.3) and provided severalrecommendations regarding participation, concise policy statements regardingwho should attend, and related enabling policies to facilitate attendance, do notappear to have been adopted by the British Columbia Ministry of AdvancedEducation, Training, and Technology. This study has illustrated thatparticipation in post-secondary education directly from high school depends onthe possession of three forms of capital -- academic (grades and appropriateprerequisites), economic (tuition and living costs), and social (information andsupport necessary to actuate plans). In addition, of crucial importance is theformulation of long term dispositions and strategies by students to participate inpost-secondary education. The degree to which policies squarely address theseprerequisites for attendance, while simultaneously monitoring demographicchanges in future cohorts as highlighted by Hodgkinson (1985) and Pallas,Natriello, and McDill (1989), will ultimately dictate who should, and will,partake in post-secondary education.340REFERENCE LISTAdams, J., Hayes, J., & Hopson, B. (1976) Transition: Understanding andmanaging personal change. London: Martin Robertson.Adler, R.B., & Towne, N. (1984). Looking out. Looking in. New York: Holt,Rinehart, & Winston.Administrative handbook (1986). British Columbia: Queen’s Printer.Akyeampong, E.B. (1989). Working for minimum wage. Perspectives on Labourand Income, 1(3), 8-20.Alba, R.D., & Lavin, D.E. (1981). Community colleges and tracking in highereducation. Sociology of Education, 54(4), 223-237.Alberta Advanced Education. (1989). 1988 high school graduate survey.Edmonton.Alberta Advanced Education. (1984). Participation patterns study. Report of thecommittee to examine participation trends of Alberta post-secondarystudents. Edmonton: Alberta Advanced Education, Planning Secretariat.Anderson, D.S., & Blakers, C. (Eds.). (1983). Youth, transition, and social research.Canberra: Australian National University Press.Alexander, K.L. & Cook, M. (1982). Curricula and coursework. A surprise endingto a familiar story. American Sociological Revi, 47(5), 626-640.Alexander, K.L., Eckland, B.K, & Griffin, L.J. (1975). The Wisconsin model ofsocioeconomic achievement: a replication. American Journal of Sociology,81(2), 324-342.Alexander, K.L., & McDill, E.L. (1976). Selection and allocation within schools.American Sociological Review, 41(6), 963-980.Alexander, K.L., & McDill, E.L. (1978). Curriculum tracking and educationalstratification: some further evidence. American Sociological Review,43(1), 47-66.Alexander, K.L., and Eckland, B.K. (1974). Sex differences in the educationalattainment process. American Sociological Review, 39(4), 668-582.341Alexander, K., Holupka, S. & Pallas, A.M. (1987a). Social background andacademic determinants of two-year versus four-year college attendance:Evidence from two cohorts a decade apart. American Journal ofEducation, 96(1), 56-80.Alexander, K.L., & Pallas, A.M. (1984). Curriculum reform and schoolperformance: an evaluation of the ‘new basics’. American Journal ofEducation, 92(4), 391-420.Alexander, K.L., Pallas, A.M., & Holupka, S. (1987b). Consistency and change ineducational stratification: Recent trends regarding social background andcollege access. In R.V. Robinson (Ed.), Research in social stratification andmobility (pp.l61-185) Greenwich, Connecticut: JAI Press Ltd.Allison, G.T. (1971). Essence of decision: Explaining the Cuban missile crisis.Boston: Little, Brown, & Company.Anderson, D.S. & Blakers, C. (Eds.). (1983). Youth, transition, and social research.Canberra: Australian National University Press.Anderson, K.L. (1984). Institutional differences in college effects. Boca Raton:Florida Atlantic University. (ERIC No. ED 256 204).Anderson, K.L. (1981). Post-high school experiences and college attrition.Sociology of EducaUon, (1), 1-15.Anderson, K.L. (1988). The impact of colleges and the involvement of male andfemale students. Sociology of Educatin, 613), 160-177.Anisef, P. (1983). Accessibility barriers to higher education in Canada and othercountries with recommendations for enhancing accessibility in theeighties. in Post-secondary education issues in the 1980s. Council ofministers proceedings of the CMEC conference on postsecondaryeducation (pp.l7’-58). Toronto: Council of Ministers of Education.Anisef, P. (1985). Accessibility to post-secondary education in Canada: A reviewof the literature. Ottawa: Department of the Secretary of State of Canada.Anisef, P. (1980). Is the die cast? Educational achievements and work destinationsof Ontario youth. Toronto: Ministry of Colleges & Universities.Anisef, P., Okihiro, N. & James, C. (1982). Losers and winners. Toronto:Butterworth & Co., Ltd.342Anisef, P. (1975). The critical juncture. Realization of the educational and careerintentions of grade 12 students in Ontario. Toronto: Ministry of Collegesand Universities.Anyon, J. (1981). Social class and school knowledge. Curriculum Inquiry, 11(1), 3-42.Aronowitz, S. & Giroux, H.A. (1985). Education under seige. Massachusetts:Bergin & Garvey Publishers, Ltd.Arrow, K. (1973). Higher education as a filter. Tournal of Public Economics, , 193-216.Astin, A. (1982). Minorities in American higher education. San Fransisco: JosseyBass.Audi, R. (1982). A theory of practical reasoning. American Philosophic Quarterly119(1), 25-39.Baird, B.F. (1978). Introduction to decision analysis. Massachusetts: DuxburyPress.Bean, J.P. & Metzner, B.S. (1985). A conceptual model of nontraditionalundergraduate student attrition. Review of Educational Research, 4),485-540.Beinder, F. (1983). The community college in British Columbia: The emphasis ison community. Nanairno, B.C.: Quadra Graphics.Bellamy, L. (1988). Student survey of the grade 12 class of 1986/87: A study ofparticipation in post-secondary education. Contracted study for SchoolDistrict 88 (Terrace) and Northwest Community College.Bellamy, L. & Guppy, N. (1991). Opportunities and obstacles for women in highereducation. In J.S. Gaskell & A. McLaren (Eds.), Women and education(2nd ed.) (pp.l63-l92.Calgary: Detselig Press.Bendix, R. & Lipset, S.M. (1953). Class, status and power. Illinois: The Free Press.Benn, S.I. & Mortimore, G.W. (Eds.) (1976). Rationality and the social sciences.London: Routledge & Kegan Paul.Bentler, P.M. (1980). Multivariate analysis with latent variables: causal modeling.Annual Review of Psychology, j, 419456.343Bezeau, L.M. (1989). Educational administration for Canadian teachers. Toronto:Copp Clark Pitman Ltd.Bidwell, C.E. & Friedkin, N.E. The sociology of education. In N. Smelser (Ed.),Handbook of sociology (pp.449-471). Beverley Hills: Sage Publications.Bielby, W.T. (1981). Models of status attainment. Research in Social Stratificationand Mobility, i 3-26.Bills, D. B. (1988). Educational credentials and promotions: Does schooling domore than get you in the door? Sociology of Education, 61(1), 52-60.Blishen, B.R., & McRoberts, H.A. (1976). A revised socioeconomic index foroccupations in Canada. Canadian Review of Sociology andAnthropology, 13(1), 71-79.Blake, J. (1985). The number of siblings and educational mobility. AmericanSociological Review, 50(1), 84-94.Blau, P.M. & Duncan, O.T. (1967). The American occupational structure. NewYork: John Wiley & Sons, Inc.Blau, P.M., Gustad, J.W. Jessor, R., Parnes, H.S. & Wilcock, R.C. (1956).Occupational choice: a conceptual framework. Industrial and LabourRelations Review, 9(4), 531-543.Bollen, K. (1989). Structural equations with latent variables. New York: JohnWiley & Sons.Boudon, R. (1974). Education, opportunity and social inequality. New York:Wiley. (Original work published in 1973).Bourdieu, P.(1977a). Cultural reproduction and social reproduction. In J. Karabel& A.H. Halsey (Eds.) Power and ideology in education, (p.487-511). NewYork: Oxford University Press.Bourdieu, P.(1984). Distinction. A social critique of the judgement of taste (R.Nice, Trans.). Cambridge: Harvard University Press. (Original workpublished in 1979).Bourdieu, P.(1990a). In other words. Essays toward a reflexive sociology (M.Adamson, Trans.). Stanford: Stanford University Press. (Original workpublished in 1982, 1987).344Bourdieu, P. (1991). Language and symbolic power (G. Raymond & M. Adamson,Trans.). Cambridge: Harvard University Press. (Original work publishedin 1977, 1984, 1983, 1984, 1984).Bourdieu, P. (1976). Marriage strategies as strategies of social reproduction E.Forster, Trans.). In R. Foster & 0. Ranum (Eds.), Family and society(pp.117-144). Baltimore: John Hopkins University Press. (Original workpublished in 1972).Bourdieu, P.(1977b). Outline of a theory of practice (R. Nice, Trans.). Cambridge:Cambridge University Press. (Original work published in 1972).Bourdieu, P., & Passeron, J. (1977c). Reproduction in education, society, andculture (R. Nice, Trans). London: Sage Publications. (Original workpublished in 1970).Bourdieu, P. (1983). The field of cultural production, or: the economic worldrevisited, Poetics. ja(4/5), 311-356.Bourdieu, P.(1986). The forms of capital (R. Nice, Trans.). In J.C. Richardson (Ed.),Handbook of theory and research for the sociology of educationi, (pp.24l-258). New York: Greenwood Press. (Original work published in 1973).Bourdieu, P., & Passeron, J. (1979). The inheritors (R. Nice, Trans.). Chicago:University of Chicago Press. (Original work published in 1966).Bourdieu, P. (1990b). The logic of practice (R. Nice, Trans.,). Stanford: StanfordUniversity Press. (Original work published in 1980).Bourdieu, P.(1976). The school as a conservative force: scholastic and culturalinequalities. In R. Dale, G. Esland, & M. MacDonald (Eds.), Schooling andcapitalism. A sociological reader (pp. 110-117). London: Routledge &Kegan Paul. (Original work published in 1979).Bowen, H.R. (1977). Investment in learning. San Fransisco: Jossey-Bass.Bowen, H.R. (1982). The state of the nation and the agenda for higher education.San Fransisco: Jossey-Bass.Bowles, S., & Gintis, H. (1976). Schooling in capitalist America. New York: BasicBooks, Inc.Boyd, M., Goyder, J., Jones, F.E., McRoberts, H.A., Pineo, P.C., & Porter, J. (1981).Status attainment in Canada: findings of the Canadian mobility study.Canadian Review of Sociology and Anthropology, 18(5), 657-673.345Bratlinger, E. (1985). What low-income parents want from schools: a differentview of aspirations, Interchange. 16(4), 14-28.Breneman, D.W., & Nelson, S.E. (1981). Financing community colleges: aneconomic perspective. Washington, D.C.: Brookings Institute.Breton, R. (1972). School and academic factors in the career decisions of Canadianyouth. Ottawa: Information Canada.Brint, S. & Karabel, J. (1989). The diverted dream. Community colleges and thepromise of educational opportunity in America, 1900-1985. New York:Oxford University Press.British Columbia Council on Admissions and Transfer. (1989). Some enrolmentand transfer trends for non-vocational post-secondary students. Reportprepared for the initial meeting of the B.C. Council on Admissions andTransfer, August 1989.British Columbia Human Resource Development Project. (1991). Current state ofthe project. Project update. November, p.2.British Columbia Research Corporation. (1990a). A follow-up survey of 1987/88grade 12 graduates. Technical Report. Vancouver: B.C. Research.British Columbia Research Corporation. (1990b). University articulation anddegree completion 1986-1989. Report prepared for the B.C. Council onAdmissions and Transfer, August 1989.British Columbia Royal Commision on Education. A legacy for learners. (1988).Victoria: Queen’s Printer.Buchrnann, M. (1989). The script of life in modern society. Entry into adulthood ina changing world. Chicago: University of Chicago Press.Campbell, G. (1975). Some comments on reports of post-secondary commissionsin relation to community colleges in Canada. Canadian Journal of HigherEducation, 5(3), 55-68.Campbell, R.T. (1983). Status attainment research: end of the beginning orbeginning of the end? Sociology of Education, 561), 47-62.Carleton, R., Colley, L., & MacKinnon, N. (Eds.). (1977). Change and society: asociology of Canadian education. Agincourt: Gage.Chapman, D.W. (1981). A model of student college choice. Journal of HigherEducation, 52(5), 490-505.345Breneman, D.W., & Nelson, S.E. (1981). Financing community colleges: aneconomic perspective. Washington, D.C.: Brookings Institute.Breton, R. (1972). School and academic factors in the career decisions of Canadianyouth. Ottawa: Information Canada.Brint, S. & Karabel, J. (1989). The diverted dream. Community colleges and thepromise of educational opportunity in America, 1900-1985. New York:Oxford University Press.British Columbia Council on Admissions and Transfer. (1989). Some enrolmentand transfer trends for non-vocational post-secondary students. Reportprepared for the initial meeting of the B.C. Council on Admissions andTransfer, August 1989.British Columbia Human Resource Development Project. (1991). Current state ofthe project. Project update. November, p.2.British Columbia Research Corporation. (1990a). A follow-up survey of 1987/88grade 12 graduates. Technical Report. Vancouver: B.C. Research.British Columbia Research Corporation. (1990b). University articulation anddegree completion 1986-1989. Report prepared for the B.C. Council onAdmissions and Transfer, August 1989.British Columbia Royal Commision on Education. A legacy for learners. (1988).Victoria: Queen’s Printer.Buchmann, M. (1989). The script of life in modern society. Entry into adulthood ina changing world. Chicago: University of Chicago Press.Campbell, G. (1975). Some comments on reports of post-secondary commissionsin relation to community colleges in Canada. Canadian Journal of HigherEducatiofl, 53), 55-68.Campbell, R.T. (1983). Status attainment research: end of the beginning orbeginning of the end? Sociology of Education, 56(1), 47-62.Carleton, R., Colley, L., & MacKinnon, N. (Eds.). (1977). Change and society: asociology of Canadian education. Agincourt: Gage.Chapman, D.W. (1981). A model of student college choice. Journal of HigherEducation, 52(5), 490-505.346Clark, B. (1960). The ‘cooling-out function in higher education.In A. H. Halsey, J.Floud, & C.A. Anderson (Eds.) Education, economy, and society (pp.513-523). New York: The Free Press.Cohen, G. L. (1989). Youth for hire. Perspectives on Labour and Income. id), 7-14.Coleman, J.S. (1990). Foundations of social theory. Cambridge: The Belknap Pressof Harvard University Press.Coleman, J.S. (1988). Social capital in the creation of human capital. AmericanJournal of Sociology, j(Supplernent), S95-S120.Coleman, J.S. (1986). Social theory, social research, and a theory of action.American Journal of Sociology, 91(6), 1309-1335.Coleman, J.S., & Husén, T. (1985). Becoming adult in a changing society. Paris:OECD.Coleman, J.S. et al. (1974). Youth. Transition to adulthood. Chicago: University ofChicago Press.Collins, R. (1979). The credential society. New York: Academic.Cook, K.S., & Levi, M.(Eds.) (1990). The limits of rationality. Chicago: Universityof Chicago Press.Coombs, J. (1986). Practical reasoning: What is it? How do we enhance it? Paperpresented at the Conference on Thinking and Problem Solving, Ohio StateUniversity, June 1986.Coser, L.A. (1975). Presidential address: two methods in search of a substance.American Sociological Review, 40(6) 691-700.Council of Ministers of Education, Canada (1982). Post-secondary issues in the1980’s. Proceedings of the CMEC Conference on Post-secondaryeducation. Toronto.Crysdale, S. (1975). Aspirations and expectations of high school youth.International Journal of Comparative Sociology, 16(2), 19-36.Curtis, J., Grabb, E., Guppy, N., & Gilbert, S. (Eds.). (1988). Social inequality inCanada. Patterns, problems, policies. Scarborough: Prentice Hall.Cuttance, P. & Ecob, R. (1987). Structural modelling by example. Cambridge:Cambridge University Press.347Dahrendorf, R. (1979). Life chances. London: Weidenfeld & Nicholson.Dale, R., Esland, G., & MacDonald, M. (Eds.). (1974). Schooling and capitalism. Asociological reader. London: Routledge & Kegan Paul.Dennison, J.D., Forrester, G.C., & Jones, G. (1982). A study of students fromacademic programs in British Columbia’s community colleges. CanadianJournal of Higher Education, 1(1), 29-41.Dennison, J.D., & Gallagher, P. (1986). Canada’s community colleges. A criticalanalysis. Vancouver: University of British Columbia Press.Dennison, J.D., Tunner, A., Jones, G., & Forrester, G.C. (1975). The impact of flcommunity colleges. Vancouver: B.C. Research.Denzin, N.K. (1989). The research act New Jersey: Prentice Hall.Department of the Secretary of State of Canada. (1988). Access to excellence. BeingCanadian . . .Working together for post-secondary education. Ottawa:Minister of Supply and Services.Department of the Secretary of State of Canada. (1990). Federal and provincialsupport for post-secondary education in Canada 1988-89. Ottawa:Minister of Supply and Services.Dillon, W.R. & Goldstein, M. (1984). Multivariate analysis. Methods andapplications. New York: John Wiley & Sons.Diliman, D., Carpenter, E., Christenson, J., & Brooks, R. (1974). Increasing mailquestionnaire response: a four state comparison. American SociologicalReview, a2.5), 744-756.DiMaggio, P. (1982). Cultural capital and school success: the impact of statusculture participation on the grades of U.S. high school students. AmericanSociological Review, 47(2), 189-201.DiMaggio, P., & Mohr, J. (1985). Cultural capital, educational attainment, andmarital selection. American Journal of Sociology, 90(6), 1231-1261.Dore, R. (1976). The diploma disease. Berkeley and Los Angeles: University ofCalifornia Press.Dougherty, K. (1989). The effects of community colleges: aid or hindrance tosocioeconomic attainment? Sociology of Educatjcm, 60(2), 86-103.348Douglass, G.K. (1977). Economic returns on investment in higher education. InH.R. Bowen, (Ed.), Investment in learning (pp.359-87). San Fransisco:Jossey-Bass.Duncan, 0. & Hodge, R.W. (1963). Education and occupational mobility: aregression analysis. American Journal of Sociology, 68(6), 629-644.Dye, R.F. (1980). Contributions to volunteer time: some evidence on income taxeffect. National Tax Journal, 33(1), 89-93.Ecob, P. & Cuttance, R. (1987). An overview of structural equation modeling. InCuttance, P. & Ecob, R. (Eds.), Structural modeling by example (pp.9-24)Cambridge: Cambridge University Press.Economic Council of Canada. (1990). Good jobs, bad jobs. Employment in theservice sector. Ottawa: Supply and Services Canada.Economic Council of Canada. (1987). Making technology work: innovation andjobs in Canada. Ottawa: Supply and Services Canada.Egan, G. (1982). The skilled helper. Monterey: Brooks/Cole Publishing Company.Elster, J. (1989a). Nuts and bolts for the social sciences. Cambridge: CambridgeUniversity Press.Elster, J. (Ed.) (1986). Rational choice. Oxford: Basil Blackwell Ltd.Elster, J. (1989b). Solornonic judgernents. Studies in the limits of rationality.Cambridge: Cambridge University Press.Elster, J. (1983). Sour grapes. Cambridge: Cambridge University Press.Erickson, F. & Schultz, 1. (1982). The counsellor as gatekeeper: social interaction ininterviews. New York: Academic Press.Fischer, Fj. (1987). Graduation-contingent student aid. Chaiig,November/December, 40-47.Foster, R. & Ranum, 0. (Eds.), Family and society. Baltimore: John HopkinsUniversity Press..Fortin, M. (1987) Accessibility to and participation in the post-secondaryeducation system in Canada. Saskatoon: National Forum on PostSecondary Education.Freeman, R. (1976). The overeducated American. New York: Academic Press.349Fuchs, V.R. (1980). Economic aspects of health. Chicago: University of ChicagoPress.Gambetta, D. (1987). Were they pushed or did they jump? Individual decisionmechanisms in education. Cambridge: Cambridge University Press.Gambetta, D. (1982). Were they pushed or did they jump? An analysis ofeducational decisions in north-west Italy. Dissertation AbstractsInternational.Gaskell, J.S. (1985). Course enrollment in the high school: the perspective ofworking class females, Sociology of Educati (1), 48-59.Gaskell, J.S. (1983). Education and women’s work: Some new research directions.Alberta Journal of Educational Researcji 29(3), 224-241.Gaskell, J.S. (1981). Equal educational opportunity for women. In J.D. Wilson(Ed.), Canadian Education in the 1980’s (pp. 173-193). Calgary: DetseligEnterprises Ltd.Gaskell, J.S. & Lazerson, M. (1981). Between school and work: perspectives ofworking class youth. In J.D. Wilson (Ed.), Canadian Education in the1980’s (pp. 173-193). Calgary: Detselig Enterprises Ltd.Gaskell, J. & McLaren, A. (Eds.). (1987). Women and education (1st ed.). Calgary:Detselig Press.Gaskell, J. & McLaren, A. (Eds.). (1991). Women and education (2nd ed.). Calgary:Detselig Press.Gera, S. (Ed.). (1991). Canadian unemployment. Lessons from the 80s andchallenges for the 90s (pp. 1-19). Ottawa: Economic Council of Canada.Gera, S., & McMullen, K. (1991). Unemployment in Canada: issues, findings, andimplications. In S. Gera (Ed.), Canadian unemployment. Lessons from the80s and challenges for the 90s (pp. 1-19). Ottawa: Economic Council ofCanada.Giddens, A. (1984). The constitution of society. Berkeley: University of CaliforniaPress.Gilbert, E.S. (1968). On discrimination using qualitative variables. Journal of theAmerican Statistical Association, 63(324), 1399-1412.350Gilbert, S. (1977). The selection of educational aspirations. In R. Carleton, L.Colley, & N. MacKinnon (Eds.), Change and society: a sociology ofCanadian education (pp.28l-97).Agincourt: Gage.Gilbert, S. & Guppy, N. (1988). Trends in participation in higher education bygender. In J. Curtis, E. Grabb, N. Guppy, & S. Gilbert (Eds.), Social equityin Canada. Patterns, problems, policies (pp.163-169). Scarborough:Prentice-Hall Canada Inc.Gilbert, S. & Pomfret, A. (1991). Gender tracking in university programs: ananalysis of gender patterns in Canada scholarships program (CSP)disciplines and non-CSP university disciplines. Industry, Science, andTechnology Canada.Gilbert, S.N. & McRoberts, H.A. (1977). Academic stratification and educationplans: a reassessment. Canadian Review of Sociology and Anthropology,li(1), 34-47.Giroux, H. (1983). Theory and resistance in education. Massachusetts: Bergin andGarvey Publishers, Inc.Glaser, B. G., & Strauss, A.L. (1967). The discovery of grounded theory. Strategiesfor qualitative research. Chicago: Aldine.Glass, G.V., & Hopkins, K.D. (1984). Statistical methods in education andpsychology. New Jersey: Prentice-Hall.Gluckman, M. (1967). The judicial process among the Barotse of NorthernRhodesia. Manchester: Manchester Press.Goetz, J.P., & LaCompte, M. D. (1984). Ethnography and qualitative design ineducational research. San Diego: Academic Press, Inc.Goffman, E. 1952. On cooling the mark out. Psychiatry, 154), 451-463).Gower, D. (1989). Canada’s unemployment inosiac. Perspectives on Labour andIncome. Ui), 15-25.Grossman, M., & Jacobowitz, S. (1981). Variations in infant mortality rates amongcounties in the United States. Demography, 18(4), 695-713.Guppy, N. (1984). Access to higher education in Canada. Canadian Journal ofHigher Education, 14(3), 79-93.Guppy, N. (1988). Accessibility to higher education - new trend data. CAUTBulletin, 35(6), 15-16.351Guppy, N. (1985). Education under seige: financing and accessibility in B.C.universities. Canadian Journal of Sociology, 10(3), 295-308.Guppy, N., Mikicich, P.D., & Pendakur, R. (1984). Changing patterns ofeducational inequality in Canada. Canadian Journal of Sociology 9(3),319-331.Guppy, N. & Pendakur, K. (1989). The effects of gender and parental education onparticipation within post-secondary education in the 1970s and 1980s.Canadian Journal of Higher Education, 19(1), 49-62.Guppy, N., Vellutini, S., & Balson, D. (1987). Women and higher education inCanadian society. In J. Gaskell & A. Mclaren (Eds.), Women andeducation (pp. 151-170). Calgary: Detselig Press.Hayduk, L. (1987). Structural equation modeling with LISREL. Baltimore: JohnHopkins University Press.Hailer, A.O. & Fortes, A. (1973). Status attainment process. Sociology ofEducation, 46(1), 51-91.Halsey, A.H., Floud, J. & Anderson, C.A, (Eds.). (1961). Education, economy, andsociety (pp.5l3-523). New York: The Free Press.Halsey, A.H., Heath, A.F., & Ridge, J.M. (1980). Origins and destinations. Oxford:Oxford University Press.Harker, R. (1990). Bourdieu: Education and reproduction. In R. Harker, C. Mahar,& C. Wilkes (Eds.), An introduction to the work of Pierre Bourdieu(pp.109-131). Hampshire: MacMillan Press Ltd.Harker, R., Mahar, C. & Wilkes, C. (Eds.). (1990) An introduction to the work ofPierre Bourdieu. Hampshire: MacMillan Press Ltd.Härnqvist, K. (1978). Individual demand for education. Paris: OECD.Harris, R. (1976). A history of higher education in Canada 1663-1960. Toronto:University of Toronto Press.Harsanyi, J.C. (1986). Advances in understanding rational behavior. In J. Elster(Ed.). Rational choice (pp.82-lO7). Oxford: Basil Blackwell Ltd.Harvey, E. (1977). Accessibility to post-secondary education, University Affairs,a(8) 10-11.352Hatten, A. (1991). Minority report. In Report of the CLMPC task forces on thelabour force development strategy, (pp. 234-237). Ottawa: CanadianLabour Market and Productivity Centre.Haveman, R.H. & Wolfe, B.L. (1984). Schooling and economic well-being: The roleof nonmarket effects. Journal of Human Resources, 19@),377-407.Heath, A. (1976). Rational choice and social exchange. Cambridge: CambridgeUniversity Press.Heberlein, T.A. & Baumgartner, R. (1978). Factors affecting response rates tomailed questionnaires: A quantitative analysis of the published literature.American Sociological Review, 43(4), 447-462.Heffich, W. (1972). Consumption benefits from education. In S. Ostry (Ed.).Canadian higher education in the seventies (pp.177-198). Ottawa:Economic Council of Canada.Heyns, B. (1974). Selection and stratification in schools. American Journal ofSociology, 79(6), 1434-1451.Hindess, B. (1988). Choice, rationality, and social theory. London: Unwin Hyman.Hoelter, J. W. (1983). The analysis of covariance structures: goodness-of-fitindices. Sociological Methods and Research, 11(3), 325-344.Hodgkinson, H.L. (1985). All one system. Demographics of education,kindergarten through graduate school. Washington, D.C.: The Institutefor Educational Leadership.Holland, J. (1973). Making vocational choices. A theory of careers. New Jersey:Prentice-Hall.Holland, J. (1966). The psychology of vocational choice. Massachusets: Blaisdall.Horan, P.M. (1978). Is status attainment research atheoretical? AmericanSociological Review, 434), 534-541.Hossler, D., Braxton, J., & Coopersmith, G. (1989). Understanding student collegechoice. In J.C. Smart (Ed.), Higher Education: Handbook of Theory andResearch. Volume V (pp.Z3l-288). New York: Agathon Press.Hunter, A.A. (1988). Formal education and initial employment. Unravelling therelationships between schooling and skills over time. AmericanSociological Review, ), 753-765.353Jackson, G.A. (1982). Public efficiency and private choice in higher education,Educational Evaluation and Policy Analysis. .(2), 237-247.Janis, I.L. & Mann, L. (1977). Decision making. A psychological analysis ofconflict, choice, and commitment. New York: The Free Press.Jencks, C., Crouse, J., & Mueser, P. (1983). The Wisconsin model of statusattainment: a national replication with improved measures of ability andaspiration. Sociology of Education, 56(1), 3-18.Jones, C., Clarke, m., Mooney, G., McWilliams, H., Crawford, I., Stephenson, B. &Tourangeau, R. (1982). High school and beyond. 1980 senior cohort firstfollow-up (1982). Data file users manual. Washington, D.C.: NationalCenter for Educational Statistics.Joreskog, K.G., & Sörbom, D. (1984). LISREL 6. Analysis of linear structuralrelationships by the method of maximum likelihood, instrumentalvariables, and least squares method. Uppsala, Sweden: University ofUppsala.Joreskog, K.G, & Sörbom, D. (1989). LISREL 7. A guide to the program anapplications. Uppsala, Sweden: SPSS Inc.Joreskog, K.G, & Sörbom, D. (1982). Recent developments in structural equationmodelling. Journal of Marketing Research, 19 (4), 404-416.Jothen, K. (1989). An analysis of career, technical, vocational, and basic trainingneeds in British Columbia, 1989-93. Victoria: Ministry of AdvancedEducation, Training and Technology for the Open Learning College.Juster, F.T. (Ed.). (1975). Education, income, and human behavior. New York:McGraw-Hill.Karabel, J. (1986). Community colleges and social stratification in the 1980’s. InL.S. Zwerling (Ed.), The community college and its critics. New Directionsfor Community Colleges, San Fransisco: Jossey-Bass, 54(2), 13-30.Karabel, J. & Halsey, A.H. (Eds.). (1977). Power and ideology in education. NewYork: Oxford University Press.Katsillis, J. & Rubinson, R. (1990). Cultural capital, student achievement, andeducational reproduction: the case of Greece. American SociologicalReview, (2), 270-279.Keller, S. & Zavalloni, M. (1964). Ambition and social class: a respecification.Social Forces, .(I), 58-70.354Kennett, J. (1973). The sociology of Pierre Bourdieu. Educational Review, (3),237-249).Kemmis, S. (1983). Action research. In D.S. Anderson & C. Blakers (Eds.), Youth,transition, and social research (pp.130-152). Canberra: Australian NationalUniversity Press.Kerckhoff, A.C. (1976). The status attainment process: socialization or allocation?Social Forces, 55(2), 368-381.Kish, L. (1987). Statistical design for researcK New York: John Wiley & Sons.Kiecka, W. R. (1980). Discrirninant analysis. Beverly Hills: Sage Publications.Knorr-Cetina, K. 1981). the micro-sociological challenge of macro-sociology:towards a reconstruction of social theory and methodology. In K. KnorrCetina & A.V. Cicourel, (Eds.), Advances in social theory andmethodology. Toward an integration of micro- and macro-sociologies(pp.1-48). Boston: Routledge & Kegan Paul.Knorr-Cetina, K. & Cicourel, A.V. (Eds.). (1981). Advances in social theory andmethodology. Toward an integration of micro- and macro-sociologies.Boston: Routledge & Kegan Paul.Krein, S.F., & Beller, A.H. (1988). Educational attainment of children from single-parent families: Differences by exposure, gender, and race. Demography,25 (2), 221-234.Lachenbruch, P.A. (1975). Discrirninant analysis. New York: Hafner Press.Lamont, M. & Lareau, A. (1988). Cultural capital: allusions, gaps, and glissandosin recent theoretical developments. Sociological Theory, , 153-168.Lane, M. (1972). Explaining educational choice. Sociology, 255-266.Lareau, A. (1987). Social class differences in family-school relationships: theimportance of cultural capital. Sociology of Education. (1), 73-85.Learning well . . . living well. (1991). Ottawa: Minister of Supply and ServicesCanada.Lee, V.E. & Ekstrom, R.B. (1987). Student access to guidance counselling in highschool. American Educational Research Journal, 24(2), 287-310.355Levi, M., Cook, K.S., O’Brien, J.A., & Faye, H. (1990). The limits of rationality, inCook, K.S. & Levi, M.(Eds.) (1990). The limits of rationality (pp.1-i6)Chicago: University of Chicago Press.Lindert, P.H. (1977). Sibling position and achievement. Journal of HumanResources, 12(2), 198-219.Litten, L.H. (1982). Different strokes in the applicant pool,.Some refinements in amodel of student college choice. Journal of Higher Education, 53(4), 283-402.Looker, E. D., & Pineo, P.C. (1983). Social psychological variables and theirrelevance to the status attainment of teenagers, American Journal ofSociology, 88(6), 1195-1219.Macdonald, J.B. (1962). Higher education in British Columbia and a plan for thefuture. Vancouver: University of British Columbia.Marjoribanks, K. (1988). Cognitive and environmental correlates of adolescents’achievement ambitions: family-group differences. Alberta Journal ofEducational Research, 34(2), 166-178.Marjoribanks, K., Secombe, M. & Smolicz, J.J. (1987). Ethnicity, educationalattainment and occupational aspirations: unemployed young adults.Educational Research and Perspectives, 14(2), 29-39.McGrew, A.G. & Wilson M.J. (1982). Decision making. Approaches and analysis.Manchester: Manchester University Press.Medsker, L. & Tillery, D. (1971). Breaking the access barrier. New York: McGrawHill.Michael, R.T. (1973). Education and the derived demand for children. Journal ofPolitical Economy, i(Supplement), si28-64.Miller, D.C. (1977). Handbook of research design and social measurement NewYork: David McKay Company, Inc.Miller, K.A., Kohn, M.L., & Schooler, C. (1986). Educational self-direction andpersonality. American Sociological Review, 51(3), 372-390.Mincer, J. (1989). Human capital and the labor market. A review of currentresearch. Educational Researcher, 18(4), 27-34.Minister of State (Youth). (1984). Focus on youth. Ottawa: Minister of Supply andServices Canada.356Ministry of Advanced Education and Job Training. (1988). B.C. post-secondaryenrolment statistics 1987/88. Victoria: Funding and Analysis Division.Ministry of Advanced Education and Job Training. (1987). Completion, transfer,and retention. Paper No. 8 in the Access, Completion and Transition toWork Series.Ministry of Advanced Education and Job Training. (1991). Ministry plan. Victoria:Ministry of Advanced Education and Job Training.Ministry of Advanced Education and Job Training. (1986). University degrcompletion 1977-1984. Report No. 51. The British Columbia CollegesArticulation Study. Vancouver: B.C. Research.Ministry of Education. (1990a). Ministry of education annual report BritishColumbia: Ministry of Education.Ministry of Education (1990b). The graduation program. Response draft. Victoria.Ministry of Education.Mishler, E.G. (1986) Research interviewing. Massachusetts: Harvard UniversityPress.Mortimore, G.W. (1976). Rational action. In S.I. Benn & G.W Mortimore, (Eds.)Rationality and the social sciences (pp.93-llO). London: Routledge &Kegan Paul.Murphy, K. & Welch, F. (1989). Wage premiums for college graduates. Recentgrowth and possible explanations. Educational Researcher. .8(4), 17-26.Myles, J., Picot, G. & Wannell, T. (1988). Wages and jobs into the 1980s: Changingyouth wages and the declining middle. Ottawa: Social and EconomicsStudies Division, Statistics Canada.Norusis, M. (1990). SPSS advanced statistics student guide. Chicago: SPSS, Inc.O’Neill, G.P. (1981). Post-secondary aspirations of high school seniors fromdifferent socio-demographic contexts. Canadian Journal of HigherEducation, 11(2), 49-66.Olson, P. (1986). Methods, interpretations, and different views of aspirations.Interchange, 11(1), 76-81.Orfield, G. & Paul, F. (1988). Declines in minority access: a tale of five cities.Educational Record, 69(1), 52-56.357Organization for Economic Cooperation and Development. (1983). Education andwork. The views of the young. Paris: OECD.Organization for Economic Cooperation and Development. (1976). Review ofNational Policies in Canada. Paris: OECD.Ostry, S. (Ed.). (1972). Canadian higher education in the seventies. Ottawa:Economic Council of Canada.Page, R. & Valli, L. (Eds.) (1990). Curriculum differentiation: interpretive studiesin U.S. secondary schools. New York: SUNY Press.Pallas, A.M. (1984). The determinants of high school dropout. DissertationAbstracts International, 45, 08B.Pallas, A.M., Natriello, G. & McDill, E.L. (1989) The changing nature of thedisadvantaged population: Current dimensions and future trends.Educational Researcher, 18(5), 16-22.Perun, P.J. (Ed.). (1982). The undergraduate woman: issues in educational equity(pp.127-158). Lexington: Lexington BooksPike, R. (1970). Who goes to university and why: a study on accessibility to highereducation in Canada. Ottawa: Association of Universities and Colleges ofCanada.Pincus, F. (1986). Vocational education: more false promises. In L.S. Zwerling(Ed.), The community college and its critics. New Directions forCommunity Colleges, San Fransisco: Jossey-Bass, 54(2), 41-52.Pineo, P.C., & Goyder, J. (1988). The growth of the Canadian educational system:an analysis of transition probabilities. Canadian Journal of HigherEducation, 17(2), 37-54.Porter, 1. (1965). The vertical mosiac. Toronto: University of Toronto Press.Porter, J., Porter, M. & Blishen, B., Barrados, M., Gilbert, S., McRoberts, H., &Russell, S. (1982). Stations and callings. Toronto: Methuen Publications.Porter, M. & Jasmin, C. (1987). A profile of post-secondary students in Canada.Ottawa: Minister of Supply and Services Canada.Prosperity through competitiveness. (1991). Ottawa: Minister of Supply andServices Canada.358Psacharopoulos, G. (1986). Links between education and the labour market: abroader perspective. European Journal of Education, 21(4), 409-415).Radwanski, G. (1987). Ontario study of the relevance of education, and the issueof dropouts. Toronto: Ministry of Education.Rehberg, R.A. & Rosenthal, E.R. (1978). Class and merit in the American highschooL New York: Longman Inc.Report of the CLMPC task forces on the labour force development strategy.(1990). Ottawa: Canadian Labour Market and Productivity Centre.Report of the Provincial Access Committee. (1988). Access to advanced educationand job training in British Columbia. British Columbia: Ministry ofAdvanced Education and Job Training.Report of the Royal Commission on the Economic Union and DevelopmentProspects of Canada. (1983). Ottawa: Information Canada.Robbins, D. (1991). The work of Pierre Bourdieu. Boulder: Westview Press.Robinson, R.V. (Ed.). (1987). Research in social stratification and mobility.Greenwich, Connecticut: JAI Press Ltd.Robinson, R.V., & Gamier, M.A. (1985). Class reproduction among men andwomen in France: Reproduction theory on its home ground. AmericanJournal of Sociology. 91(2), 250-280.Rosenbaum, J.E. (1976). Making inequality. New York: John Wiley.Rosenfeld, R.A. & Hearn, J.C. (1982). Sex differences in the significance ofeconomic resources for choosing and attending a college. In P.J. Perun(Ed.), The undergraduate woman: issues in educational equity (pp.127-158). Lexington: Lexington Books.School act. (1989). British Columbia: Queens Printer.Schultz, T.W. (1961). Investment in human capital. American Economic Review,51(1), p. 1-17.Schultz, T.W. (1975). The value of the ability to deal with disequilibrium. Journalof Economic Literature, 13(3), 827-46.Schwartz, A. (1976). Migration, age, and education. Journal of Political Economy,84(4), p. 701-20.359Science Council of Canada. (1988). Winning in a world economy. University-industry interaction and economic renewal in Canada. Ottawa: Ministerof Supply and Services.Selleck, L. (1980). Equality of access to Ontario universities. Toronto: Council ofOntario Universities.Selieck, L.J., & Breslauer, H.J., (1989). Increasing female clientele for universityeducation in Canada. Paper presented at the meeting of the CanadianSociety for the Study of Higher Education, Laval University, June 1989.Sewell, W.H. (1971). Inequality of opportunity for higher education. AmericanSociological Review, 36(5), 793-809.Seweli, W.H., Hailer, A.O., & Ohlendorf, G.W. (1970). The educational and earlyoccupational attainment process: replication and revision. AmericanSociological Reviev, 3(6), 1014-1027.Sewell, W.H., Hailer, A.O., & Portes, A. (1969). The educational and earlyoccupational attainment process. American Sociological Review, 82-92.Sewell, W.H. & Hauser, R.M. (1975). Education, occupation, and earnings. NewYork: Academic Press.Sewell, W.H., Tsai, S., & Hauser, R.M. (1983). A model of stratification withresponse error in social and psychological variables. Sociology ofEducation, (1), 20-46.Shockey, J.W. (1989). Overeducation and earnings: A structural approach todifferential attainment in the U.S. labor force (1970-1982). AmericanSociological Review, 54(5), 856-864.Simon, H. (1957). Models of man. New York: John Wiley & Sons.Sloan, T. (1987). Deciding. Self-deception in life choices. New York: Methuen &Co.Smart, J.C. (Ed.). (1989) Higher education: handbook of theory and research.Volume V. New York: Agathon Press.Smelser, N. (Ed.). (1988). Handbook of sociology. Beverley Hills: SagePublications.Solomon, L.C. (1975). The relation between schooling and savings behavior: Anexample of the indirect effects of education. In F.T. Juster, (Ed.),360Education, income, and human behavior (pp.253-94). New York:McGraw-Hill.SPSS-X user’s guide. (1988). Chicago: SPSS, Inc.Stager, D. (1989a). Focus on fees. Toronto: Council of Ontario Universities.Stager, D. (1989b). Returns to investment in selected university programs, 1960-1985. Paper presented at the Annual Meeting of the Canadian Society forthe Study of Higher Education, Université Laval, Québec, June 1989.Standing Senate Committee on National Finance. (1987). Federal policy on post-secondary education. Ottawa: Minister of Supply and Services Canada.Statistics Canada. (1989a). Canada’s youth: A profile of their 1986 labour marketexperience Ottawa: Minister of Supply and Services Canada. Catalogue71-207. March 1989.Statistics Canada. (1989b). Income disfributions by size in Canada 1988. Ottawa:Minister of Supply and Services Canada. Catalogue 13-207. November1989.Statistics Canada. (1988). The labour force. Catalogue no. 71-001. December 1988.Statistics Canada. (1980 to 1989). The labour force annual averages. Catalogue no.71-529.Statistics Canada. (1989d). Youth in Canada. Ottawa: Minister of Supply andServices Canada. Catalogue 89-511. March 1989.Stephenson, B. (1982). Closing address. In Council of Ministers of Education,Canada, Post-secondary issues in the 1980s (pp.l7-SS). Proceedings of theCMEC Conference on Post-secondary Education. Toronto.Stevens, J. (1983). Applied multivariate statistics for the social sciences. NewJersey: Lawrence Erlbaurn.Super, D.E. (1957). The psychology of careers. New York: Harper & Row.Super D.E. & Crites, J.O. (1962). Appraising vocational fitness. New York: Harper.Tabachnick, B.G. & Fidell, L.S. (1983) Using multivariate statistics. New York:Harper & Row.361Taubman, P. & Rosen, S. (1980). Healthiness, education, and marital status. InV.R. Fuchs (Ed.), Economic aspects of health (pp. 121-142). Chicago:University of Chicago Press.Tinto, V. (1987). Leaving college. Rethinking the causes and cures of studentattrition. Chicago: University of Chicago Press.Tinto, V. (1975a). Dropout from higher education: a theoretical synthesis of recentresearch, Review of Educational Research. jI), 89-125.Tinto, V. (1975b). The distributive effects of public junior college availability.Research in Higher Education, 3(3), 261-274.Trow, M. (1989). American higher education. Past, present, and future.Educational Researcher. 17(3), 13-23.Tuijnrnan, A. (1989). Recurrent education, earnings, and well-being. DissertationAbstracts Internatiojj, 51, 719C.Turner, R. (1960). Sponsored and contest mobility and the school system.American Sociological Review, 25(6), 855-867.Turrittin, A., Anisef, P., & MacKinnon, N. (1983). Gender differences ineducational achievement: a study of social inequality. Canadian Journalof Sociology, 8i4), 395-420.Tversky, A. (1972). Elimination by aspects. A theory of choice. PsychologicalReview, 79(4), 281-299).Vaillancourt, F. & Henriques, I. (1986). The returns to university schooling inCanada. Canadian Public Policy, 12(3), 449-458.Vanfossen, B.E. , Jones, J.D., & Spade, J.Z. (1987). Curriculum tracking and statusmaintenance. Sociology of Education, 60(2), 104-122.Vaizey, J. & Debeauvais (1961). Economic aspects of educational development. InHalsey, A.H., Floud, J., & Anderson, C.A. (Eds.), Education, Economy,and Society (pp. 37-52). New York: Free Press.Van Gennep, A. (1960). Rites of passage (M.B. Vizedom & G.L. Caffee, Trans.).London: Routledge & Kegan Paul Ltd. (Original work published in 1908).Velez, W. (1985). Finishing college: The effects of college type. Sociology ofEducaticn, 58(3), 191-200.362Wallace, D. (1954). The case for - and against - mail questionnaires. PublicOpinion Quarterly, , 40-52Watchtel, A. (1987). Youth employment projects in Canada. Vancouver: SocialPlanning and Research Council of Canada.Watts, R.L. (1987). The challenges and opportunities facing post-secondaryeducation in Canada. Saskatoon: National Forum on Post-secondaryEducation.Weir, R. (1986). Low income parents - what they want from schools. Interchange,(1), 82-84.West, E.G. (1988). Higher education in Canada: An analysis. British Columbia:The Fraser Institute.Wiersrna, W. (1986). Research methods in education. Boston, Allyn & Bacon.Willis, P. (1977). Learning to labour. Farnborough, Hants: Saxon House.Wilson, J.D. (Ed.), Canadian Education in the 1980’s. Calgary:Detselig EnterprisesLtd.Wolfie, L. (1987). High school seniors’ reports of parental socioeconomic status:black-white differences. In P. Cuttance & R. Ecob (Eds.), Structuralmodeling by example (pp.5l-64). Cambridge: Cambridge UniversityPress.Worth, W. (1972). A future of choices. Report of the commission on educationalplanning. Edmonton: Queen’s Printer for the Province of Alberta.Zwerling, L.S. (1986). (Ed.). The community college and its critics. New Directionsfor Community Collegs San Fransisco: Jossey-Bass, 54(2).363APPENDIX ASurvey Questionnaire364GRADE 12GRADUATE FOLLOW-UPBritish Columbia Research CorporationVancouver, B.C.365SECTION A2 3 Q4U’ U’ U’ U’LP U’ 0’ U’T U’ U’ U’Educatioml Factor:U’ I didn’t think I had the acaderrdcability necessary to succeed infurther study.U’ I didn’t have the necessary courserequirements for post-secondarystudy.U’ My apphcaiion for admission to apost-secondary institution was• rejected.U’ didn’t neod further education toget the job wanted.GtnQraphit Factnr:U’ didn’t want to attend my local• post-secondary institution.Q5 There was no college withincommuting distance.U’ There was no university withincommuting distance.Financial Factor:0’ I couldnt afford tuition fees.U’ I couldn’t afford the other costs offurther study (e.g., living, travel).U’ I didn’t qualify for financialassistance.U’ I didn’t want to take a loan.U’ I didn’t think post-secondaryeducation was worth the cost.Paroosal Factor:U’ I wanted to work.U’ I wanted to take a break frommy studies.U’ I didn’t want to live away fromhome.U’ lgotajob.U’ I didn’t know what I wanted tostudy,U’ I didn’t enjoy studying,U’ I didn’t think further study ,iould beuseful to me.U’ My parents were Opposed to furtoereducation.ln,tilulionct FactorsU’ I couldn’t get the prooram I wanted,U’ I couldot get into the institution Iwanted.U’ Part-time study was not avaiube.U’ Extra-curricular programs were nota\\’ailable.2. Choose the two MOST IMPORTANT factors which might cause you topursue additional education. (CHECK NO MORE THAN TWO,)U’ If I could afford to go.U’ If I lose my job,U’ If I need further education to get or to keep my job.0’ lit becomes possible to work and take classes part-time.U’ If the program I want becomes available near my home.U’ If a university becomes available near my home.3. In future I plan to enrol in (CHECK AS MANY AS APPROPRIATE):U’ A community college in B.C.U’ A technical or vocational institute in B.C.U’ A university in B.C..U’ The Open Learning Agency (the Open Learning Institute),U’ An institution elsewhere in Canada.U’ An institution outside of Canada.U’ I do not have any plans to attend post-secondary study.4. Which one of the following BEST describes what you are now doing?(CHECK ONE.)U’ Employed full-lime (30 hours or more per week).U’ Employed part-time (tess than 30 hours per week).U’ Presently unemployed.U’ Full-time household/family duties.5. Answer this question with respect to your MAIN employment sincegraduating from secondary school, If you have not been employed at allsince Grade 12, skip to Ouestion 10 (Section C).For your main job since leaving Grade 12 please indicate:a) your occupation or the kind of work you do (e,g.. office clerk,salesperson, auto mechanic, nurse, electronics technician, etc.).(Please specify)b) the nature of the services provided or types of products produced bythe business or industry in which you are working (e.g., appliancemanufacturer, furniture store, service station, hospital, utilitycompany, etc.).(Please specify)Not Part Fuir} Note: Full time = 30 hours or moreoy Time Time j per weekU’ U’ U’ July 1988U’ U’ U’ August 1988U’ U’ U’ September 1988U’ U’ U’ October 1988U’ U’ U’ November 1968U’ U’ U’ December 1988U’ U’ U’ January 1989U’ U’ U’ February t9890’ U’ U’ March 1989U U’ U’ April 1989NOW SKIP TO QUESTION 10 (SECTION C).IF YOU HAVE ROTA TTENDED A POST-SECONOARY INSTITUTIONSINCE LEAViNG GRADE 12. START WITH QUESTION I (SECT1ONA).iF YOU HAVE A17’ENOED A POST-SECONDARY INSTITUTION SINCELEA VINO GRADE 12. EVEN IF YOU HAVE SINCE COMPLETED DRDROPPED OUT OF YOUR STUDIES. START WITH QUESTiON 7(SECTION 5).1. How much did the following factors influence your decision to NOT go tOa post-secondary institution? (CHECK ONE FOR EACH LTNE,)INFLUENCE:Mod- VeryNone Weak erate Strong StrongI IU’ U’ U’ U’0’ U’ U’ U’U’ U’ 0’ U’U’ U’ U’ U’U’ U’ U’ U’U’ U’ U’ U’U’ U’ U’ U’U’ U’ U’ U’U’ U’ U’ U’U’ U’ U’ U’U’ U’ U’ U’U’ U’ U’ U’U’ U’ U’ U’U’ U’ 0’ U’0’ U’ U’ U’U U’ U’ U’U U’ U’ U’U’ U’ U’ U’0’ U’ U’ U’U’ U’ U’ U’6. In which months have you been employed since graduating from Grade 12?(CHECK ONE FOR EACH MONTH.)366ANSWER ONLY IF YOU HAVE ATTENDED A POST-SECONIJARYINSTITUTION SINCE LEAVING GRADE 12.SECTION B7. How much did the following factors influence your decision to enrol inpost-secondary education? (CHECK ONE FOR EACH LINE.)8. What were your main sources of financing for your post-secondaryeducation? (CHECK AS MANY AS APPROPRIATE.)j C’ Direct support from parents or other relatives.C’ Repayable loans from family and triends.C’ Government student assistance program.C’ Scholarships or bursaries offered by pont-secondary institutions.Summer work.C’ Part-time work during the academic year.C’ Earnings from full-lime work (not just summer work).C’ Personal savings.C’ Other (please specify)I 9. Which one of the following BEST describes what you are now doing?(CHECK ONE.)I C’ Full-time student (but not employed).C’ Part-time student (but not employed).C’ Full-time student and employed.C’ Part-lime student and employed.C’ Employed full-time (30 hours or more per week).C’ Employed part-time (less than 30 hours per week).C’ Presently unemployed.study. C’ Full-lime household/family duties.C’ My application for admission to a CONTINUE WITH QUESTION 10 (SECTION C].post-secondary institution wasaccepted.C’ C’ C’ C’ C’ I needed further education to getthe job I wanted.G8ographlc FactorsC’ C’ C’ C’ C’ I wanted to attend my local post-C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’secondary institution.C’ There was a college withincommuting distance.C’ There was a university withincommuting distance.FInancial FactorsC’ I could afford tuition fees.C’ I could afford the other costs offurther study (e.g.. living, travel).C’ I qualified for financial assistance.C’ I was willing to lake a loan.C’ I thought post-secondary educationwas worth the cost.Personal FautoraC’ I didnt want to work.C’ I didrit want to interrupt mystudies.C’ I wanted to live away from home.C’ I didnt get a job.C’ I knew what I wanted to study.C’ I enloy studying.C’ I thought further study would beuseful to me.C’ My parents insisted on furthereducation.Isslitulional FartorsC’ I gol tile program I wanted.C’ I got into the institution I wanted.C’ Part-time study was available.C’ Extra-curricular programs wereavailable.EVER YONE PLEASEANS WEB THE REMAINING QUESTIONS.10. When did you reach your decision to continue or not continue yourstudies after Grade 12? (CHECK ONE.)C’ In Grade 7 or earlier.C’ During Grades 810 11.C’ In Grade 12.C’ Afler completion of Grade 12.C’ I am still undecided.C’ I always knew.11. How important were Ihe following individuals in helping or influencingyou in your plans? (CHECK ONE FOR EACH PERSON.)[ INFLUENCE:Mod- VeryNone Weak erote Strong SlrongC’ C’ C’ C’ C’ Mother (or guardian).C’ C’ C’ C’ C’ Father (or cuardian).C’ C’ C’ C’ C’ Others in your family or relatives.C’ C’ C’ C’ C’ Fhenos (of azout your same age).C’ C’ C’ C’ C’ Seconoary scool teacher.C’ C’ C’ C’ C’ Seconca scnooi counsellor.C’ C’ C’ C’ C’ PosI-secocary instructor.C’ C’ C’ C’ C’ Post-secc.car/ counsellor.C’ C’ C’ C’ C’ Other Iplease soecity)INFLUENCE:Mod- VeryNone Weak erate Strong StrongEducatIonal FactorsC’ C’ C’ C’ C’ I thought I had the academic abilitynecessary 10 succeed in furtherstudy.C’ I had the necessary courserequirements for post-secondaryC’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’C’ C’ C’ C’SECTION C36712. (a) Which of the following sources of information did you use inreaching a decision about what you would do following Grade 12graduation? (CHECK AS MAHYAS APPROPRIATE.)C1 Post-secondary pamphlets or calendars.C’ TV., radio, newspaper or magazine advertising.C’ Representatives of postsecondary institutions visiting yoursecondary school.C4 Visits or field trips to post-secondary institutions.C’ Career information from Canada Employment and Immigration.C6 Career Fairs, Open Houses, or other exhibitions.Q7 Representatives of private industry visiting or lecturing atyour secondary school.C6 Visits or field trips to private industry.C’ None of the above.(b) Of your answers to 12(a) which TWO were the most helpful to you?(CHECK TWO ONLY.)C1 C’ C’ C4 C C C’ C13. How informed are you about each of the following aspects of the post-secondary education system in B.C.? (CHECK ONE FOR EACH LINE.)VeryWellHOW INFORMED:Not Not Mcerat all Very ately WellC’ C C’ C C5 Program offerings.C1 C’ C’ C4 C5 Admission requirements.C’ C’ C’ C4 C’ Admission deadlines.C1 C’ C’ C4 C’ Availability of financial aid.C’ C’ C’ C4 C5 Availability of accommodation.14. Did you receive any scholarships or bursaries for post-secondaryeducation? (CHECK AS MANY AS APPROPRIATE.)C1 Provincial Scholarship.C’ School Distnct Scholarship.C’ Passport to Education.C4 Private Scholarship.C’ Other.C No, I did not.15. For each of the following post-secondary institutions, please indicatewhether you:a) formally applied for entrance (i.e., filled out an application form andsent it in).b) were accepted (granted admission).c) attended since Grade 12.(CHECK AS MANY ASAPPROPRIATE FOR EACHCO LU M N.)At a college in B.C.Al a technical or vocational ir.stitute in(a) (b) (C)Apped Accpted AtteidedB.C.C’ C’ C’ At the Oce. Learnir. Agency (Open LearningInstitute).C4 C4 C4 At a university in B.C..C5 C’ C5 At an institution elsewhere in Canada.C6 C5 C5 At an institution outside Canada.C’ I did not apply to any post-secondaryinstitutions.16. Please respond to the following questions about distance learnig andcorrespondence education. (CHECK ONE FOR EACH LINE.)[Yes NoC1 C’ Do you think you would like distance learning?C’ C’ Have you ever taken education by correspondence?C’ C’ Have you ever heard of the Open Learning Agency?C’ C’ Did you consider applying to the Open Learning Agency?17. In which ways do you think post-secondary education would help you?(CHECK ONE FOR EACH LINE.)WOULD IT HELP YOU:Definitely Probably Not Yes,Not Not Certain Probably DefinitelyI I I IC1 C’ C’ C4 C’C1 C’ C’ C4 C’ To prepare me for ajob.C’ C’ C’ C4 C’ To increase myincome.C’ C’ C’ C C’ To make me a morewell-informed citizen.C1 C’ C’ C C’ To provide me withmore opportunities forrecreation and/orsocial activities.C’ C’ C’ C4 C’ To give me a widercheice of jobs.18. Using the 2 columns below, please indicate:a) the highest level of education that you WOULD LIKE to attain:b) the highest level of education you WOULD EXPECT to attain, asthings stand now.(a) (b)Would Would (CHECK ONE FOR EACH COLUMN.)Like ExoectC’ C1 Grade 12 graduation.C’ C’ Apprenticeship certificate.C’ C’ One or two year ciploma from a college or technicalinstitute.C4 C4 Bachelor’s decree.C’ C’ Professional decree 11am, mecicine. teaching.dentistry, etc.)C5 C5 Graduate degree IMasters or Dcn:orate Degree).To become bettereducated.Continued over36819. Please indicate your level of satisfaction with the following aspects ofsecondary school? (CHECK ONE FOR EACH LINE.)LSATISFACTION:Very Mod-Low Low erate HighT T T TC’ C2 Q3 C4C’ C2 C C4C’ C2 C3 C4C’ C2 C3 C4matter.The quality of leaching.Subjects/course content.Emphasis given to academicsubjects (e.g., math, science,English. etc.).C’ C2 C3 C4 C’ Method of assessment (e.g.,exams).C1 C2 C C4 C’ Appropriateness of home’,vorkassignments.C’ C2 C C4 C’ Relevance of work skillstaught.C1 C2 C3 C C’ Sports and recreationalactivities.C3 C4 C’ School cultural activities(e.g., music, art, drama. etc.).C3 C4 C’ School social life.C3 C4 C’ Preparation for career andpost-secondary opportunities.C3 C4 C’ Overall.20. Did you participate in any of the following types of activities duringyour years in secondary school? (CHECK ONE FOR EACH LINE.)[Sometimes OftenC’ C’ C3 Athletic teams.C’ C2 C3 Band, drama or dance.C’ C2 C3 School newspaper, yearbook, annual.C’ C2 C’ Student council.C’ C2 C3 Other chibs (e.g., photography, crafts, chess.science, debating, etc.).C’ C2 C3 Community or church youth organizations(e.g.. YMCA/YWCA, Scouts, Guides. etc.).21. What is the highest level of education completed by your Mother andFather (or legal guardian)? (CHECf( ONE FOR EACH PARENT.)Mother Father IC’ C’ Elementary scnool. less than Grade 8.C2 C’ Some secondary school.C3 C’ Graduated trcm seconoary school.C4 C4 Apprenticesnip. trade or vocational school.C’ C’ Community College.C’ C’ Some university.C C’ Completed Bucnelors or Professional Degree.C’ C’ Completes Masters or Doctorate Degree.C’ C’ Not applica::e.22. Ptease answer the following questions about your Mother and yourFather (or legal guardian). (CHECK ONE FOR EACH PARENT.):a) What is their current status of employment?Fatherb) If employed, what is the occupation or the kind of work they usually door did. it now retired or deceased? (e.g., office clerk, salesperson, automechanic, nurse, electronics technician, lawyer. etc.).Mother_______________________Father______________________c) If employed, what is the nature of the sernices provided or type ofproducts produced by the business or industry in ‘.vhich they usuallywork(ed)? (e.g., appliance manufacturer, furniture store, service stalion.hospital, utility company, legal firm. etc.).Mother Father23. Please indicate your cultural/ethnic background. (Some examples ofcultural groups are: Scottish. Native Indian. Canadian, German.Japanese, Japanese-Canadian, etc.)I belong to the__________cultural group.24. Is English the main language your parent(s) speak at home? (CHECKONE.)C’ YesC’ NoThank you for your cooperation. Allresoonses wilt be kept confidential.Please use the postage-paid returnenvelope provided.Comments are welcome overleaf.VeryHighC’C’C’C’Teachers’ knowledge of subjectC’ Employed/Self-employedC2 Not employedC3 HomemakerC4 RetiredC’ DeceasedC’ Other (please specify)C’ Employed/Self-employedC2 Not employedC’ HomemakerC4 RetiredC’ DeceasedC’ Other (please specify)C’ C’C’ C’C’ C2C’ C2Comments?369YOUR COMMENTS ARE INVITED.OFFICE USE ONLYfor statistical purposes only370GRADE 12 GRADUATE SURVEt’Several days ago we mailed a questionnaire for you to complete. This was part of aprovince-wide research study being undertaken by the British Columbia Research Corporationon behalf of the B.C. Ministry of Education and the B.C. Ministry of Advanced Educa:ionand Job Training.If you have compieed and returned this questionnaire. may we take this opportunity tothank you.If you have not yet returned the completed form, we ask that you take a few minutes now todo this.Your assistance s very much appreciated.Thank you.8RITISH COLUMBIA RESEARCH CORPORATIONGien C. ForresterResearch ConsultantGRADE 12 GRADUATE SURVEY54G HOWE STREETVANCOUVER. B.C.VEC 2C5371APPENDIX BRates of Response and Non-responseTablel.a.EligibifityforUniversityEntranceEligibleMetropolitanPost-secondaryParticipantsRatesof ResponseandNonresponseBorderlineNotEligibleresp-nonresp-undeliv-rowondentondenterabletotalresp-nonresp-undeliv-rowondentondenterabletotalresp-nonresp-undeliv-rowondentondenterabletotalage 17 18 19 20 malefemaleUBCelig.yesno60.334.55.262.832.15.258.640.21.157.142.90x2-5.15d.f.-6p>0559.037.43.665.029.15.8x2-945d.f.-2p<.0162.932.24.955.641.13.3x2-3.12d.f.-2p>0533.333.333.352.842.05.251.842.95.457.114.328.6x2-11.78d.f.-6p>05x2-6.94d.f.-2p<.0591.2008.852.641.533.358.38.352.840.37.048.645.06.348.048.04.0x2-3.03d.f.-6p>05x2-13.68d.f.-2p<.0100051.342.06.82.273.020.3 4.650.050.0n638338491025205162%62.233.04.8100.052.641.5233905.9100.028123051.342.0sex5.785.2 8.5.746.453.6375486.8100.0.883.114.4 1.846.548.058.934.943.849.66.658.834.36.95.650.86.349.2005.9100.00100.0c?) -1 L’)Tablel.a.MetropolitanPost-secondaryParticipantsEligibifityforUniversityEntranceEligibleBorderlineNotEligibleresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowondentondenterabletotalondentondenterabletotalondentondenterabletotaln6383384910252051622339028123037548%62233.04.8100.052641.55.9100.051.34206.8100.0UBCgrade.062232.45.43.650.035.015.05.152.440.76.992.71.0to1.40000000050.050.00.41.Stol.966.733.30.351.940.77.46.936.857.95.36.92.Oto2.450.048.02.04.952842,05.287.900002.5to2.957.437.84.840.3000000003.0to3.465.629.45.031.2000000003.5to4.069.825.25.019.700000000x2-17.47x2-3.42x2-4d.f.-10d.f.-4d.f.-4p>.05p>.05p>.05UVicelig.yes6223294.990.700000000no63.233.73.29.352641.55.9100.051.342.06.8100.0x2-0.61d.f.-2p>05UVicgrade.063.231.65.33.752234.813.05.952340.96.992.91.0to1.4000033.366.70.836.454.59.1201.5tol.9000054.940.54.821.539.357.13.65.12.0to2.463.235.11.85.65214215.771.800002.5to2.954.639.85.636.8000000003.Oto3.467.729.52.831.4000000003.5to4.066.726.46.922.500000000x2-21.87x2-3.42x2-3.98d.f.-8d.f.-6d.f.-4p<.01p>05p>05Tablel.a.MetropolitanPost-secondaryParticipantsEligibifityforUniversityEntranceEligibleBorderlineNotEligibleresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowondentondenterabletotalondentondenterabletotalondentondenterabletotaln6383384910252051622339028123037548%62233.04.8100.052.641.55.9100.051.342.06.8100.0SFUelig.yes6223295.094.300000000no63.834.51.75.752641.55.9100.051.342.06.8100.0x2-1.27d.f.-2p>05SFUgrade.0100.000.166.733,30.852.240.96.992.01.0to1.4000033.366.70.841.750.08.32.21.5to1.9000054.840.54.821.540.656.33.15.82.Oto2.463.235.11.85.652.041.76.376.900002.5to2.954.839.35.938.2000000003.Oto3.467.829.52.7324000000003.5to4.066.327.26.623.700000000x2-21.51x2-1.58x2-3.58d.f.-8d.f.-6d.f.-4p<.01p>05p>05SchoolDistrictx2-28.19x2-36.32x2-4396d.f.-30d.f.-30d.f.-32p>.05p>05p>05CollegeRegionx2-8.8x2x2-8.67d.f.-8d.f.-8d.f.-8p>05p>05p>05Tablelb.Urban/RuralPost-secondaryParticipantsRatesofResponseandNonresponseEligibilityforUniversityEntranceEligibleBorderlineNotEligibleresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowondentondenterabletotalondentondenterabletotalondentondenterabletotaln7602916111121551072228431926535619%68.326.25.5100.054.637.77.7100.051.542.85.7100.0age1775.022.22.83.245.545.59.13.957.142.901.11869.325.74.991.256.835.87.485.655.938.45.776.61949.136.414.54.937.951.710.310.239.356.34.518.12042.928.628.6.6100.000023.165.411.54.2x2-22.59x2x2-21.39d.f.-6d.f.-6d.f.-6<.ocnp>05p<.01sexmale61.733.35.046.848.542.49.146.542.352.55.249.3female74.219.95.953.259.933.66.653.560.533.46.150.7x2-25.49x2-373x2-23.12d.f.-2d.f.-2d.f.-2p<.001p>05p<.001UBCelig.yes68.726.35.093.600000000no63.423.91276.454.637.77.7100.051542.85.7100.0x2-557d.f.-2p<.05C)) C)]TableTb.Urban/ruralPost-secondaryParticipantsEligibilityforUniversityEntranceEligibleBorderlineNotEligibleresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowondentondenterabletotalondentondenterabletotalondentondenterabletotaln7602916111121551072228431926535619%68.326.25.5100.054.637.77.7100.051.542.85.7100.0UBCgrade.071.47.121.41.366.733.303.251.542.75.895.01.Otol.40000000050.050.00.31.Stol.975.0025.0.452.642.15.36.751.744.83.44.72.Oto2.460.430.29.44.854.337.58.290.100002.5to2.962.43205.639.9000000003.0to3.472.424.33.434.8000000003.5to4.075.218.16.718.900000000x2-34.52x2-1.32x2-d.f.-10d.f.-4d.f.-4p<.001p>.05p>05UVicelig.yes69.525.84.790.200000000no57.829.41289.854.637.77.7100.051.542.85.7100.0x2-14.36d.f.-2p<.001UVicgrade.073.710.515.81.760.040.003.551.542.75.895.01.0to1.4000057.142.902.566.733.301.51.5tol.9100.000.152032.016.026.445.550.04.53.62.0to2.453.933.71248.055.239.65.267.600002.5to2.967.428.44.139.2000000003.0to3.468.626.35.030.4000000003.5to4.074.420.15.220.600000000x2-25.42x2-10.57x2-1.59d.f.-10d.f.-6d.f.-4p<.01p>05p>05Tablelb.Urban/ruralPost-secondaryParticipantsEligibifityforUniversityEntranceEligibleBorderlineNotEligibleresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowondentondenterabletotalondentondenterabletotalondentondenterabletotaln7602916111121551072228431926535619%68.326.25.5100.054.637.77.7100.051.542.85.7100.0SFUelig.yes69.525.64.991.500000000no55.832.611.68.554.637.77.7100.051.542.85.7100.0x2-11.08d.f.-2p<.01SFUgrade.080.020.00.40100.00.451.542.75.895.01.Otol.4000057.142.902.566.733.301.51.5to1.9100.000.152032.216.026.445.550.04.53.62.Oto2.453.933.712.48.055.739.35.070.800002.5to2.967.028.24.839.6000000003.0to3.468.926.24.930.9000000003.5to4.075.119.75.221.000000000x2-19.90x2-11.77x2-1.59d.f.-10d.f.-6d.f.-4p<.05p>05p>05SchoolDistrictx2-44.91x2-5230x2-93d.f.-56d.f.-56d.f.-58p>05p>.05p>05CollegeRegionx2-9.46x2-1226x2-11.18d.f.-8d.f.-8d.f.-8p>05p>05p>05TableIc.RemotePost-secondaryParticipantsRatesofResponseandNonresponseEligibilityforUniversityEntranceEligibleBorderlineNotEligibleresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowondentondenterabletotalondentondenterabletotalondentondenterabletotaln450188296678232712131023446590%67.528.24.3100.067.826.45.8100.053.539.77.8100.0age 1773.126.903.9100.000.840.020.040.0.81867.927.94.289.868.326.75.083.557.235.07.772.51956.134.19.86.156.331.312.513.240.253.86.122.420100.000.1100.0002.540.048.012.04.2x2-5.89x2-373x2-24.15d.f.-6d.f.-6d.f.-6p>05p>05p<.001sexmale61.034.24.843.854.536.49.145.548.045.86.246.6female72.523.54.056.278.818.23.054.556.534.39.253.4x2-10.27x2-8.26x2-8.67d.f.-2d.f,-2d.f.-2p<.01p<.05p<.05UBCelig.yes67.927.54.694.500000000no59.540.505.567.826.45.8100.052.539.77.8100.0x2-4.20d.f.-2p>05c))TableLc.RemotePost-secondaryParticipantsEligibifityforUniversityEntranceEligibleBorderlineNotEligibleresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowondentondenterabletotalondentondenterabletotalondentondenterabletotaln45018829667823271213102344659067.528.24.3100.067.826.45.8100.053.539.77.8100.0UBCgrade.033.366.70.925.075.003.352739.47.992.41.0to1.40000100.000.840.060.00.81.5tol.966.733.30.470.020.010.08.352540.07.56.82.0to2.464.335.704.268.925.55.787.600002.5to2.962632.64.840.5000000003.0to3.469.524.85.833.9000000003.5to4.076.121.62.220.100000000x2-16.36x2-5.88x2-1.08d.f.-10d.f.-6d.f.-4p>05p>05p>05UVicelig.yes68.827,04.391.200000000no54.240.75.18.867.826.45.8100.052539.77.8100.0x2-sd.f.-2p>05UVicgrade.033.366.70.957.142.905.852.739.47.992.51.Otol.40000100.000.838.955.65.63.11.5to1.9000074.420.94.735.557.734.67.74.42.0to2.456.637.75.77.964.328.67.157.900002.5to2.963.231.45.439.1000000003.0to3.472.323.14.629.2000000003.5to4.073.724.32.022.800000000x2-15.74x2-3.05x2-2.22d.f.-8d.f.-4d.f.-4p<.05p>05p>05TableIc.RemotePost-secondaiyParticipantsEligibilityforUniversityEntranceEligibleBorderlineNotEligibleresp-nonresp-nndeliv-rowresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowondentondenterabletotalondentondenterabletotalondentondenterabletotaln450188296678232712131023446590%67.528.24.3100.067.826.45.8100.053.539.77.8100.0SFUelig.yes68.427.44.292.100000000no56.637.75.77.967.826.45.8100.052539.77.8100.0x2-3.10d.f.-2p>05SFUgrade.00000100.0002.552739.47.992.51.0to1.40000100.000.838.955.65.63.11.5to1.9000074.420.94.735.557.734.67.74.42.0to2.456.637.75.77.962.231.16.861.200002.5to2.963.331.45.339.6000000003.0to3.471.623.94.629.5000000003.5to4.073.224.82.022.900000000x2-10.27x2-3.84x2-2.22d.f.-6d.f.-6d.f.-4p>05p>05p>05SchoolDistrictx2-41.50x2-52.52x2-60.40d.f.-52d.f.-50d.f.-52p>05p>05p>05CollegeRegion-6.56-11.46x2-10.28d.f.-8d.f.-8d.f.-8p>05p>05p>05TableILa.EligibilityforUniversityEntranceEligibleMetropolitanPost-secondaryNon-participantsRatesofResponseandNonresponseBorderlineNotEligibleresp-nonresp-undeliv-rowondentondenterabletotalresp-nonresp-undeliv-rowondentondenterabletotalresp-nonresp-undeliv-rowondentondenterabletotaln % age16 17 18 19 202161203537158.232.39.4100.000100.0.368.426.35.35.158.332.39.486.050.040.010.08.1100.000.5x2-12.84d.f.-8p>.050100.0025.037.537.540.151.28.748.548.53.0000x2-10.99d.f.-6p>0500064.314.321.442.148.29.830.956.412.747.445.67.0x2-16.14d.f.-6p<.0501.671.220.7 6.5malefemale53.936.561.828.9x2-2.63d.f.-2p>059.645.09.355.033.359.748.340.8x2-8.86d.f.-2p<.057.051.810.848.235.854.210.044.744.510.7x2-8.57d.f.-2p<.0547.952.160.430.844.042.0x2-494d.f.-2p>058.786.514.013.500040.549.110.4101126222493544309187540.650.68.8100.040.549.110.4100.0sex.4 3.283.113.3 0UBCelig.yesno0040.650.6008.8100.00100.0cJTableha.MetropolitanPost-secondaryNon-participantsEligibilityforUniversityEntranceEligibleresp-nonresp-undeliv.rowondentondenterabletotalBorderlineresp-nonresp-undeliv-rowondentondenterabletotalNotEligibleresp-nonresp-undeliv-rowondentondenterabletotaln %21612058.232.3353719.4100.010112640.650.6222498.8100.03544309140.549.110.4875100.0UVicgrade.0 1.0to1.41.5to1.92.0to2.42.5to2.93.0to3.43.5to4.056.833.110.166.727.85.6x2-2.19d.f.-2p>.0557.138.14.800075.0025.072424.13.453.736.99.462026.112056.634.29.2x2 d.f.-10p>.055.7 01.17.840.224.820.5x2-2.19d.f.-6p>055.6.429.364.7 0 0 000040.549.110.440.948.610.530.060.010.023.570.65.9000000000000x2-sd.f.-4p>0596.9 1.11.9 0 0 0 05.0 033.318.5 6.59.314.0UBCgrade.0 1.0to1.41.5to1.92.0to2.42.5to2.93.0to3.43.5to4.0UVicelig.yesno55.040.000066.740.740.757.535.964.426.360.026.0x2-15.70d.f.-10p>0518.2 017.4 7.4 0 0 05.4 0.87.341.231.813.585.414.64.4 0 9.286.3 0 0 027.354.50030.452.242350.2000000x2 d.f.-4p>.050040.650.640.948.610.514.371.414.330.065.05.0000000000000x2-4.22d.f.-4p>0596.9 .8 2.3 0 0 0 0 0100.0008.8100.028.657.114.30100.0039.753.46.842248.49.3000000000TableTEa.MetropolitanPost-seconaryNon-participantsEligibilityforUniversityEntranceEligibleNotEligibleresp-nonresp-undeliv-rowondentondenterabletotalresp-nonresp-undeliv-rowondentondenterabletotalresp-nonresp-undeliv-rowondentondenterabletotal56.733.59.873.520.65.9x2-3.60d.f.-2p>05000040.650.68.8100.03544309187540.549.110.4100.0000040.549.110.4100.0SFUgrade.0 1.0to1.41.5to1.92.0to2.42.5to2.93.0to3.43.5to4.0100.00000075.0025.072.424.13.454.136.39.660.228.611.257.334.18.5x2-8.15d.f.-10p>.05x2-27.99d.f.-30p>05.3 01.17.842,326.422.1x2-2.23d.f.-6p>05x2-5.65d.f.-8p>051.2.429.369.1 0 0 041.148.510.430.060.010.019.071.49.5000000000000x2-5.20d.f.-4p>05x2-20.18d.f.-32p>05x2-5.32d.f.-8p>0596.5 1.12.4 0 0 0 0BorderlineSFUelig.yesnon2161203537110112622249%58.232.39.4100.040.650.68.8100.090.8 9.233.366.700100.0039.753.46.841.348.89.9000000000SchoolDistrictCollegeRegionx2-17.97d.f.-30p>05x2-4.17d.f.-8p>05TableJIb.EligibilityforUniversityEntranceEligibleUrban/ruralPost-secondaiyNon-participantsRatesof ResponseandNonresponseBorderlineNotEligibleresp-nonresp-undeliv-rowondentondenterabletotalresp-nonresp-undeliv-rowondentondenterabletotalresp-nonresp-undeliv-rowondentondenterabletotaln % age16 17 18 19 2029818756.935.7x2-8.54d.f.-8p>05395247.4100.000050.050.0050.339.610.156.337.56.3066.733.3x2-4.30d.f.-6p>05190100.0 01.188.9 8.41.646052111542.047.510.500036.445.518.243.946.010.237.651.411.037.151.611.3x2-45d.f.-6p>0510%100.0 01.070.123.3 5.7malefemale51.740.261.931.3x2-554d.f.-2p>058.149.46.850.646.742.410.953.137.89.2x2-77d.f.-2p>0548.451.640.450.09.643.645.111.4x2-2.86d.f.-2p>0550.249.8UBCelig.yesno58.034.944.244.2x2-337d.f.-2p>05100.000.242.942.914.35.357.735.56.886.663.627.39.16.325.062.512.51.595761950.040.010.0sex7.191.8000011.68.250.040.010.0100.0000042047.510.5100.0C))TableILb.Urban/ruralPost-secondaryNon-participantsEligibilityforUniversityEntranceEligibleresp-nonresp-undeliv-rowondentondenterabletotalresp-nonresp-undeliv-rowondentondenterabletotalresp-nonresp-undeliv-rowondentondenterabletotal46052111510%42.047.510.5100.0BorderlineNotEligiblen2981873952.4957619190%56.935.774100.050.040.010.0100.0UBCgrade.050.033.316.71.162537.504.241.647.710.797.31.0to1.400000000100000.11.5to1.9000046.753.307.955.241.43.42.62.Oto2.443.245.910.87.149.738.911.487.900002.5to2955.936.97.2424000000003.0to3.453.138.18.830.5000000003.5to4.070.725.34.018.900000000x2-1268x2-3.63x2-4.28d.f.-8d.f.-4d.f.-4p>.05p>.05p>.05UVicelig.yes56.435.67.988.900000000no60.336.23.411.150.040,00100.042.047.510.5100.0x2-1.54d.f.-2p>05UVicgrade.042942914.31.360.040.005.341.647.710.797.31.Otol.4000050.050.002.142.942.914.3.61.5to1.9100.000.454.933.31t826.860.939.102.12.Oto2.461.236.7209.447.242.410.465.800002.5to2.951.337.910.742.7000000003.0to3.456.236.57.326.1000000003.5to4.067.629.52920.000000000x2-15.40x2-3.06x2-49d.f.-10d.f.-6d.f.-4p>05p>05p>05QiTableII.b.Urban/ruralPost-secondaryNon-pafficipantsEligibilityforUniversityEntranceEligibleresp-nonresp-undeliv-rowondentondenterabletotalBorderlineresp-nonresp-undeliv-rowondentondenterabletotalNotEligibleresp-nonresp-undeliv-rowondentondenterabletotal56.435.661.536.5x2-2.59d,f.-2p>.058.190.11.99.900050.040.000100.046052111510%42047.510.5100.0SFUgrade.0 1.0to1.41.5to1.92.0to2.42.5to2.93.0to3.43.5to4.00100.00000100.00061.236.72051.537.411.055.437.47.267.929.228x2-17.36d.f.-10p>05x2-5953d.f.-58p>.05x2-1184d.f.-8p>05.2 0.49.443.326.520.2x2-1.97d.f.-6p>05x2-69.81d.f.-52p>05x2-14.80d.f.-8p>051.12.126.870.0 0 0 041.547.810.797.242942.914.3.662537.50220000000000000000x2-5.68d.f.-4P>05x2-6203d.f.-58P>05x2-4.10d.f.-8p>05n % SFUelig.yesno2981873952495761919056.935.77.4100.050.040.010.0100.0000042047.510.5100.050.050.0050.050.0054.933.311.848.142.19.8000000000SchoolDistrictColiegeRegionTableTIc,RemotePost-secondaryNon-partidpantsRatesofResponseandNonresponseEligibilityforUniversityEntranceEligibleBorderlineNotEligiblereSp-nonresp-undeliv-rowresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowondentondenterabletotalondentondenterabletotalondentondenterabletotaln17911024313453938739747171939%57.235.17.7100.051.744.83.4100.042.350.27.6100.0age16100.000.3000000001766.733.302.9100.0001.175.025.001.31857.035.77.486.947.947.94.183.945.648.06.468.31954.832.312.99.969.230.8014.936.254.98.923.9200000000024.259.716.16.6x2-2.86x2-3.18x2-24.29d.f.-6d.f.-4d.f.-6p>05p>05p<.001sexmale53.237.39.550.540.057.52.546.038.752.88.652.1female61.332.95.849.561.734.04.354.046.247.36.447.9x2-2.80x2-4.81x2-5.98d.f.-2d.f.-2d.f.-2p>05p>05p>05UBCelig.yes58.834.07.193.900000000no31.652.615.86.151.744.83.4100.042.350.27.6100.0x2-5.82d.f.-2p>05TableILc.RemotePost-secondaryNon-participantsEligibilityforUniversityEntranceEligibleBorderlineNotEligibleresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowondentondenterabletotalondentondenterabletotalondentondenterabletotaln17911024313453938739747171939%57.235.17.7100.051.744.83.4100.042.350.27.6100.0UBCgrade.050.0050.0.6000042.550.17.596.81.Otol.4000000000100.0.21.5to1.9000050.050.006.939.357.13.63.02.0to2.429.458.811.85.451.944.43.793.100002.5to2.959.234.76.147.0000000003.0to3.459.834.06.231.0000000003.5to4.056.032.012.016.000000000x2-13.15x2-.26x2-23.39d.f.-8d.f.-2d.f.-4p>.05p>05p<.001UVicelig.yes57.834.08.285.600000000no53.342.24.414.451.744.83.4100.042.350.27.6100.0x2-1.60d.f.-2p>.05UVicgrade.042.942914.32250.050.002.342.450.17.596.91.Otol.40000000075.012.512.5.91.5to1.9000040.056.0028.723.866.79.52.22.0to2.455.34212.612156.740.03.369.000002.5to2.958.134.17.841.2000000003.0to3.456.034.59.526.8000000003.5to4.060.03277.317.600000000x2-3.22x2-2.06x2-7.50d.f.-8d.f.-4d.f.-4p>05p>05p>05TableILc.RemotePost-secondaryNon-participantsEligibifityforUniversityEntranceEligibleBorderlineNotEligibleresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowresp-nonresp-undeliv-rowondentondenterabletotalondentondenterabletotalondentondenterabletotaln17911024313453938739747171939%57.235.17.7100.051.744.83.4100.042.350.27.6100.0SFUelig.yes57.833.78.586.300000000no53.544.22.313.751.744.83.4100.042350.27.6100.0x2-3.13d.f.-2p>05SFUgrade.040.060.001.650.050.002.342.550.17.596.81.0to1.40000000075.012.512.5.91.5to1.900012140.056.04.028.722768.29.12.32.0to2.455.34212612156.740.03.369.000002.5to2.958.533.87.741.5000000003.Oto3.455.334.110.627.2000000003.5to4.060.03277.317.600000000x2-4.63x2-2.06x2-8.04d.f.-8d.f.-4d.f.-4p>05p>05p>05SchoolDistrictx2-58.01x2-38.66x2-66.71d.f.-50d.f.-38d.f.-54p>05p>.05p>05CollegeRegioncyDx2-19.43x2-10.32x2-7.67d.f.-8d.f.-8d.f.-8p<.05p>05p>05390APPENDIX CInterview Data Collection391Superintendent of Schools,School District No. X,B.C.September, 1989Dear M.___________Further to our telephone conversation, I am writing to request permissionto interview students in School District X as part of my doctoral research.In this study, I intend to explore with current Grade 12 students how andwhy decisions regarding post-high school destinations are made. In order toaccomplish this, I plan to conduct interviews with a sample of Grade 12 studentswho are in the process of making decisions regarding post-high schooldestinations.I would like to interview fifteen Grade 12 students from one school inSchool District X. Student participants will be selected for this study, on therecommendation of senior school personnel (i.e. principal, guidancecounsellors), based on their 1) willingness to participate in the study, 2)eligibility to graduate from Grade 12 in June 1990 and likelihood of doing so,and 3) ability to contribute to an understanding of the processes of decisionmaking regarding the various post-high school destinations. In this sample, Ihope to capture students who are not likely continue on to post-secondaryeducation as well as those who are likely to continue.I wish to conduct face-to-face, semi-structured interviews, approximatelyone hour in length, during the week of October X, 1989. It is my intention toconduct follow-up interviews with the same group of student participants inApril 1990.In order to proceed with these interviews, I require a letter of consent fromyou to present to The University of British Columbia Ethics Committee. Toexpedite the completion of this task, I have enclosed a consent form and returnenvelope. I would appreciate if you could complete the form and return it to meat your earliest convenience. Once I have received your consent to conduct theinterviews, I will call you to make specific arrangements.Please find attached to this letter a more complete description of my study.If you would like further information, please contact me at 738-1384 or Dr. JohnDennison at 228-5252. I thank you for your interest in my study and I lookforward to meeting you. I would be pleased to discuss with you the details ofany aspect of this study, and upon completion of the study, to share the findingswith you.Yours sincerely,Lesley Andres Bellamy392To: Lesley Andres Bellamy,Department of Administrative, Adult and Higher Education,University of British Columbia,2125 Main Mall,Vancouver, B.C. V6T 1Z5Re: Grade 12 Students’ Post-High School Destinations, Determinants andDecisions Study__________Yes, you have permission to conduct research in thisdistrict as outlined in your recent letter.Please contact me to provide further information about the study.No, I am not able to grant permission.Additional comments:District Superintendent of SchoolsS.D. (393Principal,Secondary School,B.C.October, 1989Dear M._________Further to our telephone conversation, please find enclosed a letter entitled“Invitation to participate in a research study’. This type of letter is required bythe University of British Columbia Ethics Committee for the recruitment ofstudents for this study. Please feel free to alter this letter as necessary to mosteffectively accomplish this recruitment task. I have also enclosed both studentconsent forms and parental consent forms. If required, could you please askstudents to have their parents complete this form.I thank you for your interest in my study and I look forward to meetingyou on October X. I would be pleased to discuss with you the details of anyaspect of this study, and upon its completion, to share the findings with you.Yours sincerely,Lesley Andres Bellamy394Invitation to Participate in a Research StudyDate:_______________Dear________________A graduate student from the University of British Columbia, LesleyBellamy, is conducting a research project entitled “Transition from High School”.In this study, she wishes to explore with grade 12 students the kinds of decisionsstudents face regarding their post-high school destinations, and how and whythese decisions are made. In order to accomplish this, she plans to conductinterviews with a sample of Grade 12 students who are in the process of makingplans for next year.Please consider this letter as an invitation to participate in the researchstudy. Your participation in this study is voluntary. You are not under anyobligation to participate.Participation in this study will involve two interviews, each approximatelyone hour in length. The first interview will take place during the week ofOctober____.A follow-up interview will take place in April. Interviews will bescheduled at a time convenient to the participants. Interviews will be taped.Please be assured that the data from the interviews will be treated in aconfidential manner; that is, only the researcher and her research committee willhave access to the interview data. You will not be identified by name on tapes ortranscripts or in any reports or publications resulting from this study.During the interviews you are entitled to receive answers to any questionsthat you may have regarding the interview process. You may refuse toparticipate or withdraw at any time during this research project. Refusal toparticipate or withdrawal from this project will in no way affect your academicstanding.Please read and complete the enclosed consent form. If you wish toparticipate in this study, sign Item 1. If you do not wish to participate in thisstudy, sign item 2. Please return the consent form to my office as soon aspossible.Thank-you.Principal395Consent FormTitle of the study: “Transition from High School: Destinations,Determinants, and Decisions”.Researcher: Lesley Bellamy (telephone 228-2923 or 7384384)I understand that the purpose of this project is to explore what the kind ofchoices Grade 12 students make regarding their post-high school destinationsand how and why these decisions are made. I am aware that participation in thisstudy involves two interviews, each approximately one hour in length.I have been assured that the data from the interviews will be treated in aconfidential manner; that is, only the researcher and her research committee willhave access to the interview data. I will not be identified by name on tapes ortranscripts or in any reports or publications resulting from this study.I understand that at any time during the interviews I am entitled to receiveanswers to any questions that I may have regarding the interviews and relatedquestions. Also, I understand that I may refuse to participate or withdraw at anytime during this research project. Refusal to participate or withdrawal from thisproject will in no way affect my academic standing.Please sign one of items 1 or 2.1. On the basis of the above, I consent to participate in this study and Iacknowledge receipt of a copy of this agreement.Signature:__________________Date:__________________2. On the basis of the above, I do not consent to participate in this study.Signature:_Date:_396Parental Consent FormTitle of the study: “Transition from High School: Destinations,Determinants, and Decisions”.Researcher: Lesley Bellamy (telephone 228-2923 or 738-1384)I understand that the purpose of this project is to explore what the kind ofchoices Grade 12 students make regarding their post-high school destinationsand how and why these decisions are made. I am aware that participation in thisstudy involves two interviews, each approximately one hour in length.I have been assured that the data from the interviews will be treated in aconfidential manner; that is, only the researcher and her research committee willhave access to the interview data. My daughter/son will not be identified byname on tapes or transcripts or in any reports or publications resulting from thisstudy.I understand that at any time during the interviews I am entitled to receiveanswers to any questions that I may have regarding the interviews and relatedquestions. Also, I understand that I may refuse permission for mydaughter/son’s participation or withdraw her/his participation at any timeduring this research project. Refusal to participate or withdrawal from thisproject will in no way affect my daughter/son’s academic standing.Please sign one of items 1 or 2.1. On the basis of the above, I consent to my daughter/son’s participation inthis study and I acknowledge receipt of a copy of this agreement.Signature:_____________________Date:_________________2. On the basis of the above, I do not consent to my daughter/son’sparticipation in this study.Signature:________Date:________397Guiding Questions for InterviewsInterview 1 - October 1989As you already know, I am interested in hearing about what you are going to donext year. Perhaps we could start there.How did you arrive at those plans (or that choice)?Have you considered anything else? What else might you do?How much have you thought about this?(If planning to go on to post-secondary education) Have you ever thought at allabout not going on to post-secondary, instead ending at Grade 12 and going rightinto the work world?(If planning to go on to university) Have you ever thought about going to acommunity college? Explain.(If planning to go on to college) Have you ever thought about going to auniversity? Explain.(If not planning to go on to post-secondary education). Have you ever thoughtabout going to post-secondary? Explain.Do you have a career goal in mind? How will what you do next year help youreach this goal?What have you used to help you to plan for next year? What sources ofinformation have you used? Are there other sources of information available?Who can/do you talk to about your plans? Who has helped you the most? Howhave they helped?Have you used the C.H.O.I.C.E.S. program? Was it useful?Tell me about your best friends’ plans for next year. Do you and your friends talkvery much about what you’re going to do next year? Do their plans influenceyour plans?What do you think that post-secondary education will/would do for you interms of your life? What do you want to get out of post-secondary education?What will/would life be like without post-secondary education?398What do you see as getting in your way, or preventing you from carrying outyour plans? What have you done/will you do to deal with these constraints?What is your parents’ educational background/occupational background?I would like you to draw a life line and place yourself on it. Mark the importantdecisions that you have made so far in your life. Once you have done that, markthe important decisions that you will be making in the future. Then we willdiscuss them.Which out of all these is the most important decision?In Grade 10 you had to choose which courses you were going to take in Grade 11and 12. Do you remember doing that? How did those choices turn out? Werethey good choices, or do you wish you would have taken something else now?Have they limited you? If so, how?Grade 12 is almost half over. I would like for you to describe to me what it feelslike to be in your shoes right now (re: making your post-high school plans).If I’m trying to understand how gr.12 students make decisions, is there anythingthat I should have asked that I didn’t, is there anything that I left out?Is there anything you want to ask me?Interview 2- May 1990You have read the transcript from our last discussion. Let’s discuss it.- was it accurate? Is it still accurate?- was there anything you wanted to ask me or clarify since that interview?- what should be changed?Was there anything from the last interview that was particularly striking?What has happened since last November in regard to your plans for next year?What have you done to get ready for next year?I would like for you to describe what you would like to do next year, andcompare it to what you are going to do.What factors have helped you with your decision (facilitating factors)? Whichfactors have worked against you (constraining factors)?399Let’s talk about the courses you’ve done in the last two years and your marks.What worries or concerns you about next year? Why?What are you looking forward to? Why?Do you think that you are making a rational choice? Why? What would be a ‘notrational’ choice? What does the word ‘rational’ mean to you?For you next year, 1. university, 2. community college 3. work is: a. impossible b.possible c. natural. Discuss.What role do the following play in your plans for next year?- future rewards (e.g. income, lifestyle)- preferencesDid you calculate expected return on your investment?What do your parents think about your plans?Describe your idea of “the good life”. Do you think that your plans for next yearwill help you live this life? How?What does the work world, say ten years down the road, look like to you?Do you think your life (including work life) will be different from your parents?How?In terms of your future, how much control do you think you have?Have you used the C.H.O.I.C.E.S. program? Was it useful? If not, why not?How would you restructure the educational system to improve the transitionfrom high school?We have spent two hours discussing your plans for next year. For you, what isthe central issue of all of this? What is the key message that I should be gettingfrom our conversations?Did the last interview make any difference in your plans? (i.e. did you doanything different because of the last interview?)Is there anything that I left out or that I should have asked? Is there anything youwant to ask me?400APPENDIX DComparison of Males and Females:Means and Standard DeviationsTABLEIll.MeansandStandardDeviations.Non-participants,non-universityparticipants, anduniversityparticipants.MalesandFemales.VARIABLENON-PARTICIPANTINON-UN1VERSITYIUNIVERSITYTOTALxiia.lej.zialeiiia.leiiia.lemeansdmeansdmeansdmeansdmeansdmeansdmeansdmeansdDESCRWFIONINTERESTEXPECTMOTHEDFATHEDFATHOCCMOTHINFFATHINFFAMINFFRIENINFCURRDIFFCPASDHONOURTEACHINFCOUNSINEDISTU2DISTCCAWARDTOTBELIEF2BELIEF3BELIEF60.825.430.835.111.265.191.131.134.421.093.741.453.651.442.5713.132.6712.602.4812.502.483.0713.612.9513.033.061Z7.52.9115.5953.9715.1250.6815.62509715.401.074.001MG3.571.193.821.141.153341083.571.253.661.221.273.001.292.671.302.851301.183.311.162.911.203.091.180.270.910.290.650.48Q0.470.643.040.642.400.882.430.856.3829.776.4928.236.3428.20.201.243.141.282.601.292.721.321.282.541.352.231.272.391.301.963.161.983.601.803.591.801.561.741441.651.631631.641.10.2.061.031.601.171.801.120.743.580.673.570.753.620.650.683.500.153.500.743.490.770.793.620.653.460.803.559.72Highestlevel ofeducationwantedHighestlevel ofeducationexpectedMother’seducationFather’seducationFather’soccupationCuniculardifferentiationGradepointaverageFamily’sinfluenceonpost-highschoolplansFriends’influenceonpost-highschoolplansMother’sinfluenceonpost-highschoolplansFather’sinfluenceonpost-highschoolplans%Grade12graduatesindistrictgraduatingwithhonourTeachers’influenceonpost-highschoolplansCounsellors’influenceonpost-highschoolplansDistancefromnearestuniversityDistancefromnearestcommunitycollegeTotalnumber ofawardsreceivedBeliefthatp.s.e.isnecessarytoprepareforajobBeliefthatp.s.e.isnecessarytoincreasemyincomeBeliefthat p.s.e.willgivemeawiderchoiceofjobs4.651.574.691.485.031.285.131.185.482.971.542.851.663.731.393.661.404.5212.142.2111.832.3612.422.4812.372.4013.1112.222.7011.812.7012.782.9712.522.9413.8447.1815.4547.s14.4249.5215.1449.5215.4754.073.111,343.201.373.741.143.931.073.773.051.402.961.433.711.iq3.701.243.752.421.302.471.322.781.332.951.332.752.701.272.681.193.001.213.151.203.080.300.460.310.460.570.500.600.490.921.760.681.880.752.100.772.190.77.0627.346.3827.816.1427.815.9027.865.9530.022.171.282.191.282.681.292.721.332.811.961.202.011.252.361.312.441.342.263.791.703.681.683.771.723.781.703.031.791.791.721.641.501.591.551.611.620.981.181.151.231.611.131.75LU1.823.400.873.550.753.600.713.6.50.633.563.310.893.440.853.480.753.490.773.573.320.863.440.833.440.603.510.743.50402APPENDIX ESummary of LISREL Parameter Estimates403Table IV.Standardized M.L. Estimates, Unstandardized M.L. Estimates, t-values t,and Standard Errors s.e.Male Femalen1360 n=1793Parameter ML. ML, M.L. ML.(*fjxed) 3tandard- unstand- t s.e. standard unstand- t s.e.rzed ardized -ized ardizedLoadings of 5 indicators on the exogenous variables:(ll) .592 .732 9.41 .078 .774 .967 12.04 .080.(2,l) .809 1.000* na. n.a. .801 1.000* n.a, n.a.(3,l) .631 .781 9.18 .085 .590 .737 9.58 .077(4,2) .895 1.000* n.a. n.a. .852 1.000* n.a. n.a.M5,2) .818 .914 19.68 .046 .783 .919 21.37 .043Errors and covariances associated with indicators of the exogenous variables:Ol,l) .649 .649 8.15 .080 .402 .402 3.97 .101O2,2) .345 .345 4.94 .070 .356 .356 5.43 .065O3,3) .601 .601 12.60 .048 .651 .651 15.78 .041O4,4) .202 .202 5.33 .038 .274 .274 8.56 .03205,5) .328 .328 9.79 .033 .388 .388 13.36 .02902,l) .096 .096 1.43 .067 -.087 -.087 -1.21 .071O3,l) -.045 -.045 -1.09 .041 -.146 -.146 -3.66 .04004,l) .036 .036 2.25 .016 .043 .043 2.74 .016O5,2) .074 .074 4.61 .016 .073 .073 4.20 .01605,3) .049 .049 2.77 .018 .048 .048 2.84 .017Loadings of the 12 indicators on the dependent variables:(l,l) .600 1.000* na. n.a. .497 1.000* n.a. n.a.(2,l) .645 1.076 14.48 .074 .598 1.202 15.53 .077(3,l) .587 .978 6.34 .154 .675 1.358 6.25 .217(4,2) .696 1.000* n.a. n.a. .674 1.000* n.a. n.a.(5,2) .794 1.141 21.34 .053 .717 1.063 20.52 .052M6,3) .631 .932 13.89 .067 .626 .986 15.31 .064(7,3) .678 1.000* n.a. n.a. .635 1.000* n.a. n.a.A(8,3) .590 .870 19.85 .044 .568 .896 21.53 .042(9,4) .439 .585 10.94 .053 .358 .566 10.93 .052A(l0,4) .750 1.000* n.a. n.a. .633 1.000* n.a. n.a.A(ll,5) .950 1.000* n.a. n.a. .949 1.000* na. na.M12,6) .950 1.000* n.a. n.a. .949 1.000* na. n.a.Errors associated with the indicators of the dependent variables:Or(l,l) .641 .641 10.11 .063 .753Oc(2,2) .584 .584 8.45 .069 .643OE(3,3) .656 .656 11.43 .057 .544OE(4,4) .518 .518 19.14 .027 .546Oc(5,5) .372 .372 13.42 .028 .487OE(6,6) .601 .601 17.35 .035 .609OE(7,7) .541 .541 14.64 .037 .597OE(8,8) .652 .652 17.69 .037 .677Oe(9,9) .809 .809 22.92 .035 .872Or(lO,lO) .441 .441 9.36 .047 .600OE(ll,ll) .100 .100 na. n.a. .100O(l2,l2) .100 .100 n.a. na. .100Or(l,2) .135 .135 2.22 .061 .195O(7,8) .228 .228 7.36 .031 .256.753 15.72 .048.643 10.81 .059.544 7.59 .072.546 20.57 .027.487 17.93 .027.609 19.83 .031.597 18.74 .032.677 21.18 .032.872 27.54 .032.600 17.45 .034.100 n.a. n.a..100 n.a. n.a..195 4.02 .049.256 9.63 .027Table IV. (continued)404Males FemalesParameter(*fixed)13(2,1)13(4,1)13(5,2)13(6,2)13(1,3)13(4,3)13(2,4)13(6,4)13(6,5)ML. M.L.tandard- uristand- t s.e.ized ardizedn.s.1 n.s. n.s. n.s..215 .269 4.30 .063.184 .251 5.70 .044.628 .858 13.07 .066.254 .225 5.51 .041.237 .262 5.50 .048.399 .559 10.38 .054.574 .533 9.31 .057.110 .139 2.33 .060.085 .085 3.32 .026ML. M.L.tandard- unstand- t s.e.ized ardized-.120 -.163 -2.61 .063.183 .233 3.86 .060.169 .238 5.55 .043.522 .736 9.37 .079.211 .165 4.92 .034.308 .307 7.52 .041.332 .497 9.82 .051.751 .800 11.31 .071.164 .246 2.85 .086.101 .101 4.36 .023Regression of six endogenous variables on exogenous variables:y(l,l) .087 .064 2.14 .030 .123 .076 3.39 .022y(2,l) .145 .125 3.46 .036 n.s. n.s. n.s. n.s.y(3,l) n.s. n.s. n.s. n.s. -.132 -.105 -4.04 .026y(4,l) .333 .309 7.04 .044 .388 .306 7.98 .038.525 .398 12.71 .031 .598 .446 14.77 .030.143 .152 5.67 .027 .158 .176 6.34 .028Residual variance in the six dependent variables:C(l,l) .927 .333 5.36 .062 .943 .233 5.34 .044(2,2) .589 .285 9.99 .029 .474 .215 7.59 .028C(3,3) .724 .333 9.39 .035 .650 .262 9.63 .027C(4,4) .743 .418 8.41 .050 .691 .277 8.96 .031(5,5) .782 .706 20.76 .034 .836 .753 24.61 .031C(6,6) .418 .377 15.33 .025 .459 .414 17.99 .023Covariances among exogenous variables:p(1,l) 1.000 .654 8.46 .077•(2,2) 1.000 .801 15.17 .053(2,l) .050 .037 1.46 .0251.000 .641 8.97 .0721.000 .725 16.38 .044.156 .106 5.16 .0211Nonsiicant path."@en ; edm:hasType "Thesis/Dissertation"@en ; vivo:dateIssued "1992-05"@en ; edm:isShownAt "10.14288/1.0055770"@en ; dcterms:language "eng"@en ; ns0:degreeDiscipline "Administrative, Adult and Higher Education"@en ; edm:provider "Vancouver : University of British Columbia Library"@en ; dcterms:publisher "University of British Columbia"@en ; dcterms:rights "For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use."@en ; ns0:scholarLevel "Graduate"@en ; dcterms:title "Paths on life’s way : destinations, determinants, and decisions in the transition from high school"@en ; dcterms:type "Text"@en ; ns0:identifierURI "http://hdl.handle.net/2429/3489"@en .