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Happiness, well-being, and post-secondary attainment: measuring the subjective well-being of British… Jongbloed, Janine Alysia 2012

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HAPPINESS, WELL-BEING, AND POST-SECONDARY ATTAINMENT: MEASURING THE SUBJECTIVE WELL-BEING OF BRITISH COLUMBIA’S HIGH SCHOOL GRADUATE CLASS OF 1988 by Janine Alysia Jongbloed B.A., Simon Fraser University, 2007  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF ARTS  in The Faculty of Graduate Studies (Higher Education)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  June 2012  © Janine Alysia Jongbloed, 2012     Abstract The purpose of the current study is to create definitions and conceptualizations of the constructs of “happiness” and “well-being” in a large sample of the high school graduate class of 1988 in British Columbia, Canada, and then explore the relationships among these concepts and postsecondary educational aspirations, expectations, and attainment. In this thesis, I define the concepts of “happiness” and “well-being” in terms of the participants’ own descriptions of these concepts elicited from focused questionnaire and interview questions from the last wave of the 22-year longitudinal Paths on Life’s Way project. Data were collected using survey methods (n=574) and interviews (n=19). By analyzing both quantitative and qualitative data from Paths on Life’s Way, I employ a mixed methods approach. Specifically, I use the survey data extensively and have added my own questions to the most recent set of follow-up interviews to better define and conceptualize “happiness” and “well-being” for members of the high school graduating class of 1988 in British Columbia, Canada. The current study builds on previous work done with this dataset (Andres, 1992, 2002, 2009, 2010) using the theoretical framework of Sen’s (1985, 1993, 2005) conceptualization of functionings and capabilities in relation to people’s well-being and agency. The basic hypothesis of the current study is that people’s perceptions of their own “happiness” and “well-being” are not only distinct, but also dependent on context, time, and life sphere (e.g., work vs. family). These complex concepts, and participants’ self-ratings of them, relate to post-secondary educational aspirations, expectations, and attainment in ways that differ by gender, health, marital status, and presence or absence of children. As well, the acts of defining and measuring one’s own “happiness” and “well-being” and attempting to change these is an iterative process that is both influenced by and influences one’s educational path.  ii   Preface This research was approved by the UBC Behavioural Research Ethics Board (BREB). The UBC BREB approval certificate number is H11-03092.    iii  Table of Contents Abstract ........................................................................................................................................... ii Preface............................................................................................................................................ iii Table of Contents........................................................................................................................... iv List of Tables ................................................................................................................................ vii List of Figures .............................................................................................................................. viii Acknowledgements........................................................................................................................ ix Dedication ...................................................................................................................................... xi Chapter 1: Introduction ............................................................................................................... 1 Personal Background and Interests............................................................................................. 1 Rationale for the Study ............................................................................................................... 3 Purpose of the Study ................................................................................................................... 5 Theoretical Frame ....................................................................................................................... 7 “Bounded” Agency ................................................................................................................. 7 Capability Approach ............................................................................................................. 10 Capabilities and functionings............................................................................................ 11 Well-being......................................................................................................................... 13 Nussbaum’s take on capabilities....................................................................................... 14 Why Sen? .......................................................................................................................... 15 Research Questions................................................................................................................... 17 Dataset....................................................................................................................................... 17 Overview and Structure of the Thesis....................................................................................... 18 Chapter 2: Literature Review.................................................................................................... 20 Historical Context ..................................................................................................................... 20 Contested Meanings of Happiness............................................................................................ 27 “Subjective Well-being” (SWB)........................................................................................... 28 “Happiness” versus “Well-being”......................................................................................... 31 Measuring happiness......................................................................................................... 32 Correlates of happiness. .................................................................................................... 33 Causation in happiness research. ...................................................................................... 37 Gaps in the Literature............................................................................................................ 39 Sen’s Contribution ................................................................................................................ 42 The Role of Education .............................................................................................................. 43 The Paths on Life’s Way Project .............................................................................................. 47 History and Sample............................................................................................................... 47 Chapter 3: Methodology............................................................................................................. 49 An Apprenticeship in Research ................................................................................................ 49   iv  The 2010 Interviews ................................................................................................................. 51 The Interview Participants .................................................................................................... 52 The 2010 Survey ....................................................................................................................... 53 The Survey Participants ........................................................................................................ 53 Ethical Considerations .............................................................................................................. 63 Data Analysis ............................................................................................................................ 64 Qualitative Analysis.............................................................................................................. 64 Quantitative Analysis............................................................................................................ 65 Chapter 4: Results....................................................................................................................... 67 Definitions of Happiness and Well-being................................................................................. 67 How Participants Measure Their Happiness......................................................................... 69 Happiness is not well-being. ............................................................................................. 74 Happiness as balance. ....................................................................................................... 77 The “gears” of well-being................................................................................................. 81 Summary ............................................................................................................................... 86 Happiness and Well-being as Survey Variables ....................................................................... 90 Relevant Survey Questions ................................................................................................... 90 Descriptive statistics. ........................................................................................................ 90 Gender differences. ........................................................................................................... 96 Summary. .......................................................................................................................... 98 Data Reduction...................................................................................................................... 99 Factor analysis. ................................................................................................................. 99 Selection of variables...................................................................................................... 101 Results............................................................................................................................. 102 Summary. ........................................................................................................................ 108 Happiness and Education.................................................................................................... 109 Regression analysis......................................................................................................... 109 Inclusion of variables...................................................................................................... 111 Happiness and relevant variables from the literature...................................................... 112 Regression analysis 1.................................................................................................. 112 Regression analysis 2: gender differences. ................................................................. 116 Happiness and educational variables. ............................................................................. 120 Regression analysis 3: happiness and post-secondary educational attainment........... 120 Regression analysis 4: happiness and post-secondary educational aspirations. ......... 126 Other well-being and educational variables.................................................................... 136 Regression analysis 5: physical health........................................................................ 136 Regression analysis 6: mental health. ......................................................................... 137 Regression analysis 7: life satisfaction. ...................................................................... 139 Regression analysis 8: life satisfaction incorporating happiness................................ 141 Correlations between relevant variables. ........................................................................ 142 The “conventionality” of happiness................................................................................ 143 Regression analysis 9: happiness and traditional markers of success......................... 144 Regression analysis 10: logistic regression................................................................. 151 Summary. ........................................................................................................................ 158     v  Chapter 5: Conclusion.............................................................................................................. 163 Summary of Research Findings .............................................................................................. 164 Research Finding 1: Happiness is Not Well-being ............................................................. 165 Research Finding 2: Happiness and Well-being in the Paths on Life’s Way Survey......... 167 Research Finding 3: The Impact of Education and the “Conventionality” of Happiness .. 168 Research Limitations .............................................................................................................. 170 Implications and Directions for Future Research ................................................................... 172 Conclusion .............................................................................................................................. 174 References................................................................................................................................... 176 Appendices.................................................................................................................................. 186 Appendix A: Survey Instrument .............................................................................................. 186 Appendix B: Loadings and Communalities............................................................................. 224 Appendix C: Regression Statistics and Diagnostics ................................................................ 260    vi  List of Tables Table 1. Highest post-secondary educational attainment by survey year..................................... 56  Table 2. Highest educational attainment in 2010 by gender......................................................... 58  Table 3. Ratings of happiness and well-being by interview participants ..................................... 68  Table 4. General happiness and well-being questions .................................................................. 91  Table 5. Satisfaction questions ..................................................................................................... 92  Table 6. Satisfaction with time spent on various activities........................................................... 92  Table 7. Enhancing well-being questions ..................................................................................... 94  Table 8. Importance of values questions....................................................................................... 96  Table 9. Component matrix of factors related to happiness and well-being .............................. 103  Table 10. The effect of income, exercise, … and physical health on happiness ........................ 115  Table 11. The effect of income, … and physical health on happiness by gender ...................... 119  Table 12. The effect of demographic and educational factors … on happiness by gender ........ 123  Table 13. The effect of demographic and educational factors … on happiness by gender ........ 125  Table 14. The effect of demographic and educational factors … on happiness by gender ........ 128  Table 15. The effect of demographic and educational factors … on happiness by gender ........ 131  Table 16. The effect of demographic and educational factors … on happiness by gender ........ 133  Table 17. The effect of demographic and educational factors … on happiness by gender ........ 135  Table 18. The effect of demographic and educational variables on physical health .................. 137  Table 19. The effect of demographic and educational variables on mental health..................... 138  Table 20. The effect of demographic and educational variables on life satisfaction.................. 140  Table 21. The effect of demographic, … and happiness variables on life satisfaction .............. 141  Table 22. Correlation matrix of relevant variables ..................................................................... 142  Table 23. The effect of employment, life choices, income, … and gender on happiness .......... 145  Table 24. The effect of employment, life choices, income, … on happiness by gender ............ 147  Table 25. Determinants of happiness in BC high school graduates ........................................... 152  Table 26. Predicted probability of happiness from income ........................................................ 154  Table 27. Predicted probability of happiness from family status ............................................... 154  Table 28. Predicted probability of happiness from life choices.................................................. 155  Table 29. Determinants of happiness in male BC high school graduates................................... 156  Table 30. Determinants of happiness in female BC high school graduates................................ 157     vii  List of Figures Figure 1. A person’s capability set in social and personal context. ............................................. 12  Figure 2. Happiness as balance. ................................................................................................... 77  Figure 3. Gears of well-being....................................................................................................... 81  Figure 4. Solution using Varimax rotation. ................................................................................ 107  Figure 5. Histogram of happiness scores for the first model...................................................... 148  Figure 6. Standardized residuals versus fitted values for the first model................................... 149  Figure 7. QQ plot of standardized residuals for the first model................................................. 150     viii  Acknowledgements This thesis would never have come into being without the encouragement, support, and guidance of my supervisor, Dr. Lesley Andres. Lesley pointed me towards numerous opportunities for professional growth, allowed me to gain experience in all aspects of her longitudinal, mixedmethods research project in a rewarding “apprenticeship in research,” and challenged and pushed me at every stage of my graduate studies, from our first conversation in Vienna about the Higher Education program at UBC to the writing of my thesis. Her efforts have greatly shaped my development as a researcher and scholar, as they will continue to do in the future.  I would also like to thank Dr. Kjell Rubenson, Dr. Amy Metcalfe, and Dr. Elizabeth Hirsh as members of my committee for their critiques, challenges, support, and inspiration in the research and thesis-writing process. Each one of these outstanding researchers has served as a model to me of the researcher I would like to become.  I am grateful to both the Social Sciences and Humanities Research Council of Canada (SSHRC) and the Faculty of Education at UBC, who provided me with financial assistance through the Joseph-Armand Bombardier Canada Graduate Scholarship, Master’s, and the Faculty of Education Graduate Award, Master’s. These funds allowed me to engage with my research in a way that otherwise would not have been possible.  I would like to thank my friends and colleagues in the Department of Educational Studies, as well as all of my friends and adventure buddies from outside UBC, who read several drafts of my thesis and gave me their insights, ideas, and acted as sounding boards for my wonderings and    ix  frustrations along the way. In particular, I thank Rafael Suavet très très beaucoup for his many edits and his patience while I endlessly “finished” my thesis. In my life and studies, his determined and courageous spirit pushes me to find those attributes in myself as well.  Last, but certainly not least, I would never be where I am today without the constant help, care, and patience of my parents, Peter and Helen, who taught me the balance between persevering and adapting my plans, the art of sticking to my values while still being open to the world, and the willingness to embark on new adventures throughout life. Their contributions to the person I am today are innumerable and deserve more gratitude than I can possibly express.     x  Dedication  In hope of a better world, through education and joy.    xi  Chapter 1: Introduction For thousands of years, people have been intrigued and baffled by the elusive concept of “happiness.” From the writings of ancient Greek philosophers to the complex inquiries of modern-day science, brilliant minds from around the world have grappled with the seemingly simple, but in fact infinitely difficult, questions: What is happiness? What causes happiness? And, how can we increase happiness? Plato, Aristotle, the Buddha, Marcus Aurelius, St. Augustine, Jean-Jacques Rousseau, Friedrich Nietzsche, Sigmund Freud, Carl Jung, and many others posed and attempted to answer these questions. However, each of their answers was different and in many ways directly contrasts with one another. Current researchers (for example, Diener et al., 1999; van Praag & Ferrer-i-Carbonell, 2004; Kim-Prieto et al., 2005; Delle-Fave et al., 2011; Raibley, 2011) are still attempting to find agreement on the answers to these questions. I will also look at these issues, although from a particular geographical and theoretical niche within the study of higher education in British Columbia, Canada.  Personal Background and Interests Since childhood I have been ever-curious with the idea of happiness. A search through my high school floppy disks and binders reveals a multitude of poems, short prose pieces, and doodlings all centred on the concept of happiness. My interest did not fade away with the hormones, mood swings, and unfortunate outbreaks of adolescence. In fact, after dabbling in criminology and history, I decided to major in psychology in my undergraduate degree. Thus, happiness was a topic that came up again and again, from social, biological and cognitive perspectives. My quest did not end with my diploma either. As I ventured into the “real world” for both work and travel, I realized the multitude of approaches and perspectives on happiness, life, and “what it all  1  means.” From South America to Eastern Europe, I encountered people who have very different answers to the question, “What is happiness and how can we achieve it?” My interest in this topic stems not only from a natural curiousity about human nature itself, but also from my exposure to and experience with mental health issues within my extended family and circle of friends. My approach to coping with these difficulties has been to focus on the ways in which I can increase my own and others’ happiness. Depression has been examined by psychologists in tens of thousands of studies, but happiness studies number much fewer. My own approach leans more towards that taken in the field of positive psychology, which focuses on the explanation and promotion of well-being (Csikszentmihalyi, 1990; Seligman & Csikszentmihalyi, 2000; Yen, 2010). To address the second half of my topic area, my interest in higher education arises from my experiences as both a teacher and student in adult learning environments in Canada and overseas. I experienced student life in both Burnaby, British Columbia, and in Prague, the Czech Republic during my undergraduate degree; as well, I was an instructor of English as an Additional Language (EAL) in both Vancouver, British Columbia, and Bratislava, the Slovak Republic after completing my studies. Through both my own experiences and through observation of others I have discovered that education, and learning more generally, can be an important avenue for self-growth and self-discovery. Learning in an adult setting not only involves the explicit content material of the class, but also a multitude of social and cultural roles, expectations, and values (Lave & Wenger, 1993). Thus, learning about disparate topics can inspire one to critically engage with one’s personal realities in all areas of life. Hence, learning and education have played an important role in both my professional and personal life. I believe that my formal and informal educational experiences gave me a new  2  conception of happiness and more positive outlook on my life and place in society, shaping me into the person I am today and contributing to my own happiness and well-being. Part of the aim of this study is to find out whether this is true of other people as well and whether education really does play an important role in promoting happiness and well-being for Canadians. However, the present study deals in great part simply with defining and creating a way to measure happiness and well-being, leaving the relationship between education and happiness and well-being over time for future doctoral research. Essentially, this study is designed as the first step in a larger study that will more comprehensively examine the concepts and relationships outlined here.  Rationale for the Study The new trend, and great popularity, of using happiness as an outcome measure of social welfare and public policy is evident in Canada and internationally (Bergheim, 2007; Dolan & White, 2007; Greve, 2010; Kahneman & Kreuger, 2006) and the study of these variables has blossomed into a large field which interests both social scientists and national governments around the world, as well as the general public (e.g., Gilbert, 2006; Helliwell et al., 2012; Rubin, 2009; McMahon, 2009). Numerous reviews of the literature of happiness and subjective well-being have been written in recent years within the discipline of psychology (e.g., Diener et al., 1999; Dolan et al., 2008; Kahneman & Krueger, 2006). This is also a blossoming area of study in economics as well (e.g., Blanchflower & Oswald, 2004; Easterlin, 2005). The study of happiness or well-being as an outcome variable is common in this field, with several different approaches taken. Helliwell and Putnam (2004) describe human well-being as “the ultimate ‘dependent variable,’” and, in particular, “well-being as defined by the individual herself, or ‘subjective  3  well-being’” (p. 1435). Blanchflower and Oswald (2004) assert that happiness and well-being research “unites different kinds of social scientists” (p. 1360). They point out that there are “limitations to well-being statistics” and that it is “unlikely that human happiness can be understood without, in part, listening to what human beings say” (p. 1360). Helliwell and Barrington-Leigh (2010) argue for the importance of these positive measures in psychological, health, and economic research. They assert that although economists are often skeptical of subjective variables, following in great part from research on set-point theory (Bickman, Coates, & Janoff-Bulman, 1978), “differences of subjective life evaluations among individuals and across nations are largely explicable by the same life circumstances, and in similar ways, across the globe” (Helliwell & Barrington-Leigh, 2010, p. 733). They point to the example of the government of Bhutan, which “has Gross National Happiness as its constitutionally embodied goal” and “currently measures its national progress by an equally weighted average of nine component indicators, including a direct measure of subjective wellbeing and eight indicator variables considered likely to support sustainable well-being” (p. 735). Based on their research, Helliwell and Barrington-Leigh (2010) recommend that direct measures of subjective well-being be used in making public policy decisions and that more attention be paid to “the great importance of the quality of social identities and social capital as supports for better lives” (p. 745). The current study will utilize the work of Amartya Sen on conceptualizing human wellbeing. Having his work as a framework allows me as the researcher to take an underutilized approach of looking not only at what people are and do, but also at what they are able to be and do. Thus, the tension between freedom and meaning-making or justification, which is often incorporated as an important aspect of happiness (for example, Marar, 2003), can be included in  4  the analysis. Education may be an important avenue for achieving both of these human aims. Of importance to the current study, education has been found to be “a virtually universal correlate” of happiness and well-being (Helliwell & Putnam, 2004, p. 1436). This is the case even when other variables, such as income, are controlled for in the analysis (Blanchflower & Oswald, 2004). The present research also attempts to help fill several gaps in the literature on happiness and well-being. As yet, researchers are unable to agree upon definitions for happiness and wellbeing (Gilbert, 2006; Kahneman, 2011). This in itself is an important area of inquiry. Along with this, the perspectives and opinions of lay people, especially those who are not undergraduate psychology students, are largely missing in the literature (Delle-Fave et al., 2011). Gender comparisons have been few and inconclusive (Helliwell & Putnam, 2004). Effects of educational attainment have also varied widely depending on country and levels of education investigated (Helliwell & Putnam, 2004). This study incorporates all of these areas and attempts move towards filling in these holes.  Purpose of the Study The purpose of the current study is to create definitions and conceptualizations of the constructs of “happiness” and “well-being” in a large sample of the high school graduate class of 1988 in British Columbia, Canada, and then explore the relationship between these concepts and postsecondary educational aspirations and attainment. In this thesis, I define the concepts of “happiness” and “well-being” in terms of the participants’ own descriptions of these concepts elicited from focused questionnaire and interview questions from the 22-year longitudinal Paths on Life’s Way project. Data were collected using survey methods (n=574) and interviews (n=19).  5  By analyzing both quantitative and qualitative data from Paths on Life’s Way, I employ a mixed methods approach. Specifically, I use the survey data extensively and have added my own questions to the most recent set of follow-up interviews to better define and conceptualize “happiness” and “well-being” for members of the high school graduating class of 1988 in British Columbia, Canada. First, I examine the qualitative interview data to better understand the ways participants approach the task of assessing their own happiness and well-being when answering survey questions and to define and conceptualize “happiness” and “well-being” using the participants’ explanations of their process of answering the survey questions as a guide. Next, I use factor analysis to identify factors mapping onto the constructs of “happiness” and “well-being” from the many questions related to these concepts found in the Paths on Life’s Way survey. Finally, I trace the relationship between post-secondary educational aspirations, expectations, and attainment and these two distinct concepts in this sample using regression analysis. I control for potentially influential variables and also explore potential effects of health, marital status, and presence or absence of children. I split this analysis into separate regression analyses for men and women in order to look at gender differences in this relationship. The current study works from the basis of other research conducted using this dataset (Andres, 1992, 2002, 2009, 2010), but incorporates a new perspective by using the theoretical framework of Sen’s (1985, 1993, 2005) conceptualization of functionings and capabilities in relation to people’s well-being and agency. The central research question of the current study concerns whether people’s perceptions of their own “happiness” and “well-being” are distinct, and also whether they are dependent on context, time, and life sphere (e.g., work vs. family). These complex concepts, and participants’ self-ratings of them, are hypothesized to relate to  6  post-secondary educational aspirations, expectations, and attainment in ways that differ by gender, health, marital status, and presence or absence of children. As well, the acts of defining and measuring one’s own “happiness” and “well-being” and attempting to change these is an iterative process that is both influenced by and influences one’s educational path. Thus, the primary aims of this study are descriptive: To describe how participants define happiness and well-being and then to analyze how these concepts are related to postsecondary aspirations, expectations, and attainment.  Theoretical Frame “Bounded” Agency My entire scientific enterprise is indeed based on the belief that the deepest logic of the social world can be grasped only if one plunges into the particularity of an empirical reality, historically located and dated, but with the objective of constructing it as a ‘special case of what is possible,’ as Bachelard puts it, that is, as an exemplary case in a finite world of possible configurations. (Bourdieu, 1998, p. 2) The Paths on Life’s Way project is one such “special case of what is possible.” This group of people comes from particular geographic region, British Columbia; a particular socio-political climate, the liberal democratic nation of Canada; and a particular generational age group, as children of the 1970s (Andres & Wyn, 2010). However, the ways in which the interview participants define happiness and well-being, and the impact that post-secondary aspirations, expectations, and attainment have on the survey participants, can provide insight into the relationship between these variables in many other “special cases” across North America as well. Thus, although these results may not be generalizable to all North Americans, they may transfer to other groups of individuals of approximately the same age in Canada and the United States.  7  An important consideration when framing this study was that the survey and interview participants should not be viewed as free agents with absolute control over their lives, but neither can they be viewed as pawns within the system without any free choice. Rather, one must recognize from the outset the complex interaction between the individual and the society within which they live, which mutually influence each other. Pierre Bourdieu (1998) theorizes this interaction with his conceptualization of “the relation between social positions (a relational concept), dispositions (or habitus), and position-takings (prises de position), that is, the ‘choices’ made by the social agents in the most diverse domains of practice” (p. 6, italics in original). His ideas have been incorporated into the work of many other scholars. Lesley Andres (1992, 2009) applied his ideas to the Paths on Life’s Way data by examining academic capital and post-high school post-secondary educational choices, as well as parents as sources of cultural and social capital, which affected dispositions to post-secondary education. Andres and Wyn (2010) use Bourdieu’s work to frame their discussion of the hopes and dreams of the Paths on Life’s Way participants by arguing that “individuals are located in an historical, economic, and social context that sets the stage for their subsequent actions” (p. 67). They further assert that the participants do not have “endless possibilities,” but rather take up “subject positions that they [see] as being available to them” (Andres & Wyn, 2010, p. 67). The current study is framed within the understanding that the participants’ exert this type of “bounded” agency within their lives and choices about post-secondary education. Jon Elster (2009) emphasizes this in relation to rational choice in his book, Reason and Rationality. He points out that On the one hand, the agent can choose only among the options that he thinks are available to him [or her]. The objective existence of an option superior to those he is aware of cannot influence his [or her] action. On the other hand, the agent chooses among the options of which he [or she] is aware according to the possible consequences he [or  8  she] attributes to them and his [or her] estimate of the probability that they will occur… For action to be rational, the beliefs on which it is based must themselves be well founded. (Elster, 2009, p. 21-23) Thus, although the participants act as rational agents, their choices are also limited by their exposure to options and information, which may in turn be influenced by their socio-economic status (SES), as well as parental social capital (Andres, 2009). This bounded rationality creates a complicated environment within which decisions – and lives – take place. The participants’ actions are an outcome of a process of interactions between their desires, beliefs, and the information available to them from various sources (Elster, 2009). Although participants may also act irrationally at times, for the most part they, and people in general, take pride in acting in rational ways (Elster, 2007). They, for the most part, do “the best they can,” as defined by their desires and the opportunities available to them (Elster, 2007). Despite the fact that this may appear straightforward, the fact that these various parts of rational action are all interrelated muddies the picture: “Desires and opportunities are not always (as is sometimes assumed) independent of each other” (Elster, 2007, p. 165). Another model related to those above, but applied to area of adult education, is Rubenson and Desjardins’ (2009) “Bounded Agency Model.” This model takes “account of the interaction between structurally and individually based barriers to participation” in adult education (Rubenson & Desjardins, 2009, p.187). Thus, the participants, as agents, have both a high degree of freedom and are “also bounded by structures and contexts and by features of the self that constrain choices” (p. 192). Within this context, not participating, as well as participating, may become “highly rational” acts (p. 192). This means that the relationships found among happiness, well-being, and post-secondary aspirations and attainment must be interpreted carefully as  9  relationships influenced by a myriad of other factors both within and outside the participants’ control.  Capability Approach Bourdieu (1998), Elster (2007, 2009), and the other researchers and authors mentioned above have all been influential in my research and reading of the participants’ stories. However, the guiding framework of my analysis and interpretation of the research results is Amartya Sen’s (1993) capability approach. Although this is not a fully specified theory, it does provide a framework for understanding and evaluating how to define and measure happiness and wellbeing within this study. Other researchers recommend using the capability approach in this way: The capability approach is a broad normative framework for the evaluation and assessment of individual well-being and social arrangements, the design of policies, and proposals about social change in society. Its main characteristics are its highly interdisciplinary character, and the focus on the plural or multidimensional aspects of well-being. The approach highlights the difference between means and ends, and between substantive freedoms (capabilities) and outcomes (achieved functionings). (Robeyns, 2005, p. 94) This approach is mainly used in economics, social policy, and political philosophy (Robeyns, 2003a); however, it allows a unique look at well-being by focusing on what individuals are able to do and to be as central to human well-being. The ability to choose one’s situation and activities, irrespective of what one actually is and does, arose as an integral notion throughout the data used in this study. Sen’s (1999) famous example illustrating his capability approach is that of a fasting priest versus a starving peasant. One has the choice and ability to eat, but chooses not to, whereas the other has no choice and is simply unable to eat. As Sen (1999) describes, “an affluent person who fasts may have the same functioning achievement in terms of eating or nourishment as a  10  destitute person who is forced to starve, but the first person does have a different ‘capability set’ than the second” (p.75). This is because while “the first can choose to eat well and be well nourished,” on the other hand, “the second cannot” (Sen, 1999, p.75). Approaches that only consider what a person is and does would view these two situations as equivalent, while clearly they are not. The capability approach allows the differences between the two to become apparent.  Capabilities and functionings. Sen (1985, 1993) and others who use the capability approach (for example, Nussbaum, 2011; Robeyns, 2003a) make a distinction between capabilities and functionings when looking at quality-of-life issues. The term “capability” can be defined as the answer to the question, “What is this person able to do and to be?” and “functioning,” in turn, can be defined as the “active realization of one or more capabilities” – or, otherwise stated, “beings and doings” (Nussbaum, 2011, p.24-25). Thus, capabilities are not simply a person’s abilities, but their freedoms or opportunities to achieve various functionings. This freedom does not only reside in the person: The “political, social, and economic environment” also shapes these freedoms, much like in the “bounded agency” model discussed above (Nussbaum, 2011, p.20). Each person’s capability set can be outlined and illustrated according to the guideline of this framework (see Figure 1).  11  Figure 1. A person’s capability set in social and personal context (Robeyns, 2005, p. 98).  Thus, in order to improve the quality of people’s lives, the most important area to focus on is the capability set – what people are able to do and to be (Robeyns, 2005). This allows people the “freedom to live the kind of life that, upon reflection, they have reason to value,” which is a central argument in Sen’s approach (Robeyns, 2005, p. 94). More specifically, Sen (1993) outlines four concepts of human welfare: (1) well-being achievement, (2) agency achievement, (3) well-being freedom, and (4) agency freedom. Human beings have goals and strivings related to both well-being and agency. It is important to note that here agency is a goal in itself, and not necessarily simply a means to increase one’s well-being, although it may also do so. Thus, both achievements and the freedom to achieve are important to human beings. The achievements, or “functionings,” include everything that the person manages to do or be. This concept has its basis in Aristotelian philosophy in that capabilities reflect, “the various things a person may value doing or being” (Sen, 1999, p.75, my emphasis). The valued functionings for an individual person “may vary from elementary ones, such as being adequately  12  nourished and being free from avoidable disease, to very complex activities or personal states, such as being able to take part in the life of the community and having self-respect” (Sen, 1999, p.75). This, as well as the concept of freedom, or otherwise stated, “capabilities,” which includes everything that the person is able but may or may not choose to do or be, makes Sen’s capability approach to human quality-of-life unique.  Well-being. Happiness and well-being research today tends to focus heavily on the emotional or psychological aspects of happiness and well-being and the large-scale survey approach which asks few questions and does not question or tease apart the notions of happiness and well-being. Psychological approaches, such as the concept of “subjective well-being,” and economic approaches, such as utility approaches, focus very much on what people are or do or have, but rarely investigate happiness and well-being in terms of what people could be or could do or could have. In direct contrast to much of this research on happiness and well-being, Sen (1985) argues that “as a mental state concept, the perspective of happiness may give a very limited view of other mental activities” (p.188). This alternative view of happiness, one that does not simplify it to make it fit a single, numerical survey question or deify it to the point that it becomes the ultimate goal of human existence, has come to shape my own analysis after seeing this idea clearly reflected in the interview participants’ explanations of how they rate their levels of happiness, how this changes over time, and how they define and understand the concepts of happiness and well-being. Sen (1985) further asserts that well-being and agency are both integral to human qualityof-life, but are separate ideas. He argues that we do not always act to increase our well-being; it  13  is very important, but “there are clearly other things that are also valuable to do or be” (p. 196). Further, and importantly for this study, he also asserts that well-being and happiness are distinct. He states that although “happiness is of obvious and direct relevance to well-being, it is inadequate as a representation of well-being” (p. 189). Thus, happiness is only one part of wellbeing in his conception. In his mind, “happiness is basically a mental state, and it ignores other aspects of a person’s well-being” (p. 188). Well-being here is a much larger concept that includes multiple facets of a person’s functionings and capabilities, only one of which is happiness.  Nussbaum’s take on capabilities. Martha Nussbaum’s (2011) capabilities approach differs from Sen’s capability approach (1985, 1993). She defines this approach as a way to compare societies by asking the question, “What is each person able to do and to be?” (Nussbaum, 2011, p. 18). This is strongly linked to the work of Sen, but differs in several important ways, including the fact that she extends her concern to nonhuman animals and that she lists specific “central capabilities,” while Sen does not emphasize these areas of inquiry in his approach. He is, in fact, opposed to a universal list of capabilities, and instead emphasizes that these should be created democratically for each individual group of people and situation (Robeyns, 2003a, 2006). However, Nussbaum’s approach can add much to present study in the ways that it complements Sen’s work. It does so in several ways which are fruitful for the current study; notably in that the approach takes each person as an end, asking not just about the total or average wellbeing but about the opportunities available to each person. It is focused on choice or freedom… It thus commits itself to respect for people’s powers of self-definition. The approach is resolutely pluralist about value: it holds that the capability achievements that are central for people are different in quality, not just in quantity; that they cannot without distortion be reduced to a single numerical scale; and that a fundamental part of  14  understanding and producing them is understanding the specific nature of each. (Nussbaum, 2011, p. 18-19, italics in original) One of the key ways that Nussbaum (2011) informs the present study is by making explicit the fact that participants may voice preferences that are shaped not only by what they want but also what they are capable of imagining due to various social circumstances and constraints (in line with Bourdieu’s concept of habitus). An important consideration in the present study is the difference between having access to and being able to participate in post-secondary education versus choosing to do so or not. Even when voicing their aspirations – not only their actual participation and attainment – in regard to education, the participants’ answers are very likely shaped by their social context. Nussbaum (2002) addresses this difficulty. She argues that “preferences are endogenous, the creation of laws and institutions and traditions” (Nussbaum, 2002, p. 132). Hence, this analysis is framed with the awareness that whatever the participants’ possible hopes, dreams, and aspirations in regards to post-secondary education, they may not be able to fully actualize these in practice or even in imagination. These constraints are external and influential upon the relationships I am investigating. This is important to bear in mind when analyzing both the qualitative and quantitative data. This will make my analysis and interpretation of results more difficult; however, as Nussbaum (2002) asserts, “Anything worth measuring in human quality of life, is difficult to measure” (p.135).  Why Sen? Sen’s (1993) capabilities approach provides a good frame for this study because it points to potential differences in well-being and happiness, and also to areas of life and freedoms that might be important to people irrelevant of the potential impact on their happiness. Much like the  15  interview participants pointed out, and contrary to much of the “happiness research” done today, Sen argues that happiness is only one (perhaps small) part of well-being and that well-being is not the only valued achievement for which human beings strive. Although much of the current research limits happiness, which is usually used synonymously with well-being, subjective wellbeing (SWB), life satisfaction, and other similar terms, to a single number and uses Likert-scales and only a few – or one – question about happiness, the present study uses qualitative interview questions to get at the process that people go through when measuring their own happiness and well-being and, in turn, to critically examine our measurement and interpretation of numerical data. In doing so, much of the information that arose was centered on values, goals, and notions of the “good life,” or what the participants wanted their life to be like and how it compared to that ideal at the present moment. These ideas fit nicely into Sen’s approach, especially within his distinction between functionings and capabilities. Interview participants not only focused on what they had done and been in the time leading up to the present moment of the interview, but also on what they could have done or could have been (or could be in the future). Thus, to truly understand the ways in which they are viewing their lives and valuing them, a framework like Sen’s is indispensible. Coming back to Bourdieu’s quote (at the beginning of this section), these views of happiness are situated in a particular group of people of a certain age who grew up in one geographical region and the same overarching political climate; however, it may transfer as “a special case of what is possible” in other places and with other groups of people.  16  Research Questions The overarching research question of this study is, “What constitutes ‘happiness’ and ‘wellbeing’ for the 1988 high school graduates of British Columbia?” Within this broad research question are several specific questions: i)  How do Paths on Life’s Way interview participants define and describe “happiness”? How do they define and describe “well-being”? Are these constructs the same or different? Are there differences by gender?  ii)  Do separate factors of “happiness” and “well-being” emerge from the numerical questionnaire data of the survey participants? Do other related sub-factors emerge as well?  iii)  What are the relationships among happiness, well-being, post-secondary aspirations, expectations, and attainment, and other control variables in the survey data? Does the nature of this relationship differ by gender?  Dataset The Paths on Life’s Way project provides a unique glimpse into the lives of Canadians as the only longitudinal study of youth in British Columbia and one of only a few in Canada (Andres, 2002). This study now spans 22 years (from 1988 to 2010) and provides “a detailed examination of students’ lives, choices, and post-secondary education and work experiences across different points in time and in relation to changing social and cultural conditions” (Andres, 2002, p.1). This study consists of baseline data collected in 1988, such as demographic information and high school grade point averages, of 10,000 high school graduates in British Columbia; the first  17  survey questionnaire (“Grade 12 Graduate Follow-up”) conducted in 1989; and four follow-up surveys in 1993, 1998, 2003, and 2010. Alongside the survey project, Andres has also conducted interviews with a separate, smaller sample from the same population corresponding to all the waves of the survey. This project will be discussed in more detail in Chapter 3.  Overview and Structure of the Thesis This thesis began with my personal background and interest, the rationale and purpose of the study, the theoretical framework, and a brief introduction to the dataset used. The next chapter continues with a literature review of the historical context of happiness research and the contested meanings of happiness, as well as the potential role of education in promoting wellbeing. In the following chapter, I describe the Paths on Life’s Way project in more detail. My explanation of the research process and methodology of this study begins with an overview of my “apprenticeship in research” and goes on to describe the interview participants, the 2010 interviews, the survey participants, and the 2010 wave of the survey. I conclude this section with some remarks on ethical considerations in this study. My data analysis section defends my choice of a mixed methods approach and outlines both the qualitative and quantitative analyses conducted. The next chapter, and the results of this study, begins with descriptions of how participants measure their happiness and the intersecting domains that relate to happiness, such as family, personal relationships, work, and leisure. The qualitative results end with a defense of why happiness is not equivalent to well-being, as well as the definitions of happiness and wellbeing that emerged from the interview data. The quantitative results open with a description of the relevant survey questions and variables, as well as some descriptive statistics on happiness  18  and well-being in the Paths on Life’s Way sample. I explain the process of the factor analysis and the resulting factors. From here, I describe the regression analyses run to look at the impact of educational aspirations, expectations, and attainment on these factors. Because gender is hypothesized as a moderating variable, the analyses are run separately for men and women. This thesis ends with conclusions and recommendations for future research. I also discuss the limitations of this study and potential further studies using this dataset.  19     Chapter 2: Literature Review Historical Context We hold these truths to be self-evident, that all men are created equal, that they are endowed by their Creator with certain unalienable rights, that among these are life, liberty and the pursuit of happiness. (US Declaration of Independence, July 4, 1776) Happiness. This is one of the most, or the most, sought-after goals of human beings on earth today (Gilbert, 2006). It is enshrined in national constitutions and chased by children and adults, men and women, rich and poor alike. Happiness has been explored and studied as far back as (and surely further than) the time of the Buddha and the ancient Greeks, and many of the same questions are still posed today in the context of modern scientific methods (Diener et al., 1999). However, some claim that we have not made all that much progress in between (Wilson, 1967; Diener et al., 1999). Throughout the history of western philosophy, ideas on happiness have shifted over place and time. According to Plato in ancient Greece, a person could achieve the deepest happiness by being just. In The Republic, Plato describes three divisions of the human psyche and explained that the greatest happiness for the individual arises when there is a harmonious expression of all parts of the psyche according to their natural abilities. However, a person cannot achieve this on their own: They need to live in a just society in order to achieve happiness. To explain justice in society, Plato describes the ideal affluent society, which is just, and then describes four deviations from this ideal society that can each be ranked by how far they deviate from justice. By describing these four forms of society and the personality types that emerge from each, Plato illustrates that the just person, who is the natural product of the just society, is the happiest possible person because each part, both within the individual and society, is acting according to its specialized function with reason in charge of the whole. Plato’s belief that the just person is  20     the happiest person suggests that happiness does not depend on the individual, but depends on social action because individuals are always a reflection of the society in which they live. Later, during the time of the Roman Empire, Marcus Aurelius posited that people could achieve the deepest happiness indirectly through acceptance and duty, and more directly through deliberate self-absorption. In The Meditations, the idea of the “Self,” or the divine spirit within, is central to Aurelius’ psychology: only by knowing the “Self” could one find happiness. Happiness is Aurelius’ primary goal; all other virtues are only virtues if they help the individual achieve happiness. Aurelius proposes a set of lifestyle themes, taking an eclectic approach to happiness and leaving the individual more room for personal taste. His advice is mainly to find self-satisfaction by concentrating attention on oneself and letting self-approval be the sole aim of all one’s actions and thoughts. Aurelius’ approach suggests that happiness depends on the personal development of the individual and will therefore differ from person to person. After the spread of Christianity in Europe, St. Augustine argued that people could achieve the deepest happiness through one simple step: allowing God to fill the void that is present in all of our souls. In Confessions, he describes that in order to allow God to fill our void we must gain power over the body by rejecting earthly pleasures and we also must have a conversion experience in which we figuratively “jump off a cliff” into God’s arms, in which we give complete control of our lives to God. The joy of a faithful hope is the deepest happiness that a person can achieve, according to St. Augustine, and this can only be achieved through one source: God. Although this may seem limiting, it actually made the deepest happiness available to everyone (unlike Plato and Aurelius’s more elitist versions of happiness) because all people have a free will and thus can find God and happiness.  21     In the eastern part of the world at that time, great sources of wisdom, such as the Buddha, Muhammad, and Vahiguru, offered different visions of happiness. The teachings of Siddhartha Gautama, the Buddha or “awakened one,” explain the roots of suffering in this world – and an escape from this suffering. Similarly to St. Augustine and contrary to Marcus Aurelius’ ideas, the Buddha’s teachings claim that suffering often arises from our craving for happiness, or the things that we think will make us happy. Our tendency to cling to an inflated sense of “Self,” as well as our habit of dwelling on what we do not have but wish we did, lead us to suffering. However, by letting go of these thoughts, habits, and cravings, and following the path of the Buddha, we can achieve liberation, or Enlightenment. These teachings have permeated many places in the world since the Buddha’s lifetime in the fifth century BCE. In the mid-eighteenth century, Jean-Jacques Rousseau began to describe happiness in terms that we might recognize today from bookstore shelves of self-help books. Rousseau describes finding happiness as going in search of one’s lost self, below all of the baggage and restraint society places upon us, to find the natural purity that lies within all of us (McMahon, 2006). He describes his happiest moments as those in nature, and criticizes modern culture (at the time) for constraining human beings while it claimed to liberate them. The advancements that promised to improve human welfare also severed people from one another and from nature, creating an artificial idea of the self. If civilization could be stripped away, and people could exist in their natural state, they would rediscover their inherent happiness and true selves. These views stand in stark contrast to many of the prominent German philosophers of the next century. This tradition of Bildung (“self-cultivation” and “culture”), which was propagated by great thinkers such as Arthur Schopenhauer and Friedrich Nietzsche, viewed happiness as the result of hard work and struggle. In his early work, Schopenhauer described happiness as a  22     “mistaken” goal and belief within human beings, and argued that a person’s aim in life should be for “purification” rather than happiness (Bruford, 1975). However, later in life, he contradicted this philosophical position in order to appeal to “the level of the majority” in a practical way (Bruford, 1975, p. 113). In this later work, such as Aphorisms on Wise Living, Schopenhauer emphasized health, a material basis for life, and social connections and regard as central to achieving happiness, although one’s personal qualities were by far the most important (Bruford, 1975). If one had intelligence and health, one had “nine tenths” of happiness already (Bruford, 1975, p. 115). Greatly influenced by Schopenhauer, Nietzsche took these ideas of Bildung, and happiness as secondary to heroism, further still. In this philosophy, genius is worshipped as the highest aim of mankind – and as an aim that only a few could ever hope to achieve. Genuine Kultur was a rare accomplishment, but one through which those who were gifted enough to reach it could serve the common good. Idealism and “weakness” were no way to happiness; true happiness could only arise as secondary to the grander accomplishments of genius and heroism (Bruford, 1975). Building on Darwin’s recent theories at the time, Nietzsche emphasized “the rare emergence of the highest intelligence and cultivation, contrast[ed] the fortunate few with the millions around them, and put all his hope for the full realization of human possibilities on the deliberate breeding of improved types from promising existing stocks” (Bruford, 1975, p. 173174). According to Nietzsche, happiness would not arise from comfort or ease, but rather from hardship, struggle, and self-improvement – and only for a very few. With the creation of the field of psychology in the late nineteenth century, attention shifted away from happiness and more towards its antithesis: mental illness and unhappiness. Influential thinkers such as Sigmund Freud approached happiness as an impossibility: Our goal  23     should be to minimize unhappiness rather than strive for the unattainable. Freud had a very different view of fundamental human nature than Rousseau. Influenced by Darwin’s theory of evolution, Freud viewed human beings in their natural state as pulled towards two great longings: for sex and for death. These desires create aggression, guilt, and, often, psychological illness. Freud, unlike Rousseau and even Darwin, did not claim that human beings had an inherent purpose in life, or that they could ever achieve happiness (McMahon, 2006). His view of human nature was decidedly tragic (in the sense of the Greek literature of tragedy). Finding “authentic happiness” from Freud’s point of view was simply another self-delusion of human beings. Our goal should be to strive for “common unhappiness,” which was the best possible outcome. In his 1930 Civilization and Its Discontents, Freud outlined happiness as compromising of two parts: an absence of pain and a presence of pleasure (consistent with other thinkers, such as Jeremy Bentham). Freud described the goal of human life as to maximize the sensation of pleasure; however, this goal is thwarted from every side by our own mental components (such as the ego, which keeps us in check according to the “reality principle”), by nature itself, and by our society, which suppresses our basic urges in so many ways. Thus, although we search for happiness, suffering is waiting around every corner. A colleague of Freud, Carl Jung, took a very different view of human nature. He saw human beings as primarily religious, and made the process of individuation – integrating yet maintaining the aspects one’s conscious and unconscious being in order to become whole – central to his “analytical psychology.” Unlike Freud, who took a much darker view of human nature, Jung believed that the purpose of human life was to discover our innate potential, which extended beyond our simple material goals into the spiritual realm. Jung studied the world’s religions and believed that they all rested on a shared basic core: to find the self and the Divine  24     in spiritual experience. He introduced the concept of the “collective unconscious,” which operates alongside the personal unconscious and is shared by everyone. Jung argued that we can achieve well-being through the process of individuation, but this requires bringing to one’s consciousness not only one’s personal unconscious, but also the collective, and is essentially a spiritual quest. In this, he relied on his study of Christianity, Hinduism, and Buddhism. Buddhist teachings have been adopted into various cultures and countries, including the Vajrayana traditions in Tibet. These teachings are increasingly popular around the world today, notably in North America and on the west coast especially. The spiritual leader of Tibetan Buddhism, the Dalai Lama, is believed to be a reincarnation of the bodhisattva of compassion. The 14th Dalai Lama has spread the teachings of Buddhism internationally, with visits to various countries, interviews, speeches, and books. He co-authored a book in North America entitled, The Art of Happiness: A Handbook for Living, which describes the purpose of life and how to train and transform the mind to let go of suffering. The Dalai Lama asserts, “I believe that the very purpose of our life is to seek happiness” (His Holiness the Dalai Lama & Cutler, 1998, p. 13). He goes on to explain that happiness arises from “inner discipline,” that is, “identifying those factors that which lead to happiness and those factors which lead to suffering” and then “gradually eliminating those factors which lead to suffering and cultivating those which lead to happiness” (p. 15). Importantly, this happiness arises in great part from human warmth and compassion, as well as deepening our connection to others (His Holiness the Dalai Lama & Cutler, 1998). Thus, it is a social as well as solitary pursuit, which requires us to let go of our instinctive sense of “Self” and much of the self-interest that permeates western (and world) culture today.  25     With the rapid growth of the field of Psychology in the twentieth century and to the present, depression and mental illness have been topics of much scrutiny. PsycInfo lists 4,000 articles on the study of happiness and 20,000 on depression (Kim-Prieto et al., 2005). The modern study of happiness, now mainly referred to as “subjective well-being” (SWB) in scientific literature, began to take shape in North America with Warner Wilson’s (1967) article, “Correlates of Avowed Happiness” (p.294). Wilson (1967) found that the “happy person emerges as a young, healthy, well-educated, well-paid, extroverted, optimistic, worry-free, religious, married person with high self-esteem, high job morale, modest aspirations, of either sex and of a wide range of intelligence” (p. 294). He recommended that no further examination of simple correlations was necessary; however, many such studies followed. With all of this research one would expect that people would be getting happier – but they’re not. Happiness levels, as measured on a 10-point Likert scale, have stayed relatively consistent over the past 50 or so years, despite massive increases in disposable income and living standards (Diener et al., 1999; Easterlin, 1995, 2005). Why is this so? One possible reason is that happiness arises more from comparisons than absolute living standards and realities. Another possible reason is that our happiness may depend more on our expectations and goals than whether or not our basic needs are met. As well, most people avow happiness, and have done so since the beginning of formal research into happiness (Wilson, 1967; Diener & Diener, 1996; Diener et al., 1999). The present study will follow the sage advice of leaders in this field by attempting to move beyond a simple correlation between education and happiness to investigate the role that “the context provided by people’s experiences, values, and goals” plays when “assessing the influence of external events on happiness” (Diener et al., 1999, p.278). In particular, Wilson’s  26     assertion that the “well-educated” are happier, which has been supported – although with small effect sizes – by many other researchers, will be examined in more detail (Blanchflower & Oswald, 2004; Diener et al., 1999; Helliwell & Putnam, 2004; Kahneman, 2011).  Contested Meanings of Happiness During the last ten years we have learned many new facts about happiness. But we have also learned that the word happiness does not have a simple meaning and should not be used as if it does. Sometimes scientific progress leaves us more puzzled than we were before. (Kahneman, 2011, p. 407) Happiness is a messy concept that is difficult to define and measure. Thus far, several terms referring to a general concept of “happiness” have been used. I have used the terms “happiness” and “well-being,” as well as the more general term “subjective well-being” (SWB), many survey instruments refer to “how happy” the participants are (van Praag & Ferrer-i-Carbonell, 2004), and still others talk about “life satisfaction” and “fulfillment” (Kim-Prieto et al., 2005). The most commonly used concept in the psychological literature is “subjective well-being” (SWB), which is meant to encompass all of these as a blanket term and to emphasize the subjective, or personal, nature of happiness, as it refers to one’s “affective and cognitive evaluation of one’s life” (KimPrieto et al., 2005, p.261). Many authors use several terms together in the same article to refer to the same concept, such as van Praag and others (2003), who “use the terms subjective wellbeing, satisfaction with life, and general satisfaction as interchangeable” (p. 29). In the current study, I will examine how participants define “happiness” and “well-being” and how these concepts may differ.  27     “Subjective Well-being” (SWB) All of these differences in terminology also signify differences, and potential difficulties, when examining the theoretical constructs underlying happiness and well-being. There are several types of problems: One is the nature of the construct itself, and another is its temporal character. In psychological research, subjective well-being (SWB) is often viewed as a single latent construct that exists in individuals in varying amounts or degrees. It is often hypothesized to be domain-specific, for example, having unique levels for work, leisure, education, and relationships (van Praag et al., 2003). 1 Therefore, the construct of SWB can be viewed as a “meta-construct” with many other smaller or more specialized constructs feeding into it. On the other hand, SWB may also be viewed as a single construct that feeds into these more specialized areas (see Headey et al., 1991 for a discussion of top-down versus bottom-up effects). One of the purposes of the current study is to find out how participants describe and define the concepts of “happiness” and “well-being” and how these two concepts may have different relationships with various domains in their lives. Van Praag, Frijters, and Ferrer-i-Carbonell (2003) postulate subjective well-being as twolayered: “where individual total SWB depends on the different subjective domain satisfactions [health, financial situation, job, leisure, housing, and environment]” (p. 29). Although they are measuring subjective well-being, their individual domain satisfactions depend on “objective variables, such as age, income, gender, and education” (p. 30). They recognize how difficult it is to be sure that one is indeed measuring the underlying construct that one is interested in; they recognize that they are making an “assumption” when they claim that there is “a correspondence between what one can measure, i.e. GS [general satisfaction], and the metaphysical concept” of satisfaction and well-being (p. 34). 1  However, happiness and well-being in each of these areas would still be equivalent.  28     Alongside these challenges, the difficulty of fixing happiness and well-being temporally also arises. These can exist in a single moment, over the course of day, a week, a year, and a lifetime. They may be constantly in flux and also remain somewhat stable over time. However, one’s judgment of one’s happiness and well-being at any one moment may differ substantially from their happiness and wellness in life overall. Priming effects may also influence which domains most impact people’s judgments of their happiness levels (Diener et al., 1999; Kahneman, 2011). Kim-Prieto, Diener, Tamir, Scollon and Diener (2005) propose a “time-sequential framework of subjective well-being,” which emphasizes that SWB “extends from the specific and concrete to the global and abstract: momentary experiences versus people’s global judgments about their entire lives” (p.261). This model incorporates the three disparate approaches taken in SWB research: first, the view that SWB is “a global assessment of life and its facets;” second, the view that SWB is “a recollection of past emotional experiences;” and third, the view that SWB is “an aggregation of multiple emotional reactions across time” (p. 262263). These measures are all moderately related to one another, which has lead many researchers to assume that “the assessments tap with varying degrees of measurement error an underlying latent construct of SWB” (p. 264).2 However, these correlations are low, despite the fact that measures of SWB show “substantial validity and reliability” (p. 265). This opens up the possibility that these measures are actually tapping into different constructs, although all of them are “participants’ reactions to their lives” (p. 265). The present study attempts to investigate this possibility by teasing apart potential differences in the constructs of “happiness” and “wellbeing.”  2  On the other hand, some researchers, such as Veenhoven (1993), argue that one approach is superior (in his case, SWB as “global assessment”).  29     Kim-Prieto, Diener, Tamir, Scollon, and Diener (2005) offer a unique and helpful insight into the debate by suggesting in their model that “while SWB is a unitary construct, it changes through the passage of time” and, therefore, the various components are systematically related to one another (p. 266). They frame SWB in a time-sequence of four stages, which are all related to one another and affect each other. The four stages are: “(A) life circumstances and events; (B) affective reactions to those events; (C) recall of one’s reactions; and (D) global evaluative judgment about one’s life” (Kim-Prieto et al., 2005, p.266). Because this model is hypothesized as continuous and circular in nature, new experiences influence SWB throughout these stages and may create “return loops” that influence people’s behaviours and reactions in all four stages (p. 267). This model also highlights the mechanism by which post-secondary educational pathways may influence happiness and well-being. They assert, “One important factor that influences long-term effects of emotional reactions is goals and personal desires… This is because although people can respond emotionally to events at any given moment, only the reactions that are relevant to general goals and concerns are likely to influence SWB” (KimPrieto et al., 2005, p. 275). They argue further for the important role of goals by suggesting that “life circumstances and events most influence SWB when they either hinder or benefit major goal progress, or signify whether an important goal has been obtained or lost” (Kim-Prieto et al., 2005, p. 275-276). The current study asserts that post-secondary education is one such goal that may impact happiness and well-being for the Paths on Life’s Way sample. The weakness in KimPrieto, Diener, Tamir, Scollon, and Diener’s (2005) approach is that “happiness” and “wellbeing” are still viewed as a singular, overarching concept that may not pay enough attention to the subtle differences within its subcompenents.  30     “Happiness” versus “Well-being” Jason Raibley makes a clear distinction between “happiness” and “well-being” in his 2011 article in the Journal of Happiness Studies. He argues that happiness is “conceptually, metaphysically, and empirically distinct from well-being” (p. 2, ¶ 3). His argument aligns with that of Sen (1993) in that he proposes that happiness only contributes to well-being when it is valued and is therefore a necessary, but not sufficient, condition for high levels of well-being (Raibley, 2011). He criticizes the approach taken by many researchers approaching happiness from a utilitarian standpoint who use the terms happiness, well-being, satisfaction, and others, as interchangeable (for example, Easterlin, 2005; van Praag et al., 2003). Raibley points out problems in the SWB model, and suggests that although episodic happiness is real and important, it is only one part of well-being as a whole and limits our research and discussion. He defines episodic happiness as “the property of feeling happy at a time” and suggests that although we often use the word happiness in daily speech in this sense, what we usually want to measure in social science research is a deeper and more stable sense of happiness that is more akin to well-being (Raibley, 2011, p. 4, ¶ 3). Hence, “happiness” and “well-being,” based on these theories and research, can be viewed as a single, unitary construct or separate, distinct constructs. This means that it is integral to investigate these constructs more deeply. People may create an aggregate of life experiences in many domains and add their emotional reactions and cognitive appraisals of those experiences to create a single general appraisal of their overall SWB; or, they may view parts of their life as unique entities and a single measure may impose an artificial restraint and value on something that is not a single construct at all. Through either process, these concepts could no doubt be  31     influenced by current mood, genetics, personality, cognitive heuristics, and many other factors as well (Headey et al., 1991; Kahneman, 2011). Thus, the method by which people create these judgments is unique and individual to a certain extent. This study will attempt to explain some of the ways in which people make these appraisals and how this helps us to understand happiness and well-being measures.  Measuring happiness. The use of Likert-scale questions is one of the major limitations to untangling these complicated nuances. However, leaders in the field support the use of this type of numerical scale. Helliwell and Barrington-Leigh (2010) point out that “the goal is to combine ease of response with enough answer categories to capture the relevant variance” and that this has “led to increasing use of an 11-point scale for measures of life satisfaction and similar life evaluations, within a scale bounded by zero and 10” (p. 734). Diener and others (2009) have also asserted this, concluding that scales with a greater number of options in an odd number is best. Van Praag, Frijters, and Ferrer-i-Carbonell (2003) also use this type of structure, pointing out that this approach is based on the assumption that when “two respondents give the same answer, they are assumed to enjoy similar satisfaction levels, implying that ordinal comparability is permitted” (p. 30). In other words, “ordinal interpersonal comparability” is one of the central assumptions when using these types of scales (p. 30). One of the difficulties of this type of measurement scale is that “it is not possible to control… for person-specific fixed effects, or, in other words, for people’s dispositions” (Blanchflower & Oswald, 2004, p. 1378). Researchers have found that the single greatest predictor of happiness is on the “nature” side of the debate (Diener et al., 1999; van Praag et al.,  32     2003; Kahneman, 2011). Psychologists argue that up to 60 percent of individual differences in happiness can be explained or predicted by genetic factors and that a further 20 or so percent can be explained by personality variables (Diener et al., 1999; Kahneman, 2011). In fact, Diener and others (1999) assert that “personality is one of the strongest and most consistent predictors of subjective well-being” (p.279). Helliwell and Putnam (2004) concur with the assertion that “the most powerful predictors of subjective well-being, as reported in the literature, are genetic makeup and personality factors, such as optimism and self-esteem” (p. 1435). Doing the math from these estimates, this leaves approximately 20 percent or less of variance that is explained by the ‘nurture’ side of the debate: in other words, demographic variables such as education, marriage, leisure, work, and family (Diener et al., 1999). Thus, it would seem, we have control over a very small portion of our overall level of happiness. If in fact these assertions are correct, I believe we are left with two choices: We can either use this information to dismiss the study of happiness as a waste of time, or use it as inspiration to do the most work possible to ensure that we can make the most of this 20 percent. Other researchers agree that this is still an important area of study (for example, Diener et al., 1999; Helliwell & Putnam, 2004; Kahneman & Krueger, 2006; Kahneman, 2011).  Correlates of happiness. As mentioned above in the early research into happiness and well-being, there are many correlates associated with these concepts. For the present study, three important ones are age, income, and gender. Blanchflower and Oswald (2004) found that happiness was “U-shaped in age,” with well-being reaching “a minimum, other things held constant, around the age of 40” (p. 1381). This is particularly interesting for the current study as most of the participants were 40  33     years of age at the time of the 2010 wave of the survey. Thus, according to Blanchflower and Oswald (2004), this may be the trough in their lifetime well-being levels. Helliwell and Putnam (2004) also point to the usual U-shape in subjective well-being scores over the lifespan, asserting that the middle-aged show the lowest levels of reported well-being. Income has also found to be correlated with happiness (Kahneman, 2011). This relationship, however, only holds up to a certain income, which is between US $60,000 and US $75,000 depending on the study, and the relationship becomes zero beyond that point (for example, Kahneman, 2011; Easterlin, 2001). As well, although those people “with incomes over $90,000 are nearly twice as likely to report being ‘very happy’ as are those with incomes below $20,000,” Kahneman et al. (2006) found that “there is hardly any difference between the highest income group and those in the $50,000-89,000 bracket” (p. 4). In a fascinating article entitled “Money Giveth, Money Taketh Away: The Dual Effect of Wealth on Happiness,” Quoidbach, Dunn, Petrides, and Mikolajczak (2008) find that while having more money may allow one to enjoy a greater variety of experiences, it may actually decrease one’s ability to savor those experiences. They found evidence to support the notion that “having access to the best things in life may actually undermine the ability to reap enjoyment from life’s small pleasures” (p. 10). These results support Daniel Gilbert’s (2006) hypothesis of “experience-stretching” in his famous book, Stumbling on Happiness. According to this hypothesis, people constantly make comparisons both to what they have actually experienced and can imagine experiencing, and this may decrease the joy they find in more ordinary day-to-day pleasures. In Canada, Helliwell and Barrington-Leigh (2010) find that income is not the most important predictor of happiness when looking at differences between provinces. When comparing the Atlantic provinces with BC, they uncover trust in neighbours, confidence in  34     police, seeing friends, and sense of belonging in community and province as more important to life satisfaction than average household income. Delle Fave and others (2011) also found that happiness was “primarily defined as a condition of psychological balance and harmony” and that “family and social relations” were most prominent among the life domains associated with happiness (Delle Fave et al., 2011, p.185). Kahneman (2011) agrees with this assertion, positing that “it is only a slight exaggeration to say that happiness is the experience of spending time with people you love and who love you” (p. 395). Gender is another important variable not often investigated in happiness research. Although not usually overtly studied and measured, Blanchflower and Oswald (2004) found that women have been “the biggest losers” in well-being since the 1970s in the US (p. 1359). They claim: “Whatever the consequences of anti female-discrimination policy elsewhere in society, it has apparently not been successful in either country [the US or Britain] in creating a feeling of rising well-being among women” (p. 1381). However, this difference is in relative gains and women still report the greatest well-being, as do “married people” and the “highly educated” (p. 1381). Stevenson and Wolfers (2007) replicated this finding in their article “The Paradox of Declining Female Happiness.” They found that although “the lives of women… have improved over the past 35 years,” women’s happiness has not increased; rather, “women’s happiness has declined both absolutely and relative to male happiness” (p. i, ¶ 1). Stevenson and Wolfers (2007) hypothesize the reasons for this decline as being inadvertent side effects of greater equality: For example, if happiness is assessed relative to outcomes for one’s reference group then greater equality may have led women to compare their outcomes to of the men around them… [and] find their relative position lower than when their reference group included only women. (Stevenson & Wolfers, 2007, p. 2)  35     As well, women’s expectations may have been raised by the women’s movement faster than society actually met these expectations, and so their “actual experienced lives” were disappointing (Stevenson & Wolfers, 2007, p. 2). They refer to this as a “paradox” because “women’s relative subjective well-being has fallen over a period in which objective measures point to robust improvements in their opportunities” (p. 4). Stevenson and Wolfers (2007) point to some of the potential reasons for why women may be worse off today than 35 years ago, such as higher divorce rates, increased rates of psychological disorders including anxiety and depression, and decreased social cohesion (Putnam, 2000). Women also have to juggle competing roles more so than men, such as being a mother, homemaker, and working professional all at once (Andres & Wyn, 2010). In this way, more education may also lead to more stress and decreased life balance. These impact both men and women, but may have gender-unique types of influence, especially insofar as women must manage to live up to both traditional and new expectations in life – both from outside and within themselves. Working from a capability approach, Robeyns (2003) found that “women in Western societies are worse off than men, since taken together the dimensions in which women are worse off are more important than those in which men lose out” (p. 87). In an overview of empirical studies related to the capabilities she outlines for examining gender inequality in Western societies, she finds that women report worse mental health, more anxiety and depression, greater psychological distress, less “extensive networks in the political, economic, and legal arenas,” and – most strikingly – women shoulder more responsibility in domestic work and non-market care (Robeyns, 2003, p. 79). This last inequity may be the key to the others as well, because researchers have also found that men spend more time per week than women on leisure activities, these activities are less interrupted by work and childcare, and that women face more  36     time-pressure, especially in dual-career households (Robeyns, 2003, p. 82). Some argue that women choose and want to spend more time in domestic roles; however, as Robeyns (2003) points out, “We do not know what men and women would choose if they were liberated from their gender roles and thus genuinely free to choose” (p. 86, emphasis in original). The stress of juggling multiple roles, and feeling social pressures to do so, may lead to decreased happiness for women. Other researchers, such as Helliwell and Putnam (2004) claim that there is “no strong and straightforward” relationship between gender and subjective well-being. They did find that men reported slightly higher levels of life satisfaction than women, and that “a gender effect sometimes arises and sometimes does not, depending on the specification of the model” (p. 1440). They suggest that this may be due to the fact that men on average report better physical health than women, and “self-assessed health status is the single most important correlate of subjective well-being” (Helliwell & Putnam, 2004, p. 1440). Thus, they hint that there may be a complex relationship between gender and subjective well-being and gender, possibly moderated by other variables, but do not elaborate. The current study will attempt to look further into this puzzle. 3  Causation in happiness research. To note a final difficulty within happiness research, causation presents a further theoretical hurdle. Without experimental methods, it is impossible to claim causation. However, using  3  Another interesting area of study is cross-cultural comparisons, which show cultural differences in how people conceptualize and report happiness levels (Diener et al., 1999). The Paths on Life’s Way survey was created and implemented in a single North American setting, which leads me to assume that although each person will of course have their own subjective interpretations of happiness and well-being, these can be compared to each other. In this I follow the lead of many other researchers (van Praag et al., 2003; Headey et al., 1991; Kim-Prieto et al., 2005; Diener et al., 1999; and others).  37     evidence such as temporal sequence some make claims to causation (Kim-Prieto et al., 2005). This may be a futile game of the chicken or the egg. Researchers have made strong arguments for causation in both directions: so-called top-down and bottom-up arguments (Headey et al., 1991). Based on the evidence on both sides, and following the recent theoretical model of KimPrieto, Diener, Tamir, Scollon, and Diener (2005), I work from the premise that there is a twoway causal relationship between education and happiness and well-being. This aligns with Andres and Wyn’s (2010) interpretations of the relationship between life circumstances and well-being within this same dataset. They describe well-being as “both an outcome of and a contributing factor to” other variables in the participants lives, such as employment, study, personal relationships, and family (Andres & Wyn, 2010, p. 190). Helliwell and Barrington-Leigh (2010) also point out this difficulty in happiness research. They assert that it is “difficult to identify an underlying causal structure” because most of the research is cross-sectional in nature, and that “the best way of dealing with this is to recognize the existence of two-way relationships, and hence to treat the results as indicative of a connection,” rather than causation (p. 746). They further argue that “life is complicated and features an impressively large number of plausible explanatory variables at both individual and societal levels” and so conclusions should be made with “humility” (p. 746). Blanchflower and Oswald (2004) point out this difficulty as well. They state that “individuals are not randomly assigned to events like divorce, so the calculation of, for example, the value of marriage describes an association in the data rather than clear cause-and-effect” (p. 1378). Helliwell and Putnam (2004) deal with this problem extensively in their study on “The social context of well-being” for the The Royal Society. They outline one of the major  38     methodological cautions in this research as “Reverse causation and selection bias” (p. 1437). In their work on social capital and well-being, they assert, to the extent that a sunny disposition itself affects a person’s location in the social structure, then correlations between social circumstance and subjective well-being might reflect the effects, not the causes of subjective well-being. In principle, this problem might even affect such ‘hard’ variables as income, but it seems even more threatening as regards social factors such as marital status and friendship patterns. It is especially apparent for the linkage between subjective well-being and subjective health status evaluations, both of which are likely to vary systematically with interpersonal differences in inherent optimism. (p. 1437) Thus, based on this evidence and these arguments, I avoid the use of causal language. Other researchers do the same, although many make exceptions for “stylistic convenience” (Helliwell & Putnam, 2004, p. 1437).  Gaps in the Literature The current study is based upon the findings outlined above, but follows even more closely from a more recent study called the Eudaimonic and Hedonic Happiness Investigation (EHHI), conducted by Delle Fave, Brdar, Freire, Vella-Brodrick, and Wissing (2011). Delle Fave et al. (2011) emphasize the importance of using mixed methods in research on happiness in order to capture these nuances and complexities. They use both quantitative Satisfaction with Life Scale (SWLS) data qualitative open-ended questions to “examine definitions and experiences of happiness” (Delle Fave et al., 2011, p.185). They use approximately the same number of participants (n=666) as the current study, but from seven different countries. Delle Fave et al. (2011) recognize that opposing camps have emerged in happiness research, and that more in depth exploration of the concept of happiness is needed. The present study follows from this assertion as well, and aligns with their premise:  39     Positive psychology scholars still face a basic challenge: to find agreement on terminology. As previously stated, well-being and happiness are often used interchangeably. For example, from the hedonic perspective happiness is often considered synonymous with life satisfaction. Despite significant advancements in understanding happiness at both the theoretical and methodological levels, one crucial topic has been neglected: what do lay people refer to, when they speak about happiness? (Delle Fave et al., 2011, p. 187) The current study fits well in the intersection between Delle Fave et al. (2011) and Raibley’s (2011) work. Raibley (2011) discusses the differences between happiness and wellbeing – positing them as two unique and distinct constructs – and Delle Fave et al. (2011) emphasize the importance of mixed methods in research on happiness in order to employ triangulation and get a more full picture of people’s responses to questions about happiness. They emphasize that this is missing in most research on happiness, which instead uses limited and often singular approaches to measure happiness. They also point to the weakness in many previous studies, which usually employ “samples of college students [in the US] making it difficult to generalize results” (Delle Fave et al., 2011, p. 187). Delle Fave et al. (2011) also differentiate overtly between happiness and well-being, in line with the present study. However, despite the fact that they argue against these two terms being “used as synonyms,” claim that this causes “ambiguities in the effort of defining these terms,” and argue for investigating what “lay people” refer to when they speak about these terms, they do not actually ask their participants to define well-being (Delle Fave et al., 2011, p. 187). Instead, they make a distinction: between “happiness” as a construct empirically evaluated through qualitative and quantitative assessments, and “well-being” as a broader umbrella construct, that may have different meanings in different theoretical perspectives and that includes happiness. (Delle Fave et al., 2011, p. 187).  40     Thus, participants are welcomed to define happiness in their own words (Delle Fave et al., 2011), but not well-being. This limitation is not overtly recognized by the researchers, who claim that their approach explores “conceptualizations of well-being from both a lay person’s perspective and from the researcher’s perspective” (Delle Fave et al., 2011, p. 190). Although the “long-term aim” of their project is to “explore the role and relevance of people attribute to various components of well-being in their definitions of happiness,” it seems that only half of the wellbeing/happiness distinction is given an exploratory analysis. Well-being is imposed upon the study as a larger construct, which may be accurate, but needs further investigation, particularly in a field that “has much to gain from new ideas, approaches and assessment instruments” (Delle Fave et al., 2011, p. 186). In a somewhat contradictory way, they also include well-being as a category within the psychological components of happiness definition, although they had already claimed that it was a “broader umbrella construct” which included happiness (Delle Fave et al., 2011, p. 187). The present study will attempt to disentangle this complicated relationship. The Paths on Life’s Way survey is much more extensive than the EHHI, which included only eight questions and a short socio-demographic questionnaire (Delle Fave et al., 2011). Another way in which the current study goes beyond Delle Fave et al.’s (2011) study is that the qualitative data is collected via interviews for the Paths on Life’s Way data, while the EHHI data is collected via open-ended survey questions. Interviews allow the participant to describe more fully their ideas, and allow the interviewer to ask probing questions to elicit more detailed responses. Following from the example of EHHI, however, the current study also “assumes that the results of both qualitative and quantitative approaches [will] highlight the importance of the same constituents and sources of happiness” (Delle Fave et al., 2011, p. 189).  41     My research is influenced by all these examples. Much like Delle Fave et al.’s (2011) study, I examine how people describe their happiness levels from both qualitative and quantitative data (with a similar sample size for the quantitative data); however, I incorporate Raibley’s notion that happiness and well-being are in fact two distinct constructs which require different questions and should not simply be lumped together into a meta-construct of “subjective well-being,” as is usually done. Although that approach is economical and easier, it eliminates most of the nuance that makes happiness and well-being such interesting and difficult objects of study.  Sen’s Contribution Another unique aspect of the current study is my use of Sen’s (1993) capabilities approach, which allows me to differentiate between well-being and happiness, and also to outline areas of life and freedoms that might be important to people irrelevant of the potential impact on their happiness. Consistent with the evidence outlined above, Sen argues that happiness is only one (perhaps small) part of well-being and that well-being is not the only valued goal for which people strive. Although much of the research summarized above limits happiness to a single number or scale, the present study uses qualitative interview questions to aid in the measurement and interpretation of such numerical data. In doing so, Sen’s (1985, 1993) distinction between functionings and capabilities allows a new type of happiness research that does not idolize the concept, but rather incorporates it in a complex web of possibilities, values, and realities. Sen’s (1993) capability approach is not used extensively in education or more generally (Robeyns, 2003a), partly because it “only provides a general framework, and not a fully fleshedout theory” (Robeyns, 2003b, p. 62). However, this exploratory study of happiness and well-  42     being benefits from this flexible approach, which allows the ideas and theories of happiness outlined above to be incorporated into the framework and study. Robeyns (2006) points out that one needs to “supplement this framework with additional social theories related to the topic one is analyzing” (p. 80). She instructs those using the capability approach: Note that the capability approach is not a theory that can explain poverty, inequality or well-being; instead, it rather provides a tool and a framework within which to conceptualize and evaluate these phenomena. Applying the capability approach to issues of policy and social change will therefore often require the addition of explanatory theories. (Robeyns, 2005, p. 94, emphasis in original) Importantly, the units to be measured or analyzed in this framework and study are individuals; however, the influence of social context can also be taken into account. As well, because this study focuses on gender as a potential moderating variable in the relationships among happiness, well-being, and other factors, it was essential that this framework allowed for gender comparisons. Sen’s approach does, and researchers such as Ingrid Robeyns (2003, 2006) and others (see, for example, Agarwal, Humphries, & Robeyns, 2003) have used his approach in the development of feminist economics and other gender analyses (as described above).  The Role of Education Higher education plays an important, but sometimes understated, role in promoting happiness and well-being at both a personal and societal level. Human capital theory, as propagated by Gary S. Becker and others, argues that both well-being and health are increased by investment in higher education. However, the size of the return on investments also depends on many other factors as well. He argues that “many forms of such investments include schooling, on-the-jobtraining, medical care, migration, and searching for information about prices and income” and that they differ “in the extent to which the connection between investment and return is  43     perceived” (Becker, 1964, p. 11). However, Becker (1964) further asserts that “all these investments improve skills, knowledge, or health, and thereby raise money or psychic income” (p. 11). Thus, education promotes both economic growth and also individual well-being from this perspective. More recently, Walter McMahon (2009) also focuses on the role of higher education as a provider of “private non-market benefits” as well as material benefits to the individual (p. 118). He points out that these benefits are often overlooked because they are poorly understood by researchers and that “the evidence is weaker that education contributes further to happiness beyond… income level” (p. 119). However, he asserts that education does indeed have many benefits aside from income alone, and that there are “distortions and underinvestment” because of “poor information” about the private non-market benefits of higher education (McMahon, 2009, p. 120). McMahon (2009) argues that better information is needed in order for individuals to make informed decisions about higher education. This is one of the justifications for the current study, as it aims to do exactly this. Although human capital theory is a justification for this research – namely, to describe and quantify the “happiness gains” from additional educational attainments – I also recognize criticisms of this approach. Ingrid Robeyns (2006) attacks this approach for being “economistic, fragmentized and exclusively instrumentalistic” (p. 69). She asserts that the human capital approach sees the world “through the eyes and disciplinary lenses of contemporary main-stream economics, a discipline that has increasingly blocked out the cultural, social and non-material dimensions of life” (p.72). Human capital theory disregards people’s social commitments and responsibilities and instead views individuals as “independent and unconstrained” (p. 80). Despite this, she does not advocate throwing out the “baby with the bathwater,” but rather – in  44     line with Sen (1997) – recognizes that human capital is an important part of understanding education’s function in society and then moves beyond it to acquire greater breadth and recognition of the complexity of its role. Education, from the view of a capability approach, is important not only for instrumental reasons, such as getting a more satisfying job, a higher income, and a better social position; but also for intrinsic reasons. In fact, Dreze and Sen (2002) outline five roles of education: education for its intrinsic importance, instrumental personal economic role, instrumental collective economic role, instrumental personal non-economic role, and instrumental collective noneconomic role. Thus, education can be valued for its own sake, or to help one find a better job; it maybe be valued for creating a more educated workforce, for allowing one to speak to people from another country in their language, or for helping to build a more tolerant society (Robeyns, 2006). These roles of education point to capabilities that are not recognized in a simple human capital approach. One possible mechanism by which post-secondary educational attainment may influence happiness and well-being is through their influence as valued goals. Inconsistent findings on the direct link between education and happiness are influenced by the fact that educational attainment affects evaluations of overall happiness and momentary experienced happiness differently. As pointed out by Kahneman (2011), “more education is associated with higher evaluation of one’s life, but not with greater experienced well-being” (p. 396). This may be because the more educated also report higher stress, presumably caused by higher-status and higher-responsibility jobs. However, Kahneman (2011) does not dismiss the importance of goals. In fact, he admits: In part because of these findings I have changed my mind about the definition of wellbeing. The goals that people set for themselves are so important to what they do and how  45     they feel about it that an exclusive focus on experienced well-being is not tenable. We cannot hold a concept of well-being that ignores what people want. (Kahneman, 2011, p. 402) Educational attainment is one such valued goal or “want” for many people, and arises often in the Paths on Life’s Study. Lesley Andres and Johanna Wyn (2010) examined the “hopes and dreams” of the Paths on Life’s Way participants in their book, The Making of a Generation: The Children of the 1970s in Adulthood. They assert that “not only did Canadian young adults in this study believe in post-secondary education, but also the vast majority of survey respondents in 1989 – 70 percent of females and 69 percent of males – expected to earn a bachelor’s degree or greater” (p. 112). When asked, the participants reported that they believed that post-secondary education would make them “better educated,” “prepare them for a job,” “increase their income,” and “give them a wider choice of jobs” (Andres & Wyn, 2010, p. 110). However, interestingly, only about one third felt that post-secondary education would make them “more informed citizens” (p. 110). Thus, the Paths on Life’s Way participants value education, but perhaps for mainly utilitarian reasons. One interview participant complained, “Unfortunately, post-secondary school must be attended in order to obtain a decent job” (female, as quoted in Andres & Wyn, 2010, p. 111). Approximately half of the participants felt post-secondary education was a “waste of time,” “only one option out of many,” or “a necessary evil” in 1989, and in 2003 an even smaller percentage were completely supportive of post-secondary education without any caveats (Andres & Wyn, 2010, p. 110-111). In spite of this, participants believed that it was necessary in order to move ahead in life and the vast majority participated in post-secondary education and indicated that given the chance to do it again, they would make the same educational choices (see Chapter 4).  46     These facts and findings make post-secondary education a complicated “valued goal” for the participants to pursue. Not necessarily inherently valued, educational attainments are seen as tickets to a better life, and therefore pursued by most of the people in the Paths on Life’s Way study. In the context of the current study, this means that post-secondary education may exhibit a complicated relationship with happiness, as participants have complicated attitudes and feelings towards it. Most studies on education and happiness do not focus on post-secondary, or higher, education, so this relatively unstudied area of happiness research awaits exploration.  The Paths on Life’s Way Project The Paths on Life’s Way Project provides a unique glimpse into the lives of Canadians as the only longitudinal study of youth in British Columbia and one of only a few in Canada (Andres, 2002). This study now spans 22 years (from 1988 to 2010) and provides “a detailed examination of students’ lives, choices, and post-secondary education and work experiences across different points in time and in relation to changing social and cultural conditions” (Andres, 2002, p. 1).  History and Sample This study began in 1989 with a stratified random sample of 10,000 high school graduates selected from the overall group of approximately 43,500 graduates in 1988 in British Columbia (Andres & Wyn, 2010). This study consists of baseline data, such as demographic information and high school grade point averages, collected in 1988; the first survey questionnaire (“Grade 12 Graduate Follow-up”) conducted in 1989; and four follow-up surveys in 1993, 1998, 2003, and 2010. The response rate for the first survey was 53.5% (when adjusted for undeliverable questionnaires, 57.7%) of the 10,000 graduates in the sampling frame, which represented 23% of  47     the entire cohort of 1988 high school graduates (Andres, 1989). The sample sizes went from 5,345 in 1989 to 2,077 in 1993 to 1,055 in 1998 to 733 in 2003 and, finally, 574 in the 2010 wave of the survey. The final sample size (the sample used for the analyses in this study) represents one percent of the entire population (the high school graduates of 1988 in British Columbia), but six percent of the 10,000-person sampling frame and 11% of the first survey questionnaire sample. The response rate in 2010 is nearly 80% of the 2003 sample. The interview sample was chosen using a “purposive or judgment sample strategy” in which three British Columbia high schools were selected – “one metropolitan, one urban-rural, and one remote” (Andres & Wyn, 2010, p. 7). The interviews were face-to-face and semistructured, and follow the waves of the survey study. The same 30 participants were interviewed six times between 1989 and 2003, and so far 19 participants have been interviewed for the 2010 wave.  48     Chapter 3: Methodology The data for the current study had already been collected as part of the larger Paths on Life’s Way Project. In this study, I use data from the most recent 2010 wave of the survey and interviews (n=574). I chose to limit my research to the most recent wave of the survey and interviews in order to delimit my study to cover a manageable amount of data, while still having access to prior data to aid in my interpretation of results and for areas of future research. I refer to data from all parts of the 2010 survey, but mainly analyze the approximately 100 items in the “Health and Well-being” section of the survey. As well, I use the qualitative data from the 2010 interviews. In doing so, I use data from Professor Andres’ questions as background material for my analysis, and I also generated qualitative data for my study by adding several questions to the interviews. All of the interviews were conducted by Professor Andres and recorded and transcribed.  An Apprenticeship in Research This study uses secondary data, both quantitative and qualitative, from the Paths on Life’s Way project at the University of British Columbia. I have worked as a graduate research assistant (GRA) to Professor Andres for three years. I began my work with the Paths on Life’s Way project in May of 2009. First, another GRA and I spent several months recoding the educational attainment variables from all waves of the survey. I use all of these variables in the present study to create the “highest post-secondary educational attainment” variable in the final analysis. After that was completed, two other GRAs and I helped Professor Andres edit the survey instrument for the 2010 mail out, and design and order incentives for the participants. One of the other GRAs and I designed forms in Access in which to input the all of the data from the new survey  49     in a convenient and controlled setting. We created validation codes for all variables to minimize mistakes when entering data and limit the amount of data cleanup at the end. In the new year we, with the help of our peers in the Survey Research Methods course taught by Professor Andres, prepared survey packages with the survey itself, a personalized letter of informed consent from Professor Andres, a research report, a stamped and addressed return envelope, and a pad of Paths on Life’s Way sticky notes. We did three waves of mail outs, along with two waves of reminder postcards. At this stage we also began entering data into the Access forms we had created. We entered both the quantitative and the qualitative data, so I was able to see the participants’ responses first-hand. Once all of the data had been entered and cleaned up, we began recoding previous surveys to ensure consistency across years, a job that we had been slowly working on since September 2010. Finally, in the spring of 2011, the collection of qualitative interview data began. Professor Andres conducted all of the interviews and recorded them. I and another GRA transcribed the interviews from the recordings. I transcribed all of the qualitative data arising from the questions on “happiness” and “well-being” in order to familiarize myself with the data and aid in my qualitative analysis and coding. As a result of my immersion in this project, the current study has grown and evolved in various stages from 2009 to 2012. My research questions arose not only from my own research interests, but also the stories that I saw emerging from the survey data. Thus, although I am using secondary data, it is a project that I have been involved with “on the ground,” so to speak, and have known intimately throughout all of the stages of the fifth survey mail out and interviews.  50     The 2010 Interviews The qualitative data are from interviews conducted by Professor Andres across British Columbia and Canada. Each interview was approximately one hour and took place in either the participants’ homes or a restaurant or coffee shop. Questions about the participants’ lives, work, education, life choices, and ideas about the “good life” (both conceptually and physically drawn on a “lifeline”) were asked, as well as questions about happiness and well-being. All participants gave their consent in the form of a written consent form. The questions on happiness and wellbeing included in the interview questions were as follows: 1. On a scale of 1 to 10, in general how happy would you say you are with your life? How did you decide on your answer? What factors influenced your decision? 2. On a scale of 1 to 10, how would you describe the extent to which your life is exciting? How did you decide on your answer? What factors influenced your decision? 3. On a scale of 1 to 10, how would you describe the extent to which your life is stressful? How did you decide on your answer? What factors influenced your decision? 4. In the past few months, how healthy have you felt physically? How did you decide on your answer? What factors influenced your decision? 5. In the past few months, how healthy have you felt mentally? How did you decide on your answer? What factors influenced your decision? 6. How do you define “happiness” and “well-being”? Are these the same or different, in your opinion? As mentioned above, the current study was conceptualized and designed during the process of data collection. The interviews took place after most of the surveys had been returned. Like many questionnaires, the happiness and well-being questions on the Paths on Life’s Way  51     survey are only able to give a limited glimpse into the participants’ feelings about themselves and their lives. The interview questions dug deeper to understand better how the interview participants, and survey participants by generalization, answered these questions.  The Interview Participants The Paths on Life’s Way interview participants graduated from high school in 1988 and 1989 and most were approaching their 40th birthdays in 2011 and 2012. This sample, which included 19 participants (more than 50% of the sample from the 2003 interviews), was comprised of eight men (42%) and eleven (58%) women. Their occupations ranged from lawyer to insurance broker to police officer to high school principal to nurse. They were living in locations across British Columbia, Alberta and Ontario, ranging from the rural North to small cities in the Okanagan to the heart of the cities of Vancouver and Calgary and Ottawa. Most interviews took place in the participants’ homes, although a handful of interviews were conducted in a coffee shop or restaurant. The interviews were approximately one hour in length, varying from 45 minutes to an hour and a half. The participants discussed many aspects of their lives, including their education, careers, visions of the “good life,” and whether or not they had made rational choices in their lives. They also discussed their personal relationships and family relationships, mostly as they pertained to the questions about the “good life,” rational choices, and happiness and well-being. Most of the participants were married or living in marriage-like relationships (in fact, all except one), and almost all had children (74%). Of the five who did not have children, three were men and two were female. The composition of this sample, in terms of marriage, children, and gender composition, is remarkably similar to the survey sample, although much smaller.  52     The 2010 Survey The fifth mailout of the Paths on Life’s Way survey took place in the spring of 2010. The survey was 36 pages and included 100 questions, as well as many more subquestions, which resulted in a total of over 1,300 variables from this survey alone. The first two sections of the 2010 Paths on Life’s Way survey (see Appendix A) include questions about participants’ post-secondary education in the time period from September 2003 to March 2010. Section C asks questions about work, training, income, and career and education goals for the same time period, as well as looking into the future. The next section includes demographic questions, and also questions about the participants’ background and household. Section E, which is used extensively in this thesis and makes up the bulk of the data used in the analyses, asks the participants questions about their health and well-being, including mental, physical, and social aspects, as well as general happiness and specific areas of satisfaction with life in different domains. This section concludes with questions about the participants’ children and a lengthy question about all of their activities on a monthly basis since September 2003. The final question of the survey gives the participants a chance to make general comments about access to post-secondary education; the cost of post-secondary education; work, education, and the economy; today’s family; the lives and times of their generation; and prospects for their children’s future.  The Survey Participants The Paths on Life’s Way participants graduated from high school in 1988 and most celebrated their 40th birthdays in 2010. Of the 2010 sample, which included 574 participants (78% of the sample from the 2003 mail out), 38.8% were men and 61.2% were women. 13.3% of the sample described themselves as single in 2010, while 9.8% described themselves as “living in a  53     marriage-like relationship with a partner.” The vast majority was married in 2010, 72.7%, and 2.3% and 1.7% were divorced and separated, respectively. Only one person from this sample was widowed. Overwhelmingly the participants described themselves as heterosexual, with only 1.1% describing themselves as gay, 0.7% describing themselves as lesbian, and 1.4% describing themselves as bisexual. Over three-quarters of the participants had not experienced any change in their marital status since the last wave of the survey in 2003; however, 22.5% reported that they had. In regard to children, 72.7% reported that they had children, while 27.3% – quite a large proportion – did not. In terms of living situations, 8.1% of the sample had returned to live with their parents at some point since 2003, 9.8% were still living with their parents, and 7.8% had their parents or inlaws living with them. Twenty percent of the participants had been first-time homebuyers since 2003. For those living with partners or spouses, 32.4% were living with a female partner and 50.2% were living with a male partner, which reflects the gender composition of the sample (approximately 60% female). Of the sample, only 12.4% were living alone. The majority of the sample were living with children (69.3%). There were also other people living with the participants as well, including parents (3.3%), brothers or sisters (2.6%), in-laws (2.1%), roommates or friends (1.4%), and other relatives (2.6%). The participants’ spouses are similar in age to the participants, with a mean age of 40.56 years, but with a fair bit of variability (SD=4.67, median and mode=40). Between 2003 and 2010, 30.7% of the Paths on Life’s Way survey participants had attended a post-secondary institution. This relatively high number (bearing in mind that this sample all graduated from high school in 1988) illustrates the changing dynamics of Canadian career trajectories and life trajectories. Sixty-five percent of those who attended post-secondary  54     institutions in this time were women, which is also a change from the patterns of previous generations. During the period between 2003 and 2010, 7.1% of the survey participants earned certificates, 2.3% earned diplomas, 2.8% earned bachelor’s degrees, 1.0% earned professional degrees, 3.1% earned master’s degrees, 1.4% earned doctoral degrees, and 0.5% completed apprenticeships (n=574). The remainder of the 30.7% had not yet completed their post-secondary programs or discontinued them in or before 2010. Before 2003, 36.2% of the Paths on Life’s Way participants had completed bachelor’s degrees, 25.4% had completed non-university (such as community college or vocational) programs, and 25.3% had completed professional or graduate degrees as their highest post-secondary educational attainment. Of the remaining participants, 4% had not participated in post-secondary education and 9.1% had not yet completed a post-secondary educational program. Each of these categories of highest post-secondary educational attainment changed differently over time in the twenty-two-year period from 1988 to 2010 (see Table 1). The percentage of non-participants gradually shrunk over time, although it was never very large. The percentage of non-completers decreased dramatically, especially from 1993 to 1998. This shows that many of the participants, who all graduated from high school in 1988, took more than four years to complete their post-secondary education, but almost all completed their highest educational degree in less than ten years. The number of non-university credentials is fairly consistent over time after 1998. Although approximately a quarter of the participants attain this, the category remains fairly static over time. This illustrates that most of those who completed a non-university credential did so relatively soon after high school, and most do not pursue this as their highest level of study after that point in time. The percentage of participants with a bachelor’s degree as their highest degree increased dramatically in 1998 to almost 40%, but then  55     slowly decreased in 2003 and 2010. The explanation for this is that some of the participants who had already earned bachelor’s degrees went on to earn professional and graduate degrees, which then became their highest degree. The professional and graduate degrees category grew much larger in the three later waves of the study, understandably because these degrees take much more time to complete. The largest growth between years was in this category from 1993 to 1998, with an explosive increase of 17% (see Table 1).  Table 1 Highest post-secondary educational attainment by survey year  Year  NonParticipant/NonCompleter  Non-University Credential  Bachelor's Degree  Professional and Graduate Degree  1993 1998 2003 2010  45.8% 16.2% 13.1% 11.1%  21.8% 25.1% 25.4% 25.6%  30.3% 39.5% 36.2% 35.5%  2.1% 19.2% 25.3% 27.7% (Paths on Life's Way, 2010)  In 2010, the percentage of non-participants and non-completers is lower than the combined percentage in 2003. The percentage of participants with a non-university credential or bachelor’s degree as their highest post-secondary educational attainment decreases, while the percentage of participants with professional and graduate degrees as their highest degree increases by six percent. This continues the trend from previous years. A larger and larger percentage of participants moves to the right of this table in each wave of the survey. This clearly illustrates the life-long nature of higher education in British Columbia. Post-secondary education is not limited to the five to ten years immediately following high school, but rather continues into middle age for this sample.  56     These different levels of education showed marked gender differences. While approximately equal percentages of the men and the women completed bachelors and professional or graduate degrees in or before 2003, a slightly larger percentage of women (28.8%) completed non-university studies than men (25.3%), and a slightly larger percentage of men than women were non-completers (10.3% and 8.4%) and non-participants (5.1% and 3.9%). These gender differences were fairly consistent over time, with women holding approximately 65% of the non-university credentials and bachelor’s degrees over these three waves. The proportion of women in the professional or graduate degrees category consistently grew by a small amount from 57.0% in 1993 to 60.4% in 1998 to 62.5% in 2003. This is on par with their overall representation in the sample, and suggests relative equality in the rates of earning professional and graduate degrees for this sample. Looking at the 2010 data for a more detailed breakdown of men’s and women’s highest educational attainments, one can see that although there are many similarities between the two, some interesting differences emerge as well (see Table 2). In 2010, 12.6% of men and 10.3% of women were still non-participants or non-completers of post-secondary education. None of the women held an apprenticeship as their highest educational credential, while 4% of the men did. Non-university credentials (including certificates, diplomas, and associate’s degrees) were more common for women (27%) than men (20.6%). Thirty-five percent of women and 36.3% of men held bachelor’s degrees as their highest post-secondary educational attainment. However, less of the men than the women held professional degrees as their highest degree: Only 11.2% of men, and 15.10% of women held these. This is reversed for graduate degrees. Almost 17% of men held a graduate degree as their highest degree, while 12.5% of women held this type of degree.  57     Table 2 Highest educational attainment in 2010 by gender  Gender  NonParticipant/ NonCompleter  Apprenticeship  NonUniversity Credential  Bachelor's Degree  Professional Degree  Men Women  12.6% 10.3%  4.0% 0.0%  20.6% 27.0%  36.3% 35.0%  11.2% 15.1%  Graduate Degree 16.6% 12.5% (Paths on Life's Way, 2010)  In 2010 (n=574), the participants were generally satisfied with their educational choices, although not as much as with their choices regarding work. Fifty-seven percent of participants said that if they could choose again they would make the same educational choices. Seven percent of the participants had formally enrolled in a post-secondary institution for the 20102011 year, and a further 24.7% said that they had wanted to participate in post-secondary education or training in the past two years, but had not been able to for a variety of reasons. Looking at student loans, 46.4% of the 2010 sample said that they had taken a student loan at some point in their lives. The average total amount of that student loan was CA $17,506.27 (SD=14,341.97). The average amount still left owing in 2010 was CA $1,054.02 (SD=4,486.66), although 92.3% of participants had completely paid off their loans by 2010. In terms of the participants’ aspirations concerning post-secondary education in 2010, there was great variety. Just over twenty-seven percent wanted to achieve bachelor’s degrees as their highest level of education, while a further 26.8% wanted to complete master’s degrees. Another 13.4% wanted to complete professional degrees, such as medicine, law, or engineering, and 9.2% wanted community college diplomas or certificates. Eight percent of the sample desired a doctoral degree and 4.2% wished to have an apprenticeship, vocational, or trade school  58     as their highest level of education. Only 1.8% wanted their highest level of education to be a secondary school diploma. Participants’ expectations, given “the realities of today’s educational system and work world,” were somewhat different. Thirty percent expected to achieve a bachelor’s degree as their highest level of education, while only 22.3% expected to complete a master’s degree. Another 11.9% expected to complete a professional degree, and 11.7% expected a community college diploma or certificate. Five percent of the sample expected a doctoral degree and 4.4% expected to have an apprenticeship, vocational, or trade school as their highest level of education. Almost two percent expected their highest level of education to be a secondary school diploma. The sample has tended to become more biased towards the well educated over time (see Andres & Adamuti-Trache, 2008), but also reflects the tendency of this generation to return to the postsecondary educational system at several points in their lives. The Paths on Life’s Way sample is highly educated, and their spouses/partners are as well, although – interestingly – to a somewhat lesser extent than the participants themselves. One quarter of the participants’ spouses/partners had completed a bachelor’s degree, 16.3% had a community college diploma or certificate, 9.8% had a professional degree, 9.8% had an apprenticeship, vocational, or trade school, and 9.6% had a master’s degree. Of the remaining, 1.6% had completed a doctoral degree, while 14.3% had a high school diploma or less. This slight difference in educational levels may also be impacted by the gender composition of the sample (61.2% women), which means that the majority of the spouses/partners are male. There has been much recent attention paid to the fact that university campuses are increasingly femaledominated (in terms of the student body at least) and concern that “the boys are falling behind.” In Canada, while “young women with university education are seen as generation-makers, the  59     young men who have not achieved a post-secondary education are positioned over time as outsiders” (Andres & Wyn, 2010, p. 91, italics in original) and may struggle to find life satisfaction in a system that increasingly values formal educational credentials. However, this may also be due to the fact that men may receive more formal and informal training at work, as well as being able to gain more promotions, without the help of further post-secondary education. In terms of work, 96.5% of the participants had been employed at some point since 2003 with a mean of 2.14 jobs (SD=1.59). Slightly more men were employed in paid work than women (98% versus 96%). Women, however, held slightly more jobs on average. The mean for women was 2.18 (SD=1.69), while the mean for men was 2.07 (SD=1.41). However, the median for both groups was two, and the mode for both groups was one. Again this points to the changing career trajectories of British Columbians, who can no longer expect to work one job – or even in one field – for their entire careers, as their parents could. Of the jobs that the participants currently held, most were full-time. Those who held parttime jobs were more likely to hold more than one job. Almost fifteen percent of the participants had jobs that required them to work shifts. Most participants were satisfied with their line of work: three quarters would have chosen the same line of work if given the choice again. In their positions at work, most participants classified themselves as “an employee without supervisory responsibilities” (34.7%). Of these, 67.4% were women and 32.6% were men. Women were slightly overrepresented in this category (in comparison to the 61.2% female composition of the overall sample). Another 23.3% of the participants had “limited supervisory or management responsibilities” of five persons or less, and 22.9% were “an employee with more extensive  60     supervisory or management responsibilities.” Here women made up a smaller percentage of the total, with 57.0% and 54.4% respectively (slightly less than their 61.2% of the total sample). Quite a large percentage of the participants were self-employed: 17.5% of the overall sample. Of those who were self-employed in the Paths on Life’s Way sample, 10.2% did not have employees, while 7.3% did. As well, 73.2% of those who were self-employed without employees were women, while only 35.0% of those who were self-employed with employees were women. Considering women made up 61.2% of the sample, they are both over- and underrepresented in these categories. Finally, 1.8% of the participants described themselves as unpaid homemakers. This group included nine women and only one man. Although almost all of the participants were employed, 18.3% of them were looking for another job. The Paths on Life’s Way sample is also relatively high earning. Their average household income in 2009 (before taxes) was CA $120,098.87 (SD=79,586.34) with a very large degree of variability in the sample. The range was CA $750,000 and the median and mode were both CA $100,000. The average household income differed by the gender of the participant: Men had a mean household income of $130,064.96 (SD=85,609.56) with a median income of $112,000 and mode of $100,000, while women had a mean household income of $113,587.29 (SD=74,811.73) with a median and mode of $100,000. The range for women was larger than that of men ($750,000 versus $500,000) because one participant reported a household income of $0. 4 The greater earnings of men may also be due to the fact that the partners of the participants had, on average, less education than the participants themselves, and because men are usually the higher  4  Excluding these extreme cases, the range for both men and women was CA $597,500, with a minimum of $2,500 and a maximum of $500,000. The mean without the extreme cases was $119,371.61 (SD=$74,655.65). The range for the men was $488,000, with a minimum of $12,000 and a maximum of $500,000; the mean was $130,677.96 (SD=$85,342.34). The range for the women was $497,500, with a minimum of $2,500 and a maximum of $500,000; the mean was $111,973.63 (SD=$65,840.40). These are not significantly different from the results reported above, and so the original numbers were retained.  61     earners in a household (although this is changing), the women in the study (who represented over half of the sample) were married to men with lower educational levels than those in the study. This would lead to lower household income as well. The survey participants now live all across British Columbia, Canada, and the world. However, the largest percentage of participants lives in Vancouver (10.3%). Approximately three percent of the participants live in each of these communities: Victoria, Calgary, Kelowna, Prince George, and Kamloops. Smaller percentages of the participants are spread amongst 151 different towns and cities. Strikingly, 81.9% of the participants still live in British Columbia. The second most popular province is Alberta with 7.5%. A further 2.3% live in Ontario, and 2.3% have immigrated to the United States. Individuals within the sample have lived in places around the world, such as the Netherlands, Australia, the United Kingdom, Belize, and several countries in Asia and Africa. The number and variety of places they have travelled is even more extensive and varied. Looking at the participants’ lifestyles, 98.6% own personal computers and 97.4% have Internet access in their homes. Slightly more than sixty percent have pets, including dogs, cats, horses, birds and reptiles. The majority of the sample engage in exercise two or three times a week (40.1%), while large percentages also engage in exercise either once per week or four to five times per week (19.2% and 22.3% respectively). Approximately nine percent of the participants do not engage in exercise at all, and another nine percent engage in exercise more than more than five times a week. Most of the participants (55.6%) have participated in other forms of education and learning outside of the formal education system since 2003. These educational activities were diverse in nature, the most popular being first aid courses (6.6%). Yoga, scuba diving, music lessons, professional development workshops, and language classes  62     were also common (3% each). However, this list again was long and varied (including over 600 separate items) and worthy of its own study. The Paths on Life’s Way sample is a fascinating group of people. From their education to their work to their travel and family, each has a unique and captivating story. One ubiquitous feature of these individuals’ stories is change, and their ability to grow and adapt over time was one of the most intriguing aspects of their stories. These individuals have overcome tragedies and celebrated accomplishments small and large, and often completely transformed their lives – sometimes more than once – when needed or desired. One drawback of the survey sample is that the sample is by definition restricted to high school graduates in British Columbia, which means that those who did not complete high school are not represented in this sample. The interview sample, on the other hand, is not restricted in this way. There is also a slight bias in the survey sample towards those who have completed some form of higher education. However, as asserted by Andres and Adamuti-Trache (2008), although “the sample has been affected by attrition with a slight bias toward women and those continuing post-secondary education… overall it has remained remarkably representative of the original participant group” (p. 118). The authors also maintain, “the degree of sample bias suggests that the findings… are generalizable to similar populations” (Andres & AdamutiTrache, 2008, p. 141).  Ethical Considerations The present study uses secondary data from the Paths on Life’s Way Project. All interview participants and survey participants consented to the research by signing a consent form. The consent form states that only Professor Lesley Andres and her “research assistants… will have  63     access to the data for coding and analytical purposes.” It also explains, “Data from all phases of this study will be analyzed by [Professor Andres], together with [her] students and colleagues, for long term trends. You [the participant] will NEVER be identified by name in reports and publications resulting from this study" (Andres, 2010b, p.23, emphasis in original; see Appendix A). All participants agreed and none expressed any concerns. All interview participants are referred to by pseudonyms in this study, which indicate their gender but bear no resemblance to their actual names. As well, all information that might expose their identities is omitted from the interview quotations in this thesis.  Data Analysis Qualitative Analysis To analyze the qualitative data, I examined the interview data that emerged from the above questions to define and conceptualize “happiness” and “well-being” from the perspective of the study participants, as well as the different ways participants approached the task of measuring their own “happiness” and “well-being” when answering survey questions. First, I read through all of the interview transcripts to familiarize myself with the participants’ responses. At this stage, I simply explored what themes and connecting ideas organically emerged. I did this using both my understanding of the theoretical considerations of the field and a grounded theory approach that places priority on the participants’ descriptions and explanations of these concepts (Charmaz, 2006). Next, I loaded the interview transcripts into ATLAS-ti, and went about the task of identifying the different themes that were most prominent and important and developing descriptive labels for these themes. Finally, again in ATLAS-ti, I organized the data according to these labels and ensured that I have found all of the relevant quotations and not missed any  64     additional connecting ideas between interviews and themes. In this process, the theoretical lenses mentioned above, as well as my own stance as a researcher, informed my work. It is important to note that participants were guided towards an evaluative concept of happiness, rather than an “on-line” or experienced concept, such as that investigated by Kahneman (2011), Csikszentmihalyi (1990), and others in studies that look at happiness in individual moments and accumulate those over time. However, evaluative happiness is recognized and used by many researchers (for example, van Praag et al., 2003; Kim-Prieto et al., 2005), and even Kahneman (2011), as the champion of “experienced well-being,” has since acknowledged, “Life satisfaction is not a flawed measure of [people’s] well-being” (p. 397). He asserts that a “hybrid view,” which incorporates both “how people feel as they live” and “on how they feel when they think about their life” (Kahneman, 2011, p. 402). This study attempts to tap into both areas while acknowledging that participants are guided towards an evaluative stance by the questions asked of them.  Quantitative Analysis The objective of these analyses was to perform a structural analysis of the constructs of “happiness” and “well-being” from the existing survey items using the participants’ explanations of their process of answering the survey questions about these concepts as a guide. To analyze the quantitative data, I used factor analysis to identify factors mapping onto the constructs of “happiness” and “well-being” from the many questions related to these constructs found in the Paths on Life’s Way survey. Because I hypothesized these as two distinct factors potentially containing other sub-factors as well, I used an exploratory factor analysis (EFA) to test how  65     many factors are necessary to explain the relationships between the responses on the questions related to happiness and well-being on the Paths on Life’s Way survey. In the final step of this analysis, I examined the relationship between post-secondary aspirations, expectations, and attainment and happiness and well-being in this sample using regression analyses. I used several dependent variables, including questions about overall happiness, mental and physical well-being, and life satisfaction. I controlled for potentially influential variables, including health, marital status, and presence or absence of children. Furthermore, I examined the relationship between post-secondary aspirations, expectations, and attainment and happiness and well-being incorporating gender as a potential moderating variable. I hypothesized gender as a variable that significantly alters the relationship between postsecondary aspirations, expectations, and attainment and happiness and well-being. Specifically, I suspected that post-secondary attainment provides different benefits to the happiness and wellbeing of women and men due to the different impact that higher education has on their lives. Thus, I ran analyses separately for men and for women in order to compare the two groups. As with all research in the social sciences, the relationships between these variables are complex and difficult to disentangle. This analysis attempts to uncover some of these complexities.  66     Chapter 4: Results Definitions of Happiness and Well-being Professor Andres asked the interview participants a total of six questions about happiness and well-being. All participants agreed to answer the questions. First, she explained to the participants that she also had a survey sample from the 1988 high school graduating class in BC, which she had been following for the same period of time that she had been conducting these interviews. Five questions were taken directly from the survey. The first was: “On a scale of one to ten, in general how happy would you say you are with your life?” Professor Andres instructed the participants to give a numerical value and then explain how they went about choosing that value: essentially, how did they measure their own happiness? The next questions were: “On a scale of 1 to 10, how would you describe your life: one, very dull, ten, very exciting?” and “On a scale of 1 to 10, how would you describe the extent to which your life is stressful?” The fourth and fifth questions were about health: “In the past few months, how healthy have you felt physically?” and “In the past few months, how healthy have you felt mentally?” The scale was again from one to ten. The final question was the main research question of this study: “How do you define happiness and well-being? Do you see a difference between the two?” First I provide a brief descriptive overview of the interview participants’ responses. The participants’ happiness rating on the Likert scale ranged from five to 10, with a response mean of 7.81 (SD=1.40) and a mode of seven. In terms of how exciting their lives were, participants’ responses ranged from two to 10, with a mode of five and a mean of 6.19 (SD=1.97). The participants ranged in their stress ratings from a low of three to a high of 10 (M=5.91, SD=2.07). Participants on average rated themselves as more mentally than physically healthy. There was also slightly more variability in the ratings of physical health. The mean response for physical  67     health was 6.25 (SD=2.34); however, responses ranged from two to 9.5 (if the participant responded “between nine and ten”) on the ten-point scale. On the other hand, the responses for mental health ranged from three to nine, with a mean of 7.14 (SD=2.00) and two modes at eight and 8.5 (if the participant responded “between eight and nine”).  Table 3 Ratings of happiness and well-being by interview participants  How happy? How exciting? How stressful? Physically healthy? Mentally healthy?  Mean  Mode  Median  Standard Deviation  7.81 6.19 5.91 6.25 7.14  7 5 7 8 8.5  8 6 5.5 7 8  1.40 1.97 2.07 2.34 2.00 (Paths on Life's Way, 2010)  When describing their lives more generally, the participants mentioned various factors related to happiness and well-being. Five of the participants (26%) had sought counseling since 2003, four of whom were women. Two had been prescribed antidepressants in this time, both of whom were women. Four described themselves as having been depressed since 2003 (21%), and three of the four were women. Five of the participants were struggling with health problems (26%), and three of the five were men. Illness and death in the family, especially of parents or parents-in-law, were fairly common. Eight participants mentioned this (50%), including six women and two men. Finally, three of the participants had struggled with personal relationship problems with their spouse or partner since 2003 (16%). All of the participants who mentioned these problems were women. As mentioned above, eleven of the 19 participants were women (58%), all but one had spouses or partners, and 14 of the 19 (74%) had children.  68     How Participants Measure Their Happiness Several themes emerged from my initial reading of the qualitative data for these questions. When they were asked to rate themselves on this happiness scale, the participants talked about many different domains of life, including family, work, leisure, and travel, and some themes cut across these domains and participants. The first theme that emerged was the idea that happiness is relative to what one can imagine. As one man put it: “I think a ten would be if I got to choose what I would like to do, so some of that, of the [actual happiness rating], is sometimes you get to choose and sometimes there’s just life throwing things at you” (Ivan). These were often upward comparisons: A comparison to what the participant could imagine his or life looking like under ideal circumstances. As one participant stated, “I’m not a ten because ‘I can imagine myself eating ice cream on a beach somewhere’” (Mike). Another thought that he might be happier if he “had more money and more time” (Larry). One woman felt that “if the business can get resolved, and if I get into grad school, and like those other things kinda fall into place, then the happiness would return [sic]” (Sally). One participant summarized it neatly as “we always want more” (Ivan). One participant even felt that a ten on the happiness scale was impossible, because she thought that “you have to have such an ideal, it has to be so perfect to be a ten… In life, I don’t think anything’s a ten… there’s always room for something great to happen” (Lisa). This inability to ever reach a ten was also hinted at by another participant who thought that “sometimes we’re unrealistic in our expectations of happiness sometimes too because we think we need more than we do to be happy” (Susan). However, other participants made downward comparisons. One stated, “I really can’t justify being unhappy” because of all the things I have in my life (Lisa). This same participant  69     further explained, “I don’t have regrets, I don’t have concerns, I don’t have to worry about meeting basic needs, and I think that all goes hand-in-hand with being happy” (Lisa). Another woman stated that she couldn’t “think of anything that [she] would add to [her] life that would make it better than it already is” (Claire). However, she also admitted, “I always compare myself to my sister because she lives in [a posh neighborhood in Vancouver], so she does all of these crazy exercise classes and goes to the movies and the theatre and eats out at restaurants all the time, and I’m a real homebody” (Claire). One man explained that he was pretty happy because life “could be worse” (Conrad). Thus, these participants seemed to compare their lives to an imagined, possible life and judge it relative to what it could be. This was both negative, if they could imagine things being better and were therefore less happy, and positive, if they couldn’t imagine anything that would increase their present happiness. The examples above illustrate that sometimes not striving towards something more and simply accepting what one has may be instrumental in happiness. Looking to one’s personal past and present for comparison was also common: “I’ve come full circle… Yeah, if you had asked me that two years ago or three years ago, I’d be like a two” (Tara). This idea that the participants could “look back” and judge their happiness in comparison to other points in time was very common (Tara). The idea that happiness is relative to other times in one’s own life came up again and again in participants’ responses. Sometimes this was also in relation to one’s future. One participant expressed that the stress of her oldest son was “the only reason why I’m not a ten,” but that she was looking to the future and “realize[d] that it will come” (Tina). In contrast, some participants also emphasized the importance of living in the present moment, especially in reference to popular books, such as The Power of Now by Eckhart Tolle, and the “mindfulness movement” becoming more common along with yoga and Eastern  70     religious practices, such as Buddhism. Four participants referred directly to this, and one woman commented that “people focus too much on the past and then let the past identify who they are and let the past hold them back from doing things that wouldn’t ordinarily do or focus on the past [sic]” (Claire). Another expressed that the good life was “just enjoying life, being in the present… that is what this ‘having it all’ is all about: being able to be present right here and right now” (Amanda). Thus, although people made these comparisons through time, some also seemed to be resisting the tendency to do this. There was also the idea that happiness is an outlook or mental approach to life. One man discussed at several points in his interview the fact that “I look at every situation and I don’t look at it as being bad, I just look at it as a challenge…and looking forward through it” (Ivan). A female participant also mentioned the importance of one’s perspective: She thought that we are often “unrealistic” in what we think we need to be happy (Susan). One of the men also made this point, saying, “The good life is being able to live within your means and not always be striving for something else but really being able to appreciate what you’ve got, but [also] to have meaningful challenges to work towards” (Mike). Another participant asserted that “as long as you’re making the best of it, that’s the good life” (Ivan). One man even argued that the concepts of happiness and positivity were “synonymous on a level” (Dennis). He explained that he didn’t “use the word happy,” but he believed in “being positive” and just that (Dennis). Here, happiness was entirely outlook, entirely “a state of mind” and “what you make of your own world” (Dennis). Another man emphasized that we “can wreck our own day” and even though life “can hand us some curve balls,” well-being is “trying to be prepared at least” (Clive). Another woman emphasized this point as well; she said, “I think a good life is doing what you can with what you have” (Sally).  71     One interesting finding related to outlook was that a participant suffering from serious and rare health condition rated his happiness and mental health on par with the average of the other participants, none of whom are suffering from this type of illness. This participant also rated his health (“between a four and five”) equal to that of another participant who was concerned about her weight. This illustrates profoundly the subjective and mental nature of these concepts. Although an outside observer looking into these two people’s lives may guess that their happiness and health would be very different, they felt themselves at a similar point on these scales. This may illustrate the effects of adaptation or habituation, which is a term to explain the decreased affect of an experience of either pleasure or pain on us if it occurs on successive occasions (Gilbert, 2006, p. 144; see also, Kahneman, 2011), but may also simply shed light on what’s important for happiness: As the participant mentioned above stated, the good life may only require “having family and stuff like that; people, family, friends” (Conrad). This outlook shaped a happiness level quite contrary to what most might guess from the outside looking in. Most of the participants made references to the inevitability of change over time, and how this related to the way they gauged their own happiness. As one participant put it: “The dynamic of life… it’s not symmetrical. It’s always changing; things are changing, dynamically changing. So, I think… you have to stick with it, you can always make choices to change direction and I think that’s important” (Ivan). This focus on change is connected the last, and most common, theme. This last theme is the idea that happiness is freedom to do and be what one wants to do and be. This theme cut across all of the interviews and emphasizes the importance of Sen’s (1993, 1985) concept of capabilities. Participants’ references to this concept were sometimes  72     direct: for example, “I just want freedom… I want freedom to do the things I want to do” (Susan), “I think a ten would be if I got to choose what I would like to do” (Ivan), and “I’m just not happy where I am in my life, I’m not happy with the fact that I can’t do the things that I want to, that I think would help me be happy” (Troy). Another participant described the good life as “having the freedom to go and do what you want” (Nora). This focus on freedom was strongly linked to time. As one woman discussed when comparing her idea of the “good life” from 1989 to the present day, I want more time, I want more time to be able to just do the things I want to do with the people I want to do them with. So, I mean, family is still a priority; you know, my relationship is still a priority. I want to continue to work in some capacity or other for as long as I possibly can. I don’t want to step away from that, but it’s also not the focus. It’s kinda like, it’s a place for me to go and a place for me to be and interact with people and talk and kinda be challenged in certain ways, but it’s not the focus of my whole thought process. So, the career is still important but maybe not as much, and it’s more of a means to an end, I guess. And the house, having the home and the dog and all that stuff, I don’t really care. I’d kinda much rather have something small and portable so you can just kind of… I don’t know. I really wanna be free to live somewhere else, or just have more time. So that’s kinda my main priority, which I don’t think I valued as much back then as I do now. So, I’d say that’s probably the only thing that’s changed [since 1989]. (Susan) Others referred to freedom more indirectly. One way a participant did this was by describing happiness as “making decisions that are best to make you feel good inside” (Lisa). Another woman stated that she “would like to work less and enjoy [her] free time more… being able to travel, and eat out, and see friends and family, that and just enjoying life” (Amanda). Interestingly, men tended to emphasize freedom more directly. However, in all of the interviews being able to “more or less live the way you want to live” came up as an important precursor to happiness and the “good life” (Morris).  73     Happiness is not well-being. All of the participants differentiated between “happiness” and “well-being,” although all of the participants also felt that the two concepts were related to one another. Some felt that the two were “flip sides of the same coin” (Troy); while others felt that they were much more separate. The most common perspective was that “happiness is a part of well-being” (Susan). As one woman stated, “I think well-being is more all-encompassing in terms of physical health as well as mental health, and happiness I consider to be more mental” (Susan). She visualized it as “one feeds into the other” and that “happiness [is] one dimension of well-being” (Susan). Another woman emphasized the similarities between the two but added that “well-being is even more attached to the physical states and how physical and mental are interdigitated with each other or articulated with each other” (Nora). One man asserted that happiness and well-being were “very similar” if one defined happiness as “contentment,” rather than a momentary, “superficial thing” (Morris). However, he also added that well-being includes a “physical component” as well, and was therefore a “more holistic reading” (Morris). One man made an interesting distinction between happiness and well-being as the difference between dreams and reality: “I think there is a difference…everyone wants to be happy and I think people wanna have the dream in their head of what they want and that would make them happy, [but]… I think your well-being is more dealing with what you’re given and working your way through that” (Ivan). He felt that this was always a dynamic process, because life “is not symmetrical, it’s always changing” (Ivan). In a similar vein, one woman differentiated between well-being as doing the things you should do and happiness being doing the things you want to do. She stated, “I think well-being is day-to-day life decisions, as opposed to happiness, [which is] making decisions that are best to make you feel good inside” (Lisa). She  74     went on to explain that for well-being “you might pass up the cupcake,” but for happiness “you need it” (Lisa). Another distinction made between happiness and well-being was that “one’s well-being is always a work in motion” and that although “we can wreck our own day” and “life can hand us some curve balls,” well-being is “trying to be prepared at least” (Dennis). On the other hand, this man viewed happiness as “a state of mind” that was synonymous with being “positive” and “what you make of your own world” (Dennis). Similarly, one woman argued that happiness “is more a state of mood,” “a combination of everything that’s going on that would get to that point, so in your personal, career, life, whatever, relationships” while well-being is “more of how I am” in “the physical realm, the mental realm, the spiritual realm” (Sally). She felt that happiness would be visible to the outside world, while well-being would not. However, she thought that well-being would lead to happiness. Contrasting this, some participants felt that happiness was not a required part of wellbeing. As one woman stated, “I think you can have a general sense of well-being without being incredibly happy” (Janice). She felt that this was because “happiness is an elusive thing” and that there are just “happier times than others” (Janice). Other participants corroborate this opinion: “Happiness, happiness is nice, but is it necessary? Unfortunately, it’s not necessary. Which is, I mean, I think there’s more, I think genuine happiness is difficult” (Claire). As well, another woman stated that she thought that “your well-being can be good, … but it doesn’t necessarily mean that you’re happy” (Tara). She explained that “you need things in your life to make you happy, or people in your life to make you happy, or for you to do things in your life to make you happy” (Tara). For her, “triathlons” made her happy (Tara). Thus, although the well-being part made her “calm” and “centered,” it didn’t necessarily make her happy (Tara). However, other  75     participants who felt that you could also be happy even though you may be “physically not in a good place” (Mike). On the other hand, some participants felt that happiness and well-being were so related that one could not occur without the other as well. Some thought happiness was an integral part of well-being. One man asserted that he didn’t “think you can have well-being without being happy” (Larry). Some also thought that well-being was a necessary ingredient for happiness. “If you don’t have a sense of well-being, then I don’t think you can be happy,” one woman asserted (Tina). She added that she thought that “you can be happy if you’re not physically well, if you choose to overcome that mentally, but… well-being is the whole package, physically, emotionally (Tina). Another asserted that “happiness lends itself to a sense of well-being” (Clive) and that “in order to have a good well-being you have to be a happy person” (Clive). These participants believed that “it would be incomplete well-being if you weren’t happy” (Larry). Thus, wading through these definitions and distinctions, it becomes obvious that there are a plethora of views of happiness and well-being. However, these are joined by some common threads. Happiness was viewed by all as a mental entity, while well-being incorporated many other aspects, including a physical aspect as well. They also recognized unanimously that happiness was not a constant, but rather something that would change over time. Their responses mesh well with Sen’s (1985) assertion that although “happiness is of obvious and direct relevance to well-being, it is inadequate as a representation of well-being” (p.189). They also clearly argued that “happiness is basically a mental state, and it ignores other aspects of a person’s well-being” (Sen, 1985, p.188). Well-being to the participants was always seen as a conglomerate of many aspects of life and one’s being. From these findings, two metaphors  76     emerged to guide us toward defining these concepts.  Happiness as balance.  Figure 2. Happiness as balance.  One obvious tension in participants’ ways of measuring their happiness is between two main ideas that surfaced in almost all of the interviews. The first is setting goals and achieving them as a way to happiness, and the other is being content and not always striving for more. Often the same participant would raise both of these aspects. On the one hand, participants approached happiness as something “rational,” something to strive for, and goal that could be accomplished; on the other hand, they emphasized the need to accept those things that were out of their control and find acceptance with many aspects of life which did not go according to plan (see Figure 2). Thus, it seemed that happiness, as one part of an overall sense of well-being, emerged as from the balance between being able to or actually achieving desired goals and maintaining an attitude  77     of acceptance or contentment to what actually occurs in one’s life. As one man expressed it, this balance can arise from the ability to “live within your means and not always be striving for something else, but really be able to appreciate what [you’ve], but to have meaningful challenges to work towards” (Mike). One woman emphasized that she didn’t feel she needed “to be insanely wealthy,” but just needed “balance, balance and be happy” (Tina). Several participants pointed out that when they were “more balanced” they felt happier (Tina), and that being “out of balance” was a hindrance to happiness (Nora). The idea that happiness is accomplishing goals or attaining desired outcomes in one’s life arose in all of the interviews. Several participants referred to goals in relation to happiness, and one woman commented that she imagined that if she “managed to get closer to that [goal] then [she’d] be happier” (Susan). One man cautioned against becoming “overly content” in life (Mike). However, these goals were not usually in relation to money or “things.” Several participants mentioned being wary of getting “too caught up in the consumerism of most of our society” and attempting to focus on one’s own goals rather than those of other people (Mike). The pressure to meet society’s expectations came up as an impediment to happiness. Trying to be “where most people are supposed to be at 40” was stressful, particularly for a couple of the men in the sample (Morris). On the other hand, one participant talked about the fact that she was happy because “I have [all the things I’ve been thinking about since high school] all now” (Nora). Thus, goals that had been achieved or goals that the participants felt that they could achieve seemed to increase happiness, while those that seemed impossible or unlikely seemed to decrease happiness. The value of having achievable goals in relation to happiness has been discussed by many other researchers (see, for example, Diener et al., 1999; Kahneman, 2011). One common goal emerged in almost half of the interviews: Many of the participants  78     talked about the idea of “downsizing” or “simplifying” one’s life to become happier. The participants described the pressure of popular consumer culture, which constrained them and limited their freedom and well-being. Several participants were engaged in an active backlash against these constraining ideals in the form of a desire to “downsize” and “simplify” their lives. When describing the “good life” most of the participants had described a house, car, family, and good job in 1989 – the vision of their 1950s parents and television – but now that they had reached 40 and attained and enjoyed these things, they were beginning to acutely feel the loss of freedom that seemed to be a necessary byproduct (Andres & Wyn, 2010). This aligns with the findings of Andres and Wyn (2010) who point out that these participants must operate within an “accelerated” world to maintain a complicated balance between “education-work-family” and may shift their values over time (p. 196). Participants already felt in 2003 that life seemed to be moving in fast-forward and was very “fast-paced,” and they echoed those sentiments in 2010 (female as quoted in Andres & Wyn, 2010, p. 220). One participant talked about how he tried to avoid becoming “too content” or “too caught up in the consumerism of most of our society” and “always striving for something else” (Mike). One woman argued, “I think in order to be happy you have to be content” (Claire). Another participant pointed to the fact that most people “aren’t really all that reflexive” and most are into “consumption” (Nora). This was seen as an impediment to happiness. One participant stated that in order to reduce stress, “we’re trying to sell our house so we can downsize” (Tina). The participants thought that simplifying or downsizing their lives would lead to less stress and greater happiness. As one woman asserted, “I think I’m happier with less” (Claire). One participant felt that she lacked free time due to “mundane things that you have to do” and that it was “burdensome just buying all this stuff, having all this stuff, maintaining all this stuff, paying  79     for all this stuff” (Susan). As part of a deliberate attempt to increase her and her family’s happiness, she decided to make it her goal “to simplify, and downsize, and have more time together [with her family]” (Susan). The participants were also willing to put happiness on hold in order to focus on other aspects of life. One participant explained that she, “didn’t really put a value on happiness for a long time because… [she] saw it as something that maybe would come later” (Janice). This same participant discussed balancing different aspects of life to achieve well-being: “Even though I was unhappy in my work, I had a personal life that was very happy, so that balanced out a little bit, and now I’m not working at all, so… [laughs] There you go!” (Janice). Another woman supported this position as well, “I was fine, but knew I wasn’t happy, but time passed…and I got happier” (Claire). One man pointed out that happiness is also not the be all and end all in life. He stated, “I think our society tends to go terribly wrong in thinking we have to be happy all the time or there’s something wrong with us” (Morris). The participants felt that part of the balance for finding happiness was also foregoing happiness along the way at some points in time. Participants were willing to sacrifice their happiness at some moments in time, especially for children, but also for jobs and education, in order to gain what they predicted would be a greater happiness in the future. Thus, “temporary” and “deeper” happiness(es) were both present in participants’ discussions about this topic. Kahneman (2011), Gilbert (2006), and Kim-Prieto et al. (2005) also emphasize that happiness can exist both in the moment and in a more holistic, “overall” sense. Other authors have theorized happiness in ways similar to the participants in terms of balance. For example, Marar (2003) contrasts “freedom” and “justification” in his conceptualization of happiness. This way of viewing happiness as a balancing act between being  80     able to do what one wants, but also being tied to meaningful people and activities, fits well with the notions that the participants mention in their interviews. There is a constant tension between what people “should” do and have and be in order to be happy and then the loss of freedom this may cost them. This loss of freedom seems to be a cost in quality of life in itself, and also to take a toll on the participants’ well-being as well. On the other hand, a lack of possessions, relationships, and career or work responsibilities can also be detrimental to well-being. Marar (2003) deals extensively with this tension, claiming that it is at the root of happiness’s unattainable and elusive qualities. The participants also allude to this in their descriptions of how happy they are and how they define happiness. One can infer from their statements that there is never a permanent state of balance: throughout their ever-changing lives, the participants are continuously shifting the balance, resulting in different levels of happiness.  The “gears” of well-being.  Figure 3. Gears of well-being.  81     From the themes mentioned at the beginning of this section, and the ways in which participants’ described measuring and rating their own happiness, several key ideas become apparent: Happiness is not constant, but rather varies over time, and comparisons across time impact happiness levels; happiness is influenced by a variety of valued domains of life, and the importance of each domain changes over time, but the most important ingredient in life is optimal balance between these domains; and, finally, happiness is only a part of a person’s overall well-being, and the importance of happiness itself may vary over time and situation. From these ideas emerges a metaphor for well-being: Well-being can be visualized as a set of interlocking gears (see Figure 3). This simple machine, a transmission consisting of many gears working in tandem, which is visualized with three gears but more accurately would include many more, produces mechanical advantage if properly aligned and if all of the gears are moving smoothly. Thus, the idea of mechanical advantage would represent optimal levels of well-being, which would produce happiness, at a certain point in a person's life, and this would change over time and situation. Mechanical advantage could also be gained through different gear ratios, which would mean adjusting the "gears" of social relationships, health, work, and others to have in order to maintain optimal efficiency as well as functioning. Therefore, these gear ratios would change over time to produce similar overall mechanical advantage. For example, a difficult period of time in a person's life, such as dealing with the death of a loved one, could be thought of as riding up a hill – it is necessary to change gears to get to the top, but once there one can switch back to a different combination in order to again gain mechanical advantage. Optimal well-being requires different gear ratios at the age of 22 in university than at the age of 40 with children and  82     a mortgage. Surrounding this metaphor is Sen’s idea of capabilities and functionings. One needs the freedom and ability to switch between these gears, and if one gets “stuck,” the entire machine will stall. This would result in a person being unwell. Although this idea seems quite logical and mechanistic for something as ethereal as wellbeing, this type of mindset is exhibited by many of the participants to greater or lesser degrees. The participants, for the most part, felt that they could more or less plan their lives, and happiness was often mentioned as an explicit goal of this planning. As one woman emphasized, it’s “rational to try to be happy” and to act to promote one’s happiness (Susan). Many of them set goals in relation to happiness and felt that they could control their happiness to a certain degree. Importantly, those who mentioned this sense of control over their happiness often scored themselves as happier than those who didn’t. Some participants were wary of setting “unrealistic” expectations for happiness (Susan) and some were willing to put happiness “on hold” while accomplishing other things (Janice). This may be partly due to the “acceleration of time” as “life becomes layered with multiple tasks, responsibilities, and options” (Andres & Wyn, 2010, p. 191). As well, in line with Sen (1999) and Kahneman (2011), people may have goals that transcend their current well-being and happiness, but which may deliver future happiness. The interlocking gears of well-being include many domains of life. The idea of the “happy family” came up in almost every woman’s interview. Well-being, and happiness in life, was often equated with “children” or other familial and interpersonal concepts. One woman described the “good life” as “a happy family home” (Patricia). These usually appeared alongside career, material, and personal concepts, but were much more prevalent in women’s interviews than men’s. However, spending time with their spouse and children emerged as important for all  83     the participants who had spouses and children. One man emphasized the importance of his wife and children, and felt that he was living the good life because of them. He was “happy and content with what [his] parents had,” even if he had also given up other freedoms and opportunities in order to attain this life (Larry). Interestingly, children also arose as the impediment to well-being for one woman with two teenage boys, and as a source of some negative emotional reactions for three women with young children and babies. As one woman expressed it, she’s “very grateful for the kids and [her] husband and [her] life, but it’s a really tough go” (Elaine). This was especially linked to balancing work and childcare responsibilities and costs. Thus, children and family were both part of participants’ visions of well-being and sometimes a source of difficulty for participants as well. This was also the case with extended family, particularly parents and parents-in-law. Many of the participants were experiencing the stress of coping with parents who were ill or coping with the loss of a parent. This also detracted from well-being, or prevented it altogether, as one woman expressed. Work was mentioned by all participants, some of whom found that their work increased their sense of well-being and gave them a sense of meaning and valued goals, and some of whom found work to be a source of stress and made them less happy. There was approximately an equal split between the two, and often participants mentioned both of these two contrasting impacts of work on their lives. Women, however, were more likely to mention the stress of struggling to balance work and family, and also discrimination in the workplace. One participant pointed out that women might “get passed over because [they] have to be there for [their] kids and [their] kids are always going to be sick” (Elaine). Financial and material aspects of life usually were raised by participants as hindering rather than helping one’s happiness, although  84     one participant felt that the excitement of moving into a bigger, more expensive home had given her a positive sense of excitement. Most of the participants, conversely, mentioned money and material goods as stressors that detracted from their quality of life. As mentioned by Andres and Wyn (2010) about this same sample, the participants are “more aware of the ongoing tensions involved in managing work and family life” (p. 211). The interview respondents talked about struggling to keep both of these areas of their lives moving in harmony; however, most spent a much greater portion of the interview discussing family than work. In regard to time, none of the participants mentioned wanting more time for work, but many wanted “more time with family” and “more time with friends” (Sally). Andres and Wyn (2010) also found that even though the importance participants placed on “succeeding at work or a career and having enough money to live well” declined over the 15year period they examined, almost no one rated these as unimportant, and approximately half rated these as very important. However, “relationships with partners, children, parents, and friends continued to be rated as very important” over time (Andres & Wyn, 2010, p.86). When adjusting the “gears of well-being,” the participants must make complicated decisions based on their capabilities, knowledge, prior experiences, and best guesses about the future. As Elster (2009) explains in his outline of rational action, the participants must choose “among the options of which [they are] aware according to the possible consequences [they] attribute to them,” which are shaped by their desires, beliefs, and the information they receive – which all mutually influence one another (p. 23). Rubenson and Desjardins (2009) also discuss the complexity of this type of decision-making (in reference to participation in adult education) making use of Sen’s (1999) capability approach. They emphasize Sen’s (1999) assertion that capabilities and functionings depend not only on external and internal resources, but also on  85     “individuals knowing about the range of possibilities of how these resources can be used to realize things that matter to them and knowing how to do so” (Rubenson & Desjardins, 2009, p. 196). Likewise, the participants in this study must forecast their emotional reactions to future events – and may not always do so accurately (Dunn et al., 2008; Dunn et al., 2007; Kahneman et al., 2006) – and then “set the stage” for their lives to unfold in these more or less planned ways. Well-being then, relies upon many life domains, prior experience, a view to the future, and the operation of all these aspects in synchrony within a person’s self and life. In this complicated process, well-being may also depend “less on the objective events one encounters than on how those events are construed, dealt with, and shared with others” (Dunn et al., 2007, p. 7). In particular, due to the unpredictable nature of the future, participants are constantly making decisions within the context of uncertainty. This ongoing process of valuing, aligning, and balancing various parts of life is a process in which the participants more or less “consciously manage their well-being” (Andres & Wyn, 2010, p. 191). This may have become a new form of consumption, one that relies on both material and immaterial goods. This is also a very individualistic endeavor. One woman’s comments sum the individual nature of this quest succinctly: It’s my personal belief that I’m responsible for me, nobody else is responsible for me, and if I’m unhappy, that’s my own fault… So, I’m responsible for my own well-being, and I’m also responsible for my happiness, but I think of the two as totally separate, so I can have a sense of well-being but not be happy. (Claire) Summary From these two metaphors, one can create broad definitions of the concepts of “happiness” and “well-being.” It is impossible to create specific definitions, as one of the most obvious  86     characteristics of participants’ descriptions was that these were very personal and unique concepts that depended on the individual and his or her values. Researchers often deftly avoid defining happiness, even when claiming to measure it. However, some useful definitions have been put forward. Blanchflower and Oswald (2004) define happiness as “the degree to which an individual judges the overall quality of his or her life as favorable” (p. 1360). Kahneman (2011), somewhat humorously, defines happiness as “the experience of spending time with people you love and who love you” (p. 395). Gilbert (2006) defines happiness in his characteristically dry and playful way as “the you-know-I-mean feeling” that makes us “tongue-tied when we try to define it, as though some bratty child had just challenged us to say what the word the means and in the process made a truly compelling case for corporal punishment” (p. 33). As a subjective experience, it can be defined in innumerable ways, and “people seem pleased to use this one word to indicate a host of different things, which has created a tremendous terminological mess on which several fine scholarly careers have been based” (Gilbert, 2006, p. 33). The present study will join the others and jump into the “tar pit” of defining happiness. Broadly stated, based upon the participants responses, happiness is defined as “a positive feeling towards and evaluation of one’s self and life at a particular point or period in time, which includes an optimal balance between achievement and acceptance.” In contrast, well-being is defined as “a positive and healthy overall state of being in many areas of life at a particular point or period in time, including one’s physical state, mental state, social state, work state, and others, in which all of these domains interrelate and impact one another substantially.” Both of these are influenced by people’s unique values, goals, and life circumstances, although some commonalities emerge as well.  87     In both of these definitions I have used the phrase “at a particular point or period in time,” which is conducive to measurement, but overlooks Kim-Prieto et al.’s (2005) exploration of the temporal nature of happiness. Happiness researchers have been divided into different “camps,” some of which examine happiness in the moment, “emotional happiness” or “experienced well-being,” and some of which look at more general evaluations including larger time frames, “judgmental happiness” or “life satisfaction” (Gilbert, 2006; Kahneman, 2011). The questions used for the current study were framed from an evaluative rather than emotional standpoint; however, I believe that it is difficult to completely disentangle the two. Several researchers also argue that we act more for the benefit of our “remembering” than our “experiencing” selves (Kahneman, 2011). As one female participant argued, “I think that’s the biggest thing: Creating really powerful, profound, lasting memories” (Sally). Therefore, in the present study and for the purposes of this analysis, the focus was on happiness as a judgment of one’s life, with the recognition that short-term, on-line emotion will play an important role in these judgments as well. People engage in an ongoing act of balancing acceptance and achievement in order to be happy. This balancing act requires that people be capable of achieving various valued states and goals, and also that they actually achieve some of these. This balance spans many areas of life, and arises from a sense of well-being that consists of various domains of life turning in synchrony, much like a simple machine of interlocking gears. These life domains shift in importance over time and their varying levels of importance differ between individuals. One overwhelming finding, however, is the importance of social relationships, which were mentioned by every participant in their interviews.  88     Two problems for measurement that may emerge from these findings and definitions include the following: Firstly, some participants feel that a ten is an “impossibility” and so the scale cannot be viewed as comprising equal distances between points, and, secondly, happiness is not constant, or even consistently valued, over time and across the lifespan. For example, for a survey participant, the distance between eight and nine would be much smaller than the distance between nine and 10 if 10 were thought to be impossible by a particular participant. As well, Sen’s (1999) example of the fasting versus starving man comes into play here: Is the participant who is choosing to forgo happiness and rates herself as a six on the scale giving the same answer as another participant who feels that happiness is absolutely unattainable and rates himself a six? These might look on paper like the same thing, but really show two totally different phenomena. These two facts could lead to large inaccuracies in comparing levels of happiness between individuals, although subjective measures will always include individual differences in how to define and measure those concepts between subjects, as mentioned above. The next section of this study will look at how the variables related to the constructs of “happiness” and “well-being” in the survey group into categories using factor analysis in order to see if the themes and relationships that emerged from the interview data are also present in the survey data. This will be the first step towards devising a more comprehensive way of measuring happiness and well-being for this sample. The interview findings suggest that happiness is a separate construct from well-being, but depends upon well-being, which suggests that viewing “subjective well-being” (SWB) as a coherent, all-encompassing whole is misleading and simplistic. However, because participants recognized happiness as something distinct, and perhaps more limited, than well-being, it might be possible to use a more simplistic measure of happiness in the analysis of post-secondary educational attainment. The overwhelming message,  89     however, is that these measurements cannot be assumed to mean the same to all, and cannot be assumed to extend to all. While general impressions can be read from simple Likert-scale measures, human happiness and well-being are concepts far to complex to summarize in a number, numbers, or even an entire thesis for that matter.  Happiness and Well-being as Survey Variables Relevant Survey Questions Descriptive statistics. I conducted an initial descriptive analysis of the happiness data. The Paths on Life’s Way survey asks many questions related to happiness and well-being in the “Health and Well-being” section of the survey. There are approximately 100 questions (including the subquestions) about the participants’ health, well-being, and happiness in this section. Perhaps reflecting their feelings on the importance of these questions, or their eagerness to think about their well-being and happiness, almost all participants answered these questions, and the questions about happiness and well-being in particular were answered by all participants. Examining the 2010 survey (n=574), participants rated themselves an average of 7.81 (SD=1.52) on a ten-point scale for how happy they were generally with their lives. The median and mode were both eight. As for how exciting their lives were, participants gave an average rating of 6.83 (SD=1.61; median and mode=7.0). In terms of their stress, participants rated their lives an average of 6.45 (SD=1.92; median and mode=7.0) on ten-point scale of stressfulness. When it came to their physical health, participants felt an average of 7.16 (SD=1.83) on a ten-point scale of physically healthy. On this variable, the median was seven, but the mode was eight. Similarly, for mentally healthy,  90     participants rated themselves a mean of 7.09 (SD=1.84) and the most commonly occurring score was eight, while fifty percent of the scores fell at or below seven (see Table 4).  Table 4 General happiness and well-being questions  Likert-scale Question (1-10)  Mean  Median  Mode  Standard Deviation  How happy are you with your life? How exciting is your life? How stressful is your life? How physically health have you felt? How mentally healthy have you felt?  7.81 6.83 6.45 7.16 7.09  8 7 7 7 7  8 7 7 8 8  1.52 1.61 1.92 1.83 1.84 (Paths on Life's Way, 2010)  When asked how satisfied they were with the way things had turned out in their lives, the responses were mainly positive (see Table 5 and Table 6). Participants rated their satisfaction on a five-point Likert scale running from one, “very dissatisfied,” to five, “very satisfied.” The mean for satisfaction with “my personal life” was 4.20 (SD=1.04). Family life was rated somewhat higher on average at 4.3 (SD=1.03). Work and career was lower at 4.01 (SD=1.05). The participants were very satisfied with where they lived (M=4.26, SD=0.99). This was also the case with their educational attainment (M=4.24, SD=0.96). However, when looking at careers and educational opportunities for their entire generation, participants were somewhat less optimistic. They rated their satisfaction with these at 3.76 and 3.91 respectively (SD=0.99,0.90). Participants were “somewhat satisfied” with their health (M=4.03, SD=1.04) and “the way things were going” in general these days (M=3.99, SD= 1.04), but more enthusiastic about “the way their life had unfolded to date” (M=4.11, SD=0.96). In terms of time (M=3.48, SD=1.15) and fitness level (M=3.28, SD=1.22), participants were only slightly positive. This was also the case  91     for their satisfaction with educational opportunities for today’s children (M=3.36, SD=1.07) and their own children (M=3.43, SD=1.04). The participants were somewhat dissatisfied with the condition of our natural environment (M=2.64, SD=1.08).  Table 5 Satisfaction questions  How satisfied are you with…*  Mean  Median  Mode  Standard Deviation  your personal life? your family life? your work or career? where you live? your educational attainments? your health? the way things are going? the way your life has unfolded? your time for activities? your fitness level?  4.20 4.30 4.01 4.26 4.24 3.76 3.99 4.11 3.48 3.28  4 5 4 5 4 4 4 4 4 4  5 5 4 5 5 4 4 4 4 4  1.04 1.03 1.05 0.99 0.96 0.99 1.04 0.96 1.15 1.22  *A satisfaction scale of one to five.  (Paths on Life's Way, 2010)  Table 6 Satisfaction with time spent on various activities  Satisfaction with time spent...*  Mean  Median  Mode  Standard Deviation  with spouse or partner with children with work on personal time on professional development with friends with parents with sports buddies with volunteer participation  3.65 3.88 3.66 3.07 3.24 3.02 3.29 3.25 3.25  4 4 4 3 3 3 3 3 3  4 5 4 2 3 2 4 3 3  1.18 1.19 1.15 1.20 1.03 1.15 1.18 1.05 1.20  *A satisfaction scale of one to five.  (Paths on Life's Way, 2010)  92     When asked about the things they would need to enhance their overall well-being, participants rated their extent of agreement to ten items (see Table 7). The scale was from “strongly agree” to “strongly disagree” with a “neutral” midpoint and the option to check “not applicable.” More leisure time was ranked most highly (M=4.12, SD=0.99), followed by more family time (M= 4.01, SD=0.94) and more money (M=3.81, SD=1.08). A more supportive workplace (M=3.12, SD=1.08) was met with neutrality as an important factor in enhancing the participants’ overall well-being. In terms of family, the participants’ expressed slight disagreement with needing a more supportive immediate (M=2.62, SD=1.10) or extended family (M=2.60, SD=1.03). Those who had children (M=2.99, SD=1.15) and elderly parents (M=2.90, SD=1.17) to care for expressed neutrality to needing more help with care for these family members. Time devoted to work did not emerge as important avenue for enhancing well-being according to the participants: they slightly disagreed that more time to devote to work would increase their well-being (M=2.26, SD=0.93). However, a more supportive workplace met with more agreement (M=3.12, SD=1.08). Finally, participants did not feel that more post-secondary education would enhance their overall well-being. The mean response was 2.68 (SD=1.12), where 2 was “disagree” and 3 was “neutral.” Thus, time and money emerged as the items that participants felt were most likely to increase their overall well-being. This was reflected in the interview participants’ descriptions of their happiness levels as well.  93     Table 7 Enhancing well-being questions  To enhance my well-being, I need…*  Mean  Median  Mode  Standard Deviation  more leisure time. more family time. more time for work. more money. a more supportive workplace. a more supportive immediate family. a more supportive extended family. more help with childcare. more help with eldercare. more post-secondary education.  4.12 4.01 2.26 3.81 3.12 2.62 2.60 2.99 2.90 2.68  4 4 2 4 3 2 2 3 3 2  5 4 2 4 3 2 2 2 3 2  0.99 0.94 0.93 1.08 1.08 1.10 1.03 1.15 1.17 1.12  *An agreement scale of one to five.  (Paths on Life's Way, 2010)  This question included one other item, an “other” category. This one was rated with the highest agreement (quite naturally, since participants themselves provided the item for themselves). The average agreement ranking was 4.49 (SD=0.81). The 47 “other” responses can be broken down into several categories: improved personal relationships with friends and partners (11), improved health (9), a better society (6), self-improvement and time with oneself (6), more time for religious activities (3), a better job (3), better education (3), a better home (3), more time to connect with nature (2), and having a pet (1). Personal relationships included such things as “supportive partners,” “having a partner, being single is the WORST,” and “more ‘date nights’ with my wife.” Health included “better health,” “better mental health,” and “more sleep – two small children with sleep difficulties effects overall well-being at every level [sic].” A better society included “more social consciousness,” “more liberal drug laws,” and “more volunteer time.” Finally, self-improvement and self-care included “accepting myself,” “be more of a go getter,” “more determination to change,” and “more time alone” (x2).  94     The Paths on Life’s Way survey also asked participants about how important different values are in their lives. Here the participants rated each item’s importance on a scale of one to five, with one being not at all important, and five being very important (see Table 8). Living a psychologically healthy lifestyle and achieving a balance between work and non-work activities were the most highly ranked items in terms of importance (M=4.63,4.64; SD=0.59,0.59). Following close behind these were “time together with my spouse/partner” (M=4.60, SD=0.62) and “quality time to spend with my children” (M=4.59, SD=0.84). Also important were a physically healthy lifestyle (M=4.55, SD= 0.58), good relationships with parents (M=4.51, SD=0.72), and time for leisure activities (M=4.47, SD=0.61). Also important, but ranked as less so relative to the above-mentioned items, were “respect for the natural environment” (M=4.39, SD=0.73), “a socially just society” (M=4.39, SD=0.76), “enough money to live well” (M=4.33, SD=0.64), “the institution of marriage” (M=4.16, SD=1.09), and “developing an independent lifestyle” (M=4.08, SD=0.84). The least highly ranked items were “living in a culturally diverse community” (M=3.49, SD=1.03), “involvement in community affairs” (M=3.58, SD=0.92), and “regular involvement in organized learning activities” (M=3.49, SD=0.94). The only item to score an average of “not very important” was “participation in religious activities” (M=2.46, SD=1.4), although this item exhibited a greater degree of variability than the others.  95     Table 8 Importance of values questions  How important to you is the value of...*  Mean  Median  Mode  Standard Deviation  developing and maintaining friendships succeeding at work or career to be involved in community affairs to have enough money to live well to have a good relationship with parents to live a psychologically healthy lifestyle to have a balance between work and nonto have quality time with children the institution of marriage a culturally diverse community to have an independent lifestyle to live a physically healthy lifestyle to have time with your partner to be involved in learning activities to participate in religious activities to have time for leisure activities respect for natural environment a socially just society  4.48 4.28 3.58 4.33 4.51 4.63 4.64 4.59 4.16 3.59 4.08 4.55 4.60 3.49 2.46 4.47 4.39 4.39  5 4 4 4 5 5 5 5 5 4 4 5 5 4 2 5 5 5  5 4 4 4 5 5 5 5 5 4 4 5 5 4 1 5 5 5  0.68 0.70 0.92 0.64 0.72 0.59 0.59 0.84 1.09 1.03 0.84 0.58 0.62 0.94 1.38 0.61 0.73 0.76  *An importance scale of one to five.  (Paths on Life's Way, 2010)  Gender differences. When examining the descriptive statistics by gender, some interesting themes emerge. 5 Firstly, there were several areas in which men and women were very similar rather than different. Women and men reported themselves as equally happy (M=7.82, 7.81; SD=1.52, 1.54) and their lives as equally exciting (M=6.83, 6.82; SD=1.51, 1.76) with medians and modes of eight for happiness and seven for excitement. Women reported an average life stress rating of 6.49 (SD=1.90), while men reported an average stress rating of 6.38 (SD=1.95), which is not  5  I conducted T-Tests on each of these variables to ascertain whether the differences in the means between men and women were statistically significant at the p≤.05 level. Differences reported were statistically significant at this level and I discuss the differences for their substantive significance as well.  96     significantly different. Men and women reported the same frequency of engagement in exercise, and men rated themselves about as physically healthy (M=7.22, SD=1.84) as women (M=7.13, SD=1.83). The median for women was seven, while the median for men was eight. The mode for both groups was eight. The same was true of mental health as well. Men again showed approximately the same average rating of health (M=7.15, SD=1.91) as women (M=7.05, SD=1.80). The median was again seven for women and eight for men, with a mode of eight for both. Thus, men and women reported the same happiness levels, and approximately the same levels of stress and health on average. In the questions relating to satisfaction with various parts of life, men and women showed similar patterns; however, men were more satisfied with their personal lives (M=4.22, SD=0.98) than women (M=4.18, SD=1.07), while women were slightly more satisfied with their family lives (M=4.31, SD=1.02) than men (M=4.28, SD=1.06). The medians and modes were the same for both groups. Men were more satisfied with their work or careers (M=4.06, SD=1.06) than women (M=3.97, SD=1.05), while women were more satisfied with their educational attainments (M=4.25, SD=0.97) than men (M=4.21, SD=0.94). Consistent with the small differences in overall stress and health self-ratings, men rated themselves more highly on their time for activities and fitness level satisfaction (M=3.60, 3.52; SD=1.11, 1.18) than did women (M=3.40, 3.12; SD=1.18, 1.22). One interesting trend was that women expressed needing more everything to enhance their well-being than men did. This was especially notable for money, where women rated their average agreement as 3.84 (SD=1.11) while men rated their average agreement as 3.76 (SD=1.03). However, women also indicated needing a more supportive immediate and extended family (M=2.74, 2.69; SD=1.15, 1.06) more so than men (M=2.45, 2.47; SD=1.00, 0.97). This  97     was also particularly pronounced for childcare, where women ranked their agreement as 3.11 (SD=1.14) and men ranked their agreement as 2.82 (SD=1.14). Perhaps reflecting the lack of time and the stress that women felt more acutely than men, women thought more strongly than men that they needed all of these things to enhance their well-being. These trends are further supported in the data on satisfaction with the amount of time participants spend on various people and activities. Men are more satisfied with the amount of time that they spend with their spouse or partner (M=3.83, SD=1.11) than are women (M=3.53, SD=1.21), while women are more satisfied with the amount of time they spend with their children (M=3.97, SD=1.16) than are men (M=3.75, SD=1.21). Both are equally satisfied with the time they spend at work and in professional development, but men are more satisfied with their personal time (M=3.22, SD=1.16) than are women (M=2.98, SD=1.22). When it comes to the time the participants spend with friends, parents, and sports buddies, women’s responses are about equal to those of men. In terms of values, women tended to rate the importance they attached to each of the given values as higher than men, across all values.  Summary. These survey items present a picture of the 574 participants: desiring more time and money, strongly valuing their personal relationships, striving for balance in their lives, attaching importance to their time with family, focusing on their psychological and physical health, exhibiting concern for the environment and society in general, but overall negative and somewhat polarized on issues of religion. This group seems very cognizant of their well-being, particularly mental well-being, and attaches a great deal of importance to themselves as people and their social connections through family and marriage. In general, women seem to rate  98     themselves as more stressed and less healthy, and desire more help in various parts of their lives to enhance their well-being. This trend is consistent across the various types of questions; however, these differences were fairly small. Overall, the Paths on Life’s Way sample are happy and healthy, and generally satisfied with their lives, consistent with other North American findings (see, for example, Diener & Diener, 1996).  Data Reduction Factor analysis. Factor analysis is a method of conducting a “structural analysis” of a problem (Pett, Lackey, & Sullivan, 2003, p. 1). The research on happiness, well-being, and the broader concept of “subjective well-being” (SWB) indicate that within the broader construct of SWB there may be “several different but possibly interrelated subdimensions” (p. 1) within people’s “global assessments of life” and “recollections of past emotional experiences” across time and in different domains (Kim-Prieto et al., 2005, p. 262-263). The Paths on Life’s Way survey asked many questions about happiness and well-being both globally and specifically in various domains. The goal of the factor analysis is to analyze the structure of these variables to identify the interrelationships and then reduce this data into several groups of variables, called dimensions or factors, which summarize and describe these interrelationships in a concise manner (Pett, Lackey, & Sullivan, 2003). Within this analysis, a factor is “a linear combination or cluster of related observed variables that represents a specific underlying dimension of a construct, which is as distinct as possible from the other factors included in the solution” (p. 2-3). When the number of factors necessary to explain the interrelationships is not known, exploratory factor analysis (EFA) is  99     used. This is the approach taken in the current analysis to explore the underlying dimensions of the larger construct of SWB. The instrument was already created and the survey conducted; thus, the items used were pre-determined at the time of this study. The first stage, which was the selection of variables, is described above. Next, an initial number of factors are defined and the factors are rotated to improve the interpretation (Pett, Lackey, & Sullivan, 2003). Factors are kept or discarded from the analysis based on their eigenvalues and factor loadings, and items are kept or discarded from the analysis based on their factor loadings alone. Each factor has an eigenvalue which is a single value that “represents the amount of variance in all of the items that can be explained” by this factor (p. 91). Eigenvalues must be greater than zero and a factor is normally kept in an analysis only if the eigenvalue is equal or greater than 1.0 (Nagpal & Sell, 1985, p. 28). Factor loadings, on the other hand, “represent the correlation of each item with the given principle component” and are obtained by multiplying each of the weights in the eigenvector of the correlation matrix, which is the column of weights for each item in the matrix, with the square root of the principle component’s associated eigenvalue (Pett, Lackey, & Sullivan, 2003, p. 92). Different approaches are used for deciding whether to keep or discard items based on their factor loadings. The current analysis uses a cut-off of 0.30 for the factor loading, and further specifies that a minimum of four items with loadings of 0.30 or above must be present in order to keep any particular factor in the analysis (Nagpal & Sell, 1985). The sum of the squared factor loadings on one component is “the amount of variance in the items that can be explained by that particular principle component” (p. 92). It is optimal to explain as much variance as possible, preferably with fewer rather than more factors, for the sake of parsimony.  100     Selection of variables. The initial analysis used 53 of the 100+ variables related to health and well-being in the Paths on Life’s Way survey. 6 Participants’ ratings of their happiness, stress, and excitement in life on a ten-point Likert scale were used, as well as their rating of their mental and physical health on the same scale. All subquestions for their satisfaction with various parts of their lives on a five-point “extent of satisfaction” scale were included (15), as well as all subquestions for their satisfaction with the amount of time that they spent in various activities on the same scale (9). All subquestions about what the participants would need in order to “enhance their overall wellbeing” were included, but the scale was reversed (10). The original scale measured their extent of agreement from “strongly disagree” to “strongly agree” on a five-point scale, with six as “not applicable,” but this was inversed to show positive rather than negative interpretations of these variables. For all questions, those responding “not applicable” were coded as missing for the factor analysis. 7 Variables related to the participants’ “generation” and their children’s generation rather than them as individuals were excluded after initial analyses showed that they did not clearly load onto any of the factors. Finally, the extent of importance that they attach to various values (18) was included in initial analyses, but later eliminated on both statistical and theoretical grounds, as it taps into a different concept (values as opposed to well-being) and did not clearly load onto relevant factors. Stress was also later eliminated, as it did not clearly load onto a relevant factor in a substantively meaningful way. 8 6  Although all of the questions are related in some way to happiness or well-being, some, such as whether or not the participant had pets and whether their pet was important to their well-being, were tangential to the current study. These less central variables were left for future analyses. 7 “Not applicable” did not make conceptual sense to include as a value on an ordinal scale of level of agreement, unlike “no opinion,” which can be viewed as the midpoint on this scale. 8 Stress exhibited low to moderate loadings on four of the five final factors. I explore the relationships amongst stress and happiness and well-being in greater detail in the regression analyses. From the qualitative data, it also  101     Variables were eliminated if they did not show at least a 0.30 factor loading onto one of the factors. The variables remaining in the final analysis were the questions about how happy and exciting the participants’ lives were, mental and physical health, and all questions related to satisfaction with areas of life and time for various activities, excluding only their satisfaction with “the condition of our natural environment” and time spent in “volunteer participation.” These two variables did not load strongly onto any of the factors, and were also rated near “neutral” in participants’ extent of satisfaction, suggesting that – generally – these values may not be very important to this sample.  Results. The analyses were run using Principal Component Analysis. 9 The initial analysis with all variables found 15 factors with eigenvalues over 1.0, which explained 64% of the variance. In the next analysis I eliminated all variables without factor loadings of 0.30 or greater. The new analysis produced eight factors with eigenvalues over 1.0 and explained 62.5% of the variance. From there, I attempted to make theoretical sense of the factors from the variables included in each factor and the strength of their loadings. Doing so, I reduced the number of factors to five, reran the PCA and this resulted in a component matrix with five factors explaining 51% of the variance (see Table 9). 10  seems likely that participants interpret stress both positively and negatively (such as is done in psychology with the terms eustress and distress in Selye’s (1975) work), which makes interpretation of participants’ scores particularly complicated and difficult to interpret. 9 I ran the factor analyses, including the both the unrotated and rotated versions, in both SPSS and R. 10 I have included the matrix here with all factor loadings less than 0.30 suppressed for readability’s sake.  102     Table 9 Component matrix of factors related to happiness and well-being Components Factor 1:  Factor 2: Time with Family, Friends, and Self  Happiness  Overall Happiness and Life Satisfaction .769  Exciting Life  .613  Physically Healthy  .597  Mentally Healthy  .693  Satisfaction Personal Life  .709  -.326  Satisfaction Family Life  .607  -.334  Satisfaction Work/Career  .576  -.340  Satisfaction Where Live  .490  Satisfaction Educ. Attain.  .478  Satisfaction Health  .637  Satisfaction Way Things Going  .804  Satisfaction Way Life Unfold  .768  -.310  Satisfaction Amount of Time  .618  .426  Satisfaction Fitness Level  .497  Factor 3:  Factor 4:  Factor 5:  Social Support and Help  Tensions (FamilyHealth-Work Balance)  Satisfaction with Work, Education, and Finances  -.393  .305  .515  -.406  Need More Leisure Time*  .666  Need More Family Time*  .585  Need More Work Time*  .303 .312  Need More Money*  .313  Need More Support at Work*  .357  .376  Need More Support Imm. Family*  .408  .566  Need More Support Ext. Family*  .348  .648  Need More Help with Child Care*  .385  .568  Need More Help with Elder Care*  .337  .649  Need More Post-secondary Educ.*  .347  .395  Satisfaction Time with Spouse  .374  Satisfaction Time with Children  .325  Satisfaction Time for Work  .343  Satisfaction Personal Time  .408  Satisfaction Time for Prof. Devel.  .367  Satisfaction Time with Friends  .404  Satisfaction Time with Parents Satisfaction Time Sports Buddies  .507 .372  .400  .518 .372  .634 .447 .508 .381  .363  .420  -.476  Extraction Method: Principal Component Analysis. *These items were reversed to show "satisfaction."  103     As illustrated in Table 9, the five factors emerging from this analysis are as follows: 1) Overall Happiness and Life Satisfaction, 2) Time Spent with Family, Friends, and Self, 3) Social Support and Help, 4) Tensions (Family-Health-Work Balance), and 5) Satisfaction with Work, Education, and Finances. These all fit into the umbrella of “life satisfaction” or “subjective well-being” (see, for example, van Praag, 2003); however, each forms a unique group of related variables. The first fits well with the traditional view and measurement of happiness as a meta-construct of both happiness and well-being, or “subjective well-being” (SWB; see, for example, Kim-Prieto et al., 2005). This supports other findings of the close relationship between these types of variables (see, for example, Helliwell & Putnam, 2004). The other four categories are all areas highlighted in the literature as being instrumental in happiness. These also highlight areas that arose in the participants’ interviews as well. 11 The first factor, which comprises the largest group of variables, included participants’ general happiness with their life, rating of how exciting their lives were, rating of their mental health, rating of their physical health, satisfaction with their personal lives, satisfaction with their family lives, satisfaction with the way their lives had unfolded to date, and all of the other satisfaction questions asked (Andres, 2010b; see Appendix A). This maps onto participants’ general feelings and evaluations of their life as a whole. This is akin to Gilbert’s (2006) concept of “judgmental happiness,” an evaluative stance on one’s life overall.  11  The interview participants are completely separate from the survey participants and had never seen or completed the survey at the time of the interviews.  104     The second factor, which is centred on time, includes participants’ satisfaction with the amount of time they have to spend on activities they enjoy, participants’ satisfaction with time for leisure, family, children, friends, sports buddies, and personal time (or not needing more of these types of time to enhance their well-being, as these questions were reversed). Satisfaction with personal life, family life, work and career, and overall life satisfaction negatively loaded onto this factor, suggesting that there may be inherent tensions between time and well-being. Time is highly valued and sought after, as mentioned in almost all of the interviews as well, but does not translate into well-being. Time seems to be separate, and may not always correlate positively with well-being variables. Social support and help, the third factor, arose in some of the interviews. Needing social support and help grouped clearly into one discrete factor. This was mainly in relation to family: Needing a more supportive immediate and extended family, and more help with elder and child care, in order to enhance one’s overall well-being. However, support at work also loaded onto this factor, suggesting a link between family and work. The need to manage these two often opposing forces in their lives emerged in the interview data as well. This leads into the fourth factor, which was a tension factor. Balance, a key finding emerging from the qualitative data, was the fourth factor. Physical health, satisfaction with fitness level, and time with sports buddies loaded strongly but negatively onto this factor. Satisfaction with time spent with spouse, children, and work loaded strongly and positively onto this factor. Thus, it seems that this factor points to the tensions of attempting to lead a balanced life, with some areas suffering, such as health, if other areas become the focus of more effort. The concept of balance, which was central to the interview findings, is again central  105     in this analysis. The “gears of well-being” must run in sync to improve overall well-being, but the danger is always that as some areas improve others may become wounded in the process. The final factor comprises of variables related to work, career, and education. Higher education emerges strongly in this factor. It is composed of participants’ satisfaction with their educational attainments, the extent to which they feel they need more post-secondary education (reversed), and their satisfaction with time for professional development. Satisfaction with work and career also loaded onto this factor. This suggests that one discrete and important part of the participants’ well-being was with education and career. This again corroborates the interview data, where participants’ brought up work as a significant part of their well-being and judgments of their happiness with life overall. Although none of the participants’ brought up their educational attainments in speaking about happiness, it is an important stepping-stone to work and careers and has been instrumental in shaping participants’ work trajectories. These five factors remain in similar groupings in a rotated PCA using Varimax rotation. The rotation converged in eight iterations and the rescaled components in this solution exhibited factor loadings very similar to those in the unrotated component matrix (see Appendix B for the unrotated and rotated component matrix and correlation matrix). The rotated solution exhibited similar factor loadings as the unrotated solution as well (see Figure 4). However, one key difference to note is that the fourth factor emerged much more strongly as a “health” grouping in this rotated solution. The factors are much more clearly differentiated in this analysis, both statistically and substantively as well.  106     Figure 4. Solution using Varimax rotation. The benefit of this solution is that it gives information about “which items correlated most strongly with a given factor” and provides a simple structure, without any overlap among the explained variances of the factors (Pett, Lackey, & Sullivan, 2003, p. 143). However, I chose to mainly use and interpret the results from the unrotated solution because Varimax rotations tend to “split up the variances of the major factors among the less important factors, thus reducing the possibility of identifying an overall general factor” and I was wary of overinflating the importance of the lesser factors (Pett, Lackey, & Sullivan, 2003, p. 143). These items are all  107     interrelated to some extent, and many researchers claim that there is one general factor underlying all, so I chose the more conservative analysis.  Summary. The results of the factor analysis mirror those of the interviews in several ways. Firstly, it is useful to return to the definitions derived from the qualitative analysis, in which I defined happiness as “a positive feeling towards and evaluation of one’s self and life at a particular point or period in time, which includes an optimal balance between achievement and acceptance,” and well-being as “a positive and healthy overall state of being in many areas of life at a particular point or period in time, including one’s physical state, mental state, social state, work state, and others, in which all of these domains interrelate and impact one another substantially.” I indicated that both of these are influenced by people’s unique values, goals, and life circumstances, although some commonalities emerge as well. These differences emerge strongly in the factor analysis: Factor 1 can be thought of as happiness by this definition, and well-being emerges in Factors 3 and 5, social support and work and educational attainments, and also in Factor 2, time with family, friends, and self. Factor 4 is also a part of this, but points to the tensions and balance involved in achieving well-being in various parts of life concurrently (as well as the importance of health, as shown in the rotated solution). These five factors can also be thought of as five key capabilities using Sen’s (1993) framework. The notions of balance and gears working in synchrony are useful metaphors when looking at these five factors and how they might relate to each other as well. The survey participants, just like the interview participants, engage in an ongoing act of balancing acceptance and achievement in order to achieve an overall sense of happiness. This balance  108     spans many areas of life, including family and friends, work and education, and physical health, and arises from a sense of well-being that consists of various domains of life turning in synchrony, much like a simple machine of interlocking gears. The overwhelming finding here is the tensions that arise between different aspects of well-being that must be balanced or shifted in order to allow for all aspects of life to exist in a harmonious relationship that does not stifle any at the expense of the others.  Happiness and Education Regression analysis. Regression arises from an inquiry about the relationship between two or more variables and is, at its most basic, a method of fitting a line to a scatter of points (Lewis-Beck, 1980, p. 9). Regression is often used to develop causal models, which “specify the effects of one or more independent variables on one or more dependent variables or outcome variables” (Jaccard & Turrisi, 2003, p. 1). It is also “one of the most flexible and widely used techniques of quantitative analysis” (Hardy, 1993, p. 1). Relationships in the social sciences, unlike the physical sciences, are almost always inexact and so linear relationships include the variables under investigation and an error term as well (Lewis-Beck, 1980). This means that not all points will fall on the line, and several different lines are possible. Because of this, the method for choosing amongst these lines “becomes one of selecting the straight line which minimizes the sum of the squares of the errors (SSE)” or the least squares principle (Lewis-Beck, 1980, p. 14). The present analysis will use both multiple and logistic regression to examine the relationship between educational aspirations, expectations, and attainment and other variables suggested by the literature to be important, and happiness and other well-being variables. Thus,  109     happiness will be a “linear additive function of the independent variables… and the stochastic error term” (Hardy, 1993, p. 4). This allows the researcher to find “conditional means or expected values of Y i for fixed values of X ki ” (p. 4). In the context of this analysis, happiness can be predicted from varying levels of educational attainments, aspirations, expectations, presence or absence of marriage, marital dissolution, presence or absence of children, rates of exercise, and other variables. In this, I assume that the independent variables are having an effect on happiness, but recognize that, substantively, the relationship moves in both directions. These models are vastly simplified in comparison to the realities of the social world. As John Fox (2008) points out in his tome on regression analysis, Applied Regression Analysis and Generalized Linear Models, “From the improbable moment of birth, each of our lives is governed by chance and contingency. The statistical models typically used to analyze social data… are, in contrast, ludicrously simple” (p. 1). Despite the capriciousness and unpredictability of human lives, however, he points to the value in attempting to understand some of the social structures and variables that may impact them, with the understanding that they do not determine them. My own theoretical framing at the beginning of this thesis points to the same underlying point. I also defend the value in attempting to model relationships in the social sciences, even if these models are vastly simplified: As a quote by George Box asserts, “All models are wrong but some are useful” (Box, 1979, p. 202). I approach the following analyses and models with the same humbleness.  110     Inclusion of variables. The regression analyses were run first together and then separately for men and women. This is based on other researchers’ (inconclusive) findings of the influence of gender upon happiness (Helliwell & Putnam, 2004). This relationship is inconsistent and suggests a complicated relationship, although the impact of gender on happiness is not always significant (Helliwell & Putnam, 2004). Some researchers have found that the happiness levels of women are increasing less relative to men’s and may even be decreasing in some situations over time, despite huge gains in post-secondary attainment and earnings (Stevenson & Wolfers, 2007; Blanchflower & Oswald, 2004). This “paradox of women’s declining relative well-being” is an interesting puzzle to further investigate (Stevenson & Wolfers, 2007, p. 1). Thus, the present analysis is split by gender, to try to unearth potential future areas of investigation in this unclear relationship. One variable central to this analysis was the participants’ highest post-secondary educational attainment in 2010. Internationally, education has been found to be “a virtually universal correlate” of happiness and well-being (Helliwell & Putnam, 2004, p. 1436), even when other variables, such as income, are controlled for in the analysis (Blanchflower & Oswald, 2004). In the current study, this variable was operationalized as the highest of all post-secondary educational degrees, licenses, diplomas, and other certifications completed between 1988 and 2010. 12 The hierarchy of educational attainment was defined from lowest being a non-participant or non-completer to highest being a PhD or doctorate. Highest educational attainment was defined in the following order and categories: Non-completer, apprenticeship, certificate, diploma, associate’s degree, bachelor’s degree, professional degree or certification, masters degree, and PhD or doctorate. Other variables, such as income, were included as controls based  12  Data from 1988 were not included, as participants did not enter into the post-secondary system until September 1988 and very few had completed any type of certification before the second survey wave in 1989.  111     on a literature review of influential variables on happiness and the variables available in the survey data. Income in particular has been hypothesized by some as a moderating variable in the relationship between education and happiness, so it was important to control for this. Being married and healthy also show consistent positive effects on happiness levels (Blanchflower & Oswald, 2004; Helliwell & Putnam, 2004; Seligman, 2011). This evidence warrants including these variables in any analysis of the relationship between happiness and education. In most of the analyses, happiness is the dependent variable. Happiness is operationalized by the participants’ response to the survey question, “On a scale of 1 to 10, in general how happy would you say you are with your life? (circle one)” (Andres, 2010b, p.23, emphasis in original; see Appendix A). This Likert-style variable is first considered as a continuous, linear variable, consistent with other research (see, for example, van Praag et al., 2003), but in later analyses this approach is problematized and a logistic regression is conducted using a binary measure of happiness. Other dependent variables, such as mental and physical health and satisfaction with life as a whole, are also used to gain a fuller picture of the influence of the independent variables on participants’ overall well-being.  Happiness and relevant variables from the literature. Regression analysis 1. The first regression analysis uses an ordinary least squares (OLS) regression to regress happiness onto income, exercise, marital status, marital change, family status (presence or absence of children), level of stress, mental health, and physical health, controlling for sex of the participant. These are variables known to have an impact on happiness in the literature (see, for example, Diener et al., 1999; van Praag et al., 2003; Gilbert, 2006; Kahneman, 2011). The variable  112     measuring happiness is treated as continuous despite the fact that it is an ordinal variable on a Likert scale coded from one to ten. Other researchers have used the same approach in recent studies (see, for example, van Praag et al., 2003). Happiness is operationalized here by the participants’ response to the survey question, “On a scale of 1 to 10, in general how happy would you say you are with your life? (circle one)” (Andres, 2010b, p.23, emphasis in original; see Appendix A). The independent variables were as follows: The “income” variable is the total household income of the participant and their spouse/partner (if applicable) from all sources, before taxes or deductions, in 2009. It is recoded into thousands of Canadian dollars. The “marital status” variable is recoded from six options into a binary variable of married or not married, 13 as is the “children” variable (see Appendix A for the original questions and response categories). The “exercise” variable is operationalized as exercise frequency, from the question, “How often do you participate in sports or engage in regular exercise?” It includes five responses categories, from “Not at all” to “More than five times a week” in ascending order. Level of stress, mental health, and physical health are all Likert-scale variables, coded from one to ten, with one being the lowest on all and ten being the highest. Each of these variables can be tracked over time, from 1988 to the present, but only the 2010 data were used in the present study. The regression equation for this model is Y happy = β 0 + β 1 x income + β 2 x exercise + β 3 x marital status + β 4 x marital change + β 5 x children + β 6 x stress + β 7 x mental health + β 8 x physical health + β 9 x gender +e  13  Those who were married and those in common-law relationships were coded as “married” for the purpose of this analysis, while those who described themselves as single, divorced, separated, and widowed were coded as “not married.” The reason for this was to focus on the social rather than beaurocratic aspects of marriage.  113     The participants’ levels of mental and physical health are associated with general increases in happiness on the Likert scale variable measuring overall happiness. A one-point increase in participants’ mental health on a Likert-scale measure is associated with an 0.40 (p<.01) increase in happiness on the same type of Likert-scale measure. A one-point increase in participants’ physical health is associated with an 0.09 (p=.01) increase in happiness on the same type of Likert-scale measure. A thousand-dollar increase in yearly household income is associated with an 0.002 (p=.01) increase in happiness, which is statistically if not practically significant. Being married is associated with a 0.73 (p<.01) increase in happiness on this scale. These are the only significant associations; however, some interesting findings here are that exercise is not significant when physical health is controlled for, although it is when used as a proxy for physical health (see the final regression analyses on the “conventionality” of happiness), that marital change and stress have slight negative impacts, but these are not at all significant, and that having children and gender did not emerge as important factors in this analysis. These results are somewhat surprising: Although gender was expected to exert a complicated effect on happiness, children do sometimes exert a positive effect on happiness (see the final regression analyses on the “conventionality” of happiness). Thus, the factors that emerge as important for predicting happiness within the Paths on Life’s Way sample are mental health, physical health, income, and marriage. Increases in health and income are associated with general increases in happiness on the ten-point Likert scale, and being married results in an increase in happiness as compared to not being married. These results align with previous findings (Diener et al., 1999; Helliwell & Putnam, 2004; Kahneman, 2011).  114     Table 10 The effect of income, exercise, marital status, marital change, family status, gender, level of stress, mental health, and physical health on happiness 14  Predictors  Βs  Intercept  3.64 (0.00)***  Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) Children (No=0) Gender (Male=0) Level of Stress (10=Very Stressful) Mental Health (10=Very Healthy) Physical Health (10=Very Healthy)  − −  −  0.00 (0.01)** 0.01 (0.87) 0.73 (0.00)*** 0.15 (0.22) 0.16 (0.24) 0.07 (0.49) 0.03 (0.26) 0.40 (0.00)*** 0.09 (0.01)**  R-square RSS  0.43 1,200.18  d.f.  520 (Paths on Life's Way, 2010)  The overall model is significant (F=44.0, p<0.01) with an R2 of 0.43, which is a large effect size according to Cohen’s (1988) criteria. This model explains 43% of the variance in the happiness scores.  14  Note: p-values are represented by asterixes. Three asterixes (***) represents p<.01, two asterixes (**) represents p=.01, one asterix (*) represents p≤.05, and a centred dot (·) represents p≤.10. This is the case for all tables, unless otherwise noted.  115     Regression analysis 2: gender differences. The second regression analysis again uses an ordinary least squares (OLS) regression to regress happiness onto income, exercise, marital status, marital change, family status (presence or absence of children), level of stress, mental health, and physical health, but splits the analysis by the gender of the participant. As in the first analysis, happiness is operationalized here by the participants’ response to the survey question, “On a scale of 1 to 10, in general how happy would you say you are with your life? (circle one)” (Andres, 2010b, p.23, emphasis in original; see Appendix A). The same independent variables were included in the second analysis, except the gender variable. The “income” variable is the total household income of the participant and their spouse/partner (if applicable) from all sources, before taxes or deductions, in 2009. It is recoded into thousands of Canadian dollars. The “marital status” variable is recoded from six options into a binary variable of married or not married, as is the “children” variable (see Appendix A for the original questions and response categories). The “exercise” variable is operationalized as exercise frequency, from the question, “How often do you participate in sports or engage in regular exercise?” It includes five responses categories, from “Not at all” to “More than five times a week” in ascending order. Level of stress, mental health, and physical health are all Likert-scale variables, coded from one to ten, with one being the lowest on all and ten being the highest. The regression equations for these models are Y happy male = β 0 + β 1 x income + β 2 x exercise + β 3 x marital status + β 4 x marital change + β 5 x children + β 6 x stress + β 7 x mental health + β 8 x physical health + e  116     Y happy female = β 0 + β 1 x income + β 2 x exercise + β 3 x marital status + β 4 x marital change + β 5 x children + β 6 x stress + β 7 x mental health + β 8 x physical health + e  The men’s levels of mental and physical health are associated with general increases in happiness on the Likert scale variable measuring overall happiness, although mental health is more predictive than physical health (see Table 11). A one-point increase in men’s mental health on a Likert-scale measure is associated with an 0.34 (p<.01) increase in happiness. A one-point increase in men’s physical health is associated with an 0.09 (p<.05) increase in happiness. A thousand-dollar increase in yearly household income is associated with an 0.002 (p=.10) increase in happiness, which is not significant in this model. Being married is associated with a 1.04 (p<.01) increase in happiness on this scale, which is highly significant and larger than in the model with both men and women. Otherwise stated, men who were married reported, on average, 1.04 higher happiness scores than those who were not married, holding all of the other variables in the analysis constant (health, children, income, and all other variables). The women’s levels of mental and physical health are associated with general increases in happiness on the Likert-scale variable measuring overall happiness as well (see Table 11). Again, this is more significant for mental health. A one-point increase in the women’s mental health on a Likert-scale measure is associated with an 0.44 (p<.01) increase in happiness. This is larger than the increase shown by the men in this sample. A one-point increase in the women’s physical health is associated with an 0.10 (p<.04) increase in happiness on the same type of Likert-scale measure. A thousand-dollar increase in yearly household income is associated with an 0.002 (p<.10) increase in happiness, which, like with the men, is not statistically significant. Being married is associated with a 0.54 (p=.01) increase in happiness, which is a smaller effect  117     than that shown by men. Some non-significant effects that are substantively interesting are that children seem more important for women’s happiness than men’s, marital change has a negative but non-significant effect, and stress does not seem to negatively impact the participants’ happiness scores. Hence, the factors that emerge as important for predicting happiness within the Paths on Life’s Way sample for men and women exhibit some differences, the most striking of which is that men seem to gain more happiness from marriage than do women (see Table 11). Although being married shows a significant positive affect both sexes, the men have a larger happiness gain than do the women. In contrast, mental health seems to be more important for women’s happiness than men’s. Income has a modest affect on the happiness of both men and women, while stress does not seem to affect the happiness of women at all (although it may exert a slight negative affect on men’s happiness). 15  15  As noted earlier, this may be due to the way the “stress” question was asked and potential different interpretations of the question: i.e. eustress versus distress.  118     Table 11 The effect of income, exercise, marital status, marital change, family status, level of stress, mental health, and physical health on happiness by gender Predictors Intercept Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) Children (No=0) Level of Stress (10=Very Stressful) Mental Health (10=Very Healthy) Physical Health (10=Very Healthy)  − −  Men  Women  Bs  Bs  4.03 (0.00)*** 0.00 (0.10)· 0.01 (0.88) 1.04 (0.00)*** 0.15 (0.48) 0.07 (0.78) 0.07 (0.13) 0.34 (0.00)*** 0.09 (0.15)  3.37 (0.00)*** 0.00 (0.09)· 0.04 (0.60) 0.54 (0.01)** 0.21 (0.18) 0.21 (0.21) 0.00 (1.00) 0.44 (0.00)*** 0.10 (0.04)*  − −  R-square RSS  0.40 477.26  0.44 722.50  d.f.  206  313 (Paths on Life's Way, 2010)  The overall model is significant for both men (F=18.17, p<0.01) and women (F=31.91, p<0.01) with an R2 of 0.40 for men and with an R2 of 0.44 for women, which are both large effect size according to Cohen’s (1988) criteria. Compared to the combined model, these models predict equally well for women, but not quite as well for men, probably due to the fact that the number of men is lower than women in this sample. These demographic variable models are interesting; however, education is the main variable I am interested in, so I add variables related to education in the next set of regression analyses.  119     Happiness and educational variables. Regression analysis 3: happiness and post-secondary educational attainment. The third regression analysis uses an ordinary least squares (OLS) regression to regress happiness onto income, exercise, marital status, marital change, family status (presence or absence of children), level of stress, mental health, and physical health, but includes a postsecondary educational attainment variable as well, again splitting the analysis by the gender of the participant. As in the first set of analyses, happiness is operationalized here by the participants’ response to the survey question, “On a scale of 1 to 10, in general how happy would you say you are with your life? (circle one)” (Andres, 2010b, p.23, emphasis in original; see Appendix A). The same independent variables were included in this set of analyses, except the “highest educational attainment in 2010” variable, which was operationalized as the highest of all postsecondary educational degrees, licenses, diplomas, and other certifications completed between 1988 and 2010. The hierarchy of educational attainment was defined from lowest being a nonparticipant or non-completer to highest being a PhD or doctorate. Highest educational attainment was defined in the following order and categories: Non-completer, apprenticeship, certificate, diploma, associate’s degree, bachelor’s degree, professional degree or certification, masters degree, and PhD or doctorate. The “income” variable is the total household income of the participant and their spouse/partner (if applicable) from all sources, before taxes or deductions, in 2009. It is recoded into thousands of Canadian dollars. The “marital status” variable is a binary variable of married or not married, as is the “children” variable (see Appendix A for the original questions and response categories). The “exercise” variable is operationalized as  120     exercise frequency. Level of stress, mental health, and physical health are all Likert-scale variables, coded from one to ten, with one being the lowest on all and ten being the highest. The regression equations for these models are Y happy male = β 0 + β 1 x income + β 2 x exercise + β 3 x marital status + β 4 x marital change + β 5 x children + β 6 x stress + β 7 x mental health + β 8 x physical health + β 9 x highest educ + e  Y happy female = β 0 + β 1 x income + β 2 x exercise + β 3 x marital status + β 4 x marital change + β 5 x children + β 6 x stress + β 7 x mental health + β 8 x physical health + β 9 x highest educ + e  Men’s levels of mental health in this model are associated with general increases in happiness on the Likert-scale variable measuring overall happiness; however, physical health in this model is not predictive of happiness (see Table 12). A one-point increase in men’s mental health on a Likert-scale measure is associated with an 0.33 (p<.01) increase in happiness again. A thousanddollar increase in yearly household income is associated with an 0.002 (p<.10) increase in happiness, which is only significant at the α=0.10 level in this model. Being married, marital change, and having children were not significant in this model. Highest post-secondary educational attainment was not at all significant in predicting men’s happiness in this model. Both women’s levels of mental health and physical health were associated with general increases in happiness on the Likert scale variable measuring overall happiness in this model (see Table 12). This is more significant for mental health, but physical health shows a strong relationship with happiness for women in this model as well. A one-point increase in women’s mental health on a Likert-scale measure is associated with an 0.43 (p<.01) increase in happiness. In contrast to the men, a one-point increase in women’s physical health is associated with an 0.11  121     (p<.03) increase in happiness on the same type of Likert-scale measure. A thousand-dollar increase in yearly household income is associated with an 0.002 (p<.10) increase in happiness, which, like with the men, is only significant at the α=0.10 level in this model. Being married is significant for women, and associated with a 0.47 (p<.04) increase in happiness, which again differs from the relationship in the model for the men. Highest post-secondary educational attainment is again non-significant for the women. Thus, similar factors emerge as important for predicting happiness within the Paths on Life’s Way sample for men and women in this model, despite adding in the educational variable. When taking income and stress into account, educational attainments do not seem to exert an effect on happiness. Rather, mental and physical health, as well as income and marriage are the main predictors of happiness. This follows from other studies, which have found health to be the single greatest predictor of happiness, and social capital in the form of family and friends to be very influential as well (Helliwell & Putnam, 2004).  122     Table 12 The effect of demographic factors and educational factors on happiness by gender Predictors  Model 1  Model 2  Men Intercept Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) Children (No=0) Level of Stress (10=Very Stressful) Mental Health (10=Very Healthy) Physical Health (10=Very Healthy) Highest Educ. Attain. 2010 (20=PhD)  − −  Women  Men  Women  Bs  Bs  Bs  Bs  4.03 (0.00)***  3.37 (0.00)***  3.97 (0.00)***  3.12 (0.00)***  0.00 (0.10)·  0.00 (0.09)·  0.00 (0.08)·  0.00 (0.09)·  0.04 (0.60) 0.54 (0.01)** 0.21 (0.18) 0.21 (0.21) 0.00 (1.00) 0.44 (0.00)*** 0.10 (0.04)*  0.11 (0.20) 0.59 (0.12) 0.10 (0.66) 0.35 (0.20) 0.04 (0.38) 0.33 (0.00)*** 0.05 (0.39)  0.01 (0.88) 1.04 (0.00)*** 0.15 (0.48) 0.07 (0.78) 0.07 (0.13) 0.34 (0.00)*** 0.09 (0.15)  − −  − −  − − −  0.04 (0.59) 0.47 (0.03)* 0.23 (0.16) 0.24 (0.19) 0.00 (0.10) 0.43 (0.00)*** 0.11 (0.03)*  0.01 (0.76)  0.02 (0.5)  R-square RSS  0.40 477.26  0.44 722.50  0.36 369.85  0.42 625.79  d.f.  206  313  179  280  (Paths on Life's Way, 2010)  123     The overall model including educational attainment is still significant for both men (F=12.50, p<0.01) and women (F=23.60, p<0.01), but less than the previous model not including education. As well, this model only has an R2 of 0.36 for men and an R2 of 0.42 for women, which, while they are both still large effect size according to Cohen’s (1988) criteria, are lower than in the previous model. This is true for both men and women. The non-significance of higher education is a surprising and intriguing finding based on previous research. In order to ensure that this was not simply due to the fact that post-secondary educational attainments were coded in such specific detail, I reran the analysis using a modified variable for education, which contained only three ordinal categories: (1) No post-secondary education, (2) Non-university credentials, and (3) University degrees. The results were generally the same as the previous analysis, with the exception of men’s education. Men’s post-secondary educational attainments showed a positive effect on happiness, with each unit increase in education associated with an 0.20 (p<.10) increase in happiness. There was no relationship between these two variables for women (see Table 13).  124     Table 13 The effect of demographic factors and educational factors on happiness by gender Predictors  Model 1  Model 2  Men Intercept Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) − Children (No=0) Level of Stress (10=Very Stressful) − Mental Health (10=Very Healthy) Physical Health (10=Very Healthy) Highest Educ. Attain. 2010 (3=University)  Women  Men  Women  Bs  Bs  Bs  Bs  4.03 (0.00)***  3.37 (0.00)***  3.66 (0.00)***  3.29 (0.00)***  0.00 (0.10)·  0.00 (0.09)·  0.00 (0.16)  0.00 (0.11)  0.04 (0.60) 0.54 (0.01)** 0.21 (0.18) 0.21 (0.21) 0.00 (1.00) 0.44 (0.00)*** 0.10 (0.04)*  0.03 (0.73) 0.98 (0.00)*** 0.18 (0.40) 0.12 (0.62) 0.08 (0.09)· 0.33 (0.00)*** 0.09 (0.14) 0.20 (0.09)·  0.01 (0.88) 1.04 (0.00)*** 0.15 (0.48) 0.07 (0.78) 0.07 (0.13) 0.34 (0.00)*** 0.09 (0.15)  − −  − −  − − −  0.04 (0.60) 0.55 (0.01)** 0.21 (0.18) 0.22 (0.20) 0.00 (0.99) 0.44 (0.00)*** 0.09 (0.04)* 0.04 (0.71)  R-square RSS  0.40 477.26  0.44 722.50  0.41 477.26  0.44 722.5  d.f.  206  313  206  313  (Paths on Life's Way, 2010)  125     The overall model is significant for both men (F=16.62, p<0.01) and women (F=28.30, p<0.01) with an R2 of 0.41 for men and with an R2 of 0.44 for women, which are both large effect size according to Cohen’s (1988) criteria. This is a moderate improvement on both the base model and the more detailed educational attainment model. However, no strong, clear effect emerges. In order to more fully look at this relationship I add variables related to educational aspirations and expectations in the next set of regression analyses.  Regression analysis 4: happiness and post-secondary educational aspirations. The next set of regression analyses again includes the “highest educational attainment in 2010” variable, which was operationalized as the highest of all post-secondary educational degrees, licenses, diplomas, and other certifications completed between 1988 and 2010, but also includes the participants’ highest post-secondary educational attainment aspirations and expectations. These were measured by their responses to the questions, “In your lifetime, what is the highest level of education that you WANT to achieve? (check one)” and “Given the realities of today’s educational system and work world, what is the highest level of education that you EXPECT to achieve? (check one)” (Andres, 2010b, p. 15, emphasis in original; see Appendix A). These were measured on the scale “graduate degree,” “professional degree,” “bachelor’s degree,” “college/technical certificate or diploma,” “apprenticeship,” and “secondary school diploma,” from the highest to the lowest option (6 = “graduate degree” and 1 = “secondary school diploma”). The rest of the independent variables from the previous analyses were included as well. Again, happiness is the outcome variable and operationalized here by the participants’ response to the question, “In general how happy would you say you are with your life?”  126     The regression equations for these models are Y happy male = β 0 + β 1 x income + β 2 x exercise + β 3 x marital status + β 4 x marital change + β 5 x children + β 6 x stress + β 7 x mental health + β 8 x physical health + β 9 x highest educ 2010 + β 10 x highest educ desired 1989 + β 11 x highest educ expected 1989 + e  Y happy female = β 0 + β 1 x income + β 2 x exercise + β 3 x marital status + β 4 x marital change + β 5 x children + β 6 x stress + β 7 x mental health + β 8 x physical health + β 9 x highest educ 2010 + β 10 x highest educ desired 1989 + β 11 x highest educ expected 1989 + e  Similar to the last model, men’s mental, but not physical health, is associated with increases in happiness (see Table 14). Income is significant at the α=0.05 level. Highest post-secondary educational attainment was again not at all significant in predicting men’s happiness in this model; however, post-secondary educational aspirations (or “desired” educational attainments) were predictive of happiness scores for men at the α=0.10 level. Women’s mental health and physical health were again both significant, as was income at the α=0.10 level. Being married was highly significant for women, with those who were married reporting 0.58 units higher happiness than those who were not married (holding all other variables constant). Contrary to the findings for the men, highest post-secondary educational attainment, highest post-secondary desired educational attainment, and highest post-secondary expected educational attainments were all non-significant for the women.  127     Table 14 The effect of demographic factors and educational factors (2010 and 1989) on happiness by gender Predictors  Model 1  Model 2  Men  Women  Men  Women  Bs  Bs  Bs  Bs  Intercept  4.03 (0.00)***  3.37 (0.00)***  4.04 (0.00)***  4.09 (0.00)***  Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) Children (No=0) Level of Stress (10=Very Stressful) Mental Health (10=Very Healthy) Physical Health (10=Very Healthy) Highest Educ. Attain. 2010 (20=PhD) Highest Education Desired (1989) Highest Education Expected (1989)  0.00 (0.10)· 0.01 (0.88) 1.04 (0.00)*** 0.15 (0.48) 0.07 (0.78) 0.07 (0.13) 0.34 (0.00)*** 0.09 (0.15)  0.00 (0.09)· 0.04 (0.60) 0.54 (0.01)** 0.21 (0.18) 0.21 (0.21) 0.00 (1.00) 0.44 (0.00)*** 0.10 (0.04)*  0.00 (0.02)* 0.09 (0.33) 0.46 (0.21) 0.11 (0.62) 0.35 (0.23) 0.03 (0.53) 0.37 (0.00)*** 0.02 (0.74) 0.01 (0.92) 0.14 (0.10)· 0.12 (0.24)  0.00 (0.08)· 0.12 (0.11) 0.58 (0.01)** 0.25 (0.14) 0.15 (0.44) 0.02 (0.64) 0.39 (0.00)*** 0.11 (0.05)* 0.01 (0.77) 0.01 (0.85) 0.04 (0.57)  − −  − −  − −  − −  − − −  −  R-square RSS  0.40 477.26  0.44 722.50  0.39 307.53  0.39 486.96  d.f.  206  313  152  238  (Paths on Life's Way, 2010)  128     The overall model including educational attainment is still significant for both men (F=9.98, p<0.01) and women (F=14.77, p<0.01), but even less than the previous model including only completed education. However, this model decreased the variance explained to an R2 of 0.39 for both men and women, which is smaller than the models without any educational variables both men and women. In a final attempt to tease out a potential relationship between happiness and higher education in this sample, I create a difference score between desired and expected education (expected – desired = difference score). This investigates whether the distance between people’s goals and capabilities, to refer back to the qualitative analysis and Sen’s (1985, 1993, 2009) approach to well-being, impacts happiness.  The regression equations for these models are Y happy male = β 0 + β 1 x income + β 2 x exercise + β 3 x marital status + β 4 x marital change + β 5 x children + β 6 x stress + β 7 x mental health + β 8 x physical health + β 9 x highest educ 2010 + β 10 x expected-desired difference score 1989 + e  Y happy female = β 0 + β 1 x income + β 2 x exercise + β 3 x marital status + β 4 x marital change + β 5 x children + β 6 x stress + β 7 x mental health + β 8 x physical health + β 9 x highest educ 2010 + β 10 x expected-desired difference score 1989 + e  Looking at Table 15, one can see that the difference score between highest post-secondary desired educational attainment and highest post-secondary expected educational attainment is again only significant for men, and not for women. This relationship is also negative, which  129     indicates that having higher educational “wants” or “desires” than higher educational “expectations” is actually beneficial for happiness. This points to the importance of goal-setting in relation to happiness, as emphasized by Kahneman (2011) and Seligman (2011). This greater impact of education, both actual and desired, on men’s happiness may also signify a difference in values (or perhaps societal expectations) between men and women, or may be linked to the men’s lower participation in post-secondary education and, therefore, greater rewards now associated with gaining educational credentials as compared to those who do not participate. Women may be able to achieve a life and lifestyle that promotes happiness without higher education, while this may be more difficult for men. This falls in line with a more “traditional” family and gender roles view; however, it seems to play out in the present analysis.  130     Table 15 The effect of demographic factors and educational factors (2010 and 1989) on happiness by gender Predictors  Model 1  Model 2  Men  Women  Men  Women  Bs  Bs  Bs  Bs  Intercept  4.03 (0.00)***  3.37 (0.00)***  4.00 (0.00)***  3.99 (0.00)***  Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) Children (No=0) Level of Stress (10=Very Stressful) Mental Health (10=Very Healthy) Physical Health (10=Very Healthy) Highest Educ. Attain. 2010 (20=PhD) Diff. between Educ. Expected-Desired (1989)  0.00 (0.10)· 0.01 (0.88) 1.04 (0.00)*** 0.15 (0.48) 0.07 (0.78) 0.07 (0.13) 0.34 (0.00)*** 0.09 (0.15)  0.00 (0.09)· 0.04 (0.60) 0.54 (0.01)** 0.21 (0.18) 0.21 (0.21) 0.00 (1.00) 0.44 (0.00)*** 0.10 (0.04)*  0.00 (0.02)* 0.09 (0.33) 0.46 (0.21) 0.11 (0.62) 0.35 (0.23) 0.03 (0.53) 0.37 (0.00)*** 0.02 (0.75) 0.01 (0.88) 0.13 (0.08)·  0.00 (0.09)· 0.12 (0.11) 0.58 (0.01)** 0.25 (0.14) 0.16 (0.43) 0.02 (0.62) 0.39 (0.00)*** 0.11 (0.05)* 0.01 (0.82) 0.02 (0.63)  − −  − −  − −  − −  − − −  R-square RSS  0.40 477.26  0.44 722.50  0.40 307.53  0.39 486.96  d.f.  206  313  152  238  (Paths on Life's Way, 2010)  131     The overall model is significant for both men (F=11.06, p<0.01) and women (F=16.30, p<0.01), but fails to predict happiness as well as the model without educational variables. The following two models are both significant as well (p<0.01) and show the effects of educational aspirations and expectations from 1989 on 2010 happiness scores, excluding post-secondary educational attainment in 2010 from the analysis (see Table 16).  132     Table 16 The effect of demographic factors and educational factors (1989) on happiness by gender Predictors  Model 1  Model 2  Men  Women  Men  Women  Bs  Bs  Bs  Bs  Intercept  4.03 (0.00)***  3.37 (0.00)***  3.94 (0.00)***  4.12 (0.00)***  Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) Children (No=0) Level of Stress (10=Very Stressful) Mental Health (10=Very Healthy) Physical Health (10=Very Healthy) Highest Education Desired (1989) Highest Education Expected (1989)  0.00 (0.10)· 0.01 (0.88) 1.04 (0.00)*** 0.15 (0.48) 0.07 (0.78) 0.07 (0.13) 0.34 (0.00)*** 0.09 (0.15)  0.00 (0.09)· 0.04 (0.60) 0.54 (0.01)** 0.21 (0.18) 0.21 (0.21) 0.00 (1.00) 0.44 (0.00)*** 0.10 (0.04)*  0.00 (0.04)* 0.03 (0.69) 0.77 (0.01)** 0.10 (0.65) 0.09 (0.73) 0.05 (0.25) 0.37 (0.00)*** 0.04 (0.50) 0.18 (0.02)* 0.17 (0.05)*  0.00 (0.09)· 0.10 (0.17) 0.65 (0.00)*** 0.22 (0.17) 0.14 (0.44) 0.02 (0.59) 0.41 (0.00)*** 0.10 (0.05)* 0.02 (0.75) 0.06 (0.40)  − −  − −  − −  −  − − −  −  R-square F-value RSS  0.40 18.17*** 477.26  0.44 31.91*** 722.50  0.40 12.43*** 364.67  0.42 19.84*** 570.63  d.f.  206  313  171  264  (Paths on Life's Way, 2010)  133     One can see here that both men’s educational aspirations and expectations were significant when their actual attainments were excluded. The same was true of the difference score between these as well, which is presented in the next table (see Table 17).  134     Table 17 The effect of demographic factors and educational factors (1989) on happiness by gender Predictors  Model 1  Model 2  Men  Women  Men  Women  Bs  Bs  Bs  Bs  Intercept  4.03 (0.00)***  3.37 (0.00)***  3.92 (0.00)***  3.95 (0.00)***  Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) Children (No=0) Level of Stress (10=Very Stressful) Mental Health (10=Very Healthy) Physical Health (10=Very Healthy) Diff. between Educ. Expected-Desired (1989)  0.00 (0.10)· 0.01 (0.88) 1.04 (0.00)*** 0.15 (0.48) 0.07 (0.78) 0.07 (0.13) 0.34 (0.00)*** 0.09 (0.15)  0.00 (0.09)· 0.04 (0.60) 0.54 (0.01)** 0.21 (0.18) 0.21 (0.21) 0.00 (1.00) 0.44 (0.00)*** 0.10 (0.04)*  0.00 (0.04)* 0.03 (0.69) 0.77 (0.01)** 0.10 (0.65) 0.09 (0.72) 0.05 (0.24) 0.37 (0.00)*** 0.04 (0.50) 0.17 (0.01)**  0.00 (0.10)· 0.10 (0.17) 0.66 (0.00)*** 0.22 (0.17) 0.14 (0.43) 0.02 (0.56) 0.41 (0.00)*** 0.10 (0.05)* 0.03 (0.46)  − −  − −  − −  −  − − −  R-square F-value RSS  0.40 18.17*** 477.26  0.44 31.91*** 722.50  0.40 13.90*** 364.67  0.42 22.08*** 570.63  d.f.  206  313  171  264  (Paths on Life's Way, 2010)  135     Educational attainments, aspirations, and expectations after high school proved to be significant predictors of happiness in 2010, but only for the men in this sample. These were not significant for women. This, in and of itself, although not the expected findings for this study, is a fascinating “non-finding.” Higher education, beyond the secondary level, does not predict happiness for female high school graduates in British Columbia, while it does so for men. Although other levels of education (for example, coded as elementary, secondary, postsecondary) may predict happiness in some places for both men and women (e.g., Blanchflower & Oswald, 2007; Kahneman, 2011), credentials received do not show a linear effect on happiness scores in this sample. One potential problem and critique is treating happiness in this simplistic manner, which was criticized in the qualitative findings of this study. Therefore, I examine the effects of these variables on mental and physical health and life satisfaction as well, in order to get a full picture of any other potential links between happiness, well-being, and postsecondary educational attainment.  Other well-being and educational variables. Regression analysis 5: physical health. The variables in these analyses are operationalized in the same manner as explained above (see the previous analyses). The first analysis uses physical health as the outcome variable (see Table 18).  136     Table 18 The effect of demographic and educational variables on physical health by gender Predictors  Men  Women Bs  Intercept Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) Children (No=0) Level of Stress (10=Very Stressful) Mental Health (10=Very Healthy) Highest Educ. Attain. 2010 (20=PhD)  − − −  R-square RSS d.f.  Bs  2.15 (0.04)* 0.00 (0.26) 0.30 (0.01)** 0.14 (0.76) 0.20 (0.46) 0.02 (0.95) 0.02 (0.80) 0.49 (0.00)*** 0.04 (0.51)  − −  0.24 (0.77) 0.00 (0.40) 0.38 (0.00)*** 0.11 (0.67) 0.29 (0.15) 0.29 (0.19) 0.05 (0.32) 0.58 (0.00)*** 0.09 (0.02)*  0.35 594.2  0.42 911.72  179  280  (Paths on Life's Way, 2010)  Here, two main effects are seen: Firstly, exercise and mental health are highly predictive of physical health for both men and women, and, secondly, women’s post-secondary educational attainment is a significant influence on physical health in this model. Specifically, each one-unit increase on the scale of post-secondary educational attainments is associated with a 0.09 (p<.05) increase on the scale of physical health. Thus, post-secondary education may have an indirect effect on women’s happiness through an effect on their physical health. This model does a better job of predicting women’s (R2=0.42) scores than men’s (R2=0.35), but this model is significant for both men (F=12.91, p<.01) and women (F=25.78, p<.01).  Regression analysis 6: mental health. The sixth analysis uses mental health as the outcome variable (see Table 19).  137     Table 19 The effect of demographic and educational variables on mental health by gender Predictors  Men  Women Bs  Intercept Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) Children (No=0) Level of Stress (10=Very Stressful) Physical Health (10=Very Healthy) Highest Educ. Attain. 2010 (20=PhD) R-square RSS d.f.  − − −  Bs  2.73 (0.01)** 0.00 (0.96) 0.13 (0.27) 0.34 (0.47) 0.31 (0.27) 0.79 (0.03)* 0.14 (0.03)* 0.51 (0.00)*** 0.07 (0.21)  − − − −  4.25 (0.00)*** 0.00 (0.05)* 0.07 (0.43) 0.23 (0.37) 0.11 (0.55) 0.05 (0.82) 0.26 (0.00)*** 0.55 (0.00)*** 0.01 (0.90)  0.36 630.95  0.43 899.1  179  280  (Paths on Life's Way, 2010)  Three gender differences emerge in this analysis: First, while physical health and stress are both predictive of mental health for men and women, stress is much more significant for women than men; second, children exert a positive, significant effect on men’s mental health, but show no effect on women’s mental health; and, third, household income is a strong predictor of women’s mental health, but not men’s. Dramatically, each one-unit increase in stress for women is associated with an 0.26 (p<.01) decrease on the scale of mental health, while men show an 0.14 (p<.05) decrease. It is particularly interesting that stress does not show a significant effect on either happiness or physical health, but does show an effect on mental health. This illustrates that although these variables are related, they tap into different underlying constructs. Men with children show an 0.79 (p<.05) increase in mental health relative to those who don’t, but marriage and marital change show no significant effect on mental health in this model for men or women. The models were both significant (F=13.53, p<.01 for men, F=27.78, p<.01 for women). 138     Regression analysis 7: life satisfaction. Life satisfaction is often measured by researchers on a five-point scale as a proxy for subjective well-being (van Praag et al., 2003; Delle Fave et al., 2011). The following two analyses regress demographic and educational variables onto life satisfaction, but the second incorporates happiness as a predictor variable, while the first does not. Life satisfaction is operationalized as the participants’ response to the question, “Thinking back to when you were in high school and the kinds of hopes you had then, how satisfied are you with the way things have turned out for you now in the way your life as unfolded to date? (check one)” (Andres, 2010, p. 25, emphasis in original; see Appendix A). The response categories are “very dissatisfied” to “very satisfied” with a midpoint of “neutral.” There is no “not applicable” option on this question. The other variables were operationalized as above.  139     Table 20 The effect of demographic and educational variables on life satisfaction by gender Predictors  Men  Women Bs  Intercept Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) Children (No=0) Level of Stress (10=Very Stressful) Physical Health (10=Very Healthy) Mental Health (10=Very Healthy) Highest Educ. Attain. 2010 (20=PhD) R-square RSS d.f.  − −  Bs  1.81 (0.00)*** 0.00 (0.02)* 0.04 (0.43) 0.22 (0.34) 0.22 (0.11) 0.31 (0.09)· 0.04 (0.18) 0.02 (0.60) 0.21 (0.00)*** 0.02 (0.54)  − − −  1.58 (0.00)*** 0.00 (0.02)* 0.01 (0.89) 0.49 (0.00)*** 0.04 (0.73) 0.16 (0.21) 0.04 (0.14) 0.04 (0.31) 0.18 (0.00)*** 0.04 (0.11)  0.38 160.8  0.29 256.76  179  278  (Paths on Life's Way, 2010)  One can see that mental, but not physical health, exerts a strong influence on life satisfaction in this model for both men and women (see Table 20). Income is also predictive of life satisfaction for both groups. The most striking finding here is the importance of marriage (which includes common-law) for women in predicting life satisfaction levels. Women who were married or in common-law relationships reported an 0.49 (p<.01) greater level of life satisfaction than those who were not in such relationships. No such effect emerged for the men; however, children influenced men’s life satisfaction but not women’s in this model. This reflects a difference between life satisfaction and happiness as outcome variables, as men’s marital status was highly significant in the baseline model with happiness as the outcome variable. Both models were significant (F=13.17, p<.01 for men, F=13.6, p<.01 for women).  140     Regression analysis 8: life satisfaction incorporating happiness. The final analysis in this section incorporates happiness as a predictor variable (see Table 21).  Table 21 The effect of demographic, educational, and happiness variables on life satisfaction by gender Predictors  Men  Women  Intercept Household Income (in 1000s of CAD) Exercise Married (No=0) Marital Change (No=0) Children (No=0) Level of Stress (10=Very Stressful) Physical Health (10=Very Healthy) Mental Health (10=Very Healthy) Happiness (10=Very Happy) Highest Educ. Attain. 2010 (20=PhD)  0.42 (0.39) 0.00 (0.09)· 0.01 (0.91) 0.03 (0.90) 0.19 (0.11) 0.18 (0.23) 0.03 (0.31) 0.00 (0.94) 0.10 (0.01)** 0.35 (0.00)*** 0.01 (0.60)  Bs  − −  Bs  − −  0.41 (0.34) 0.00 (0.07)· 0.01 (0.82) 0.32 (0.02)* 0.05 (0.62) 0.08 (0.46) 0.04 (0.09)· 0.00 (0.89) 0.03 (0.46) 0.37 (0.00)*** 0.00 (0.15)  R-square RSS  0.56 160.8  0.48 256.76  d.f.  179  278  (Paths on Life's Way, 2010)  Once included, this overshadows all other effects, again pointing to the strong link between happiness and mental health. The models are both significant (F=23.60, p<.01 for men, F=26.44, p<.01 for women). Mental health is still linked to men’s life satisfaction, and marriage to women’s life satisfaction, in this model; however, controlling for happiness diminishes the effects of all other variables, pointing to the strong interrelations between these variables, which is unavoidable in the social sciences and in the lives of human beings.  141     Correlations between relevant variables. The correlations between these variables are included below:  Table 22 Correlation matrix of relevant variables related to happiness and well-being  Happiness Mental Health Physical Health Life Satisfaction Stress Excitement  −  Happiness  Mental Health  Physical Health  Life Satisfaction  Stress  Excitement  1.00 0.60 0.42 0.69 0.21 0.60  0.60 1.00 0.59 0.50 0.30 0.44  0.42 0.59 1.00 0.34 0.19 0.40  0.69 0.50 0.34 1.00 0.21 0.51  0.21 0.30 0.19 0.21 1.00 0.00  0.60 0.44 0.40 0.51 0.00 1.00  −  −  *All relationships are significant except that between excitement and stress.  −  − − − −  (Paths on Life's Way, 2010)  142     The “conventionality” of happiness. 16 The final analyses take a different approach by using two types of regression analyses to regress happiness onto employment, income, marital status, family status, exercise (used as a proxy for health status), and satisfaction with educational and employment decisions. The first is an ordinary least squares (OLS) regression, which treats the dependent happiness variable as continuous despite the fact that it is an ordinal variable on a Likert scale coded from one to 10. Other researchers have used the same approach in recent studies (see, for example, van Praag et al., 2003). Happiness is operationalized here by the participants’ response to the survey question, “On a scale of 1 to 10, in general how happy would you say you are with your life? (circle one)” (Andres, 2010b, p.23, emphasis in original; see Appendix A). The second analysis uses a recoded binary version of the “happiness” variable, and uses logistic regression. In this case, happiness is operationalized as a “high happiness” or “low happiness” binary variable, using the same Likert-scale question with the cut-off for “high” being eight and above. Thus, this analysis attempts to predict under which circumstances extremely high levels of happiness occur in this sample. Each analysis was run separately with and without influential cases, but the results were similar enough that the analyses with all cases were kept.17 The independent variables were the same in both analyses. The “employment” variable indicates whether the participant has been employed in paid work at any time in the past seven years (since the last survey in 2003). The “life choices” variables on work and education each ask the participant, “If you had the choice to make again would you choose the same [line of work/educational choices]?” to which the participants choose “yes” or “no.” The “income” variable is the total household income of the participant and their spouse/partner (if applicable) 16  The analyses in this section were run in R rather than SPSS. Missing data was excluded, with a maximum number of missing cases of 57. All participants responded to the “happiness” question. The total sample size for this analysis was 570. 17  143     from all sources, before taxes or deductions, in 2009. It is recoded into thousands of Canadian dollars. The “marital status” variable is recoded from six options into a binary variable of married or not, as is the “children” variable (see Appendix A for the original questions and response categories). The “health” variable is operationalized as exercise frequency, from the question, “How often do you participate in sports or engage in regular exercise?” It is recoded from five options to a binary measure, with once a week or less as “no” and two or more times a week as “yes.” Each of these variables can be tracked over time, from 1988 to the present, but only the 2010 data were used in the present study.  Regression analysis 9: happiness and traditional markers of success. The first analysis in this section regresses happiness on employment, work and educational life choices, income, marital status, family formation, health, and sex of the participant (see Table 23). The regression equation for this model is Y happy = β 0 + β 1 x employed + β 2 x samework + β 3 x income + β 4 x sameeducation + β 5 x sex + β 6 x married + β 7 x children + β 8 x exercise +e  144     Table 23 The effect of employment, life choices, income, marital and family status, and gender on happiness Predictors Intercept Employed (No=0) Choose Same Work Again (No=0) Household Income (in 1000s of CAD) Choose Same Education Again (No=0) Sex (Male=0) Married (No=0) Children (No=0) Exercise (No=0)  Βs 4.79 (0.00)*** 1.09 (0.06)· 0.69 (0.00)*** 0.00 (0.00)*** 0.32 (0.02)* 0.06 (0.64) 0.37 (0.03)* 0.53 (0.00)*** 0.35 (0.01)**  R-square RSS d.f.  0.18 930.03 487.00 (Paths on Life’s Way, 2010)  The overall model is significant (F=14.93, p<0.01) with an R2 of 0.18, which is a medium effect size according to Cohen’s (1988) criteria. The participants’ satisfaction with their choice of work, their household income, and whether or not they have children are associated with general increases in happiness on the Likert-scale variable measuring overall happiness. The participants’ satisfaction with their choice of work is associated with an 0.69 (p<.01) increase in happiness on the Likert-scale measure. A thousand-dollar increase in yearly household income is associated with an 0.002 (p<.01) increase in happiness, which is statistically if not substantively significant. Having children is associated with an 0.53 (p<.01) increase in happiness on this scale (otherwise stated, those with children scored, on average, 0.53 units higher on the happiness variable). These are the most significant associations; however, participants’ satisfaction with their educational choices, whether they are married, and their frequency of exercise are also statistically significant. Those participants who are satisfied with their educational choices report a 0.32 (p<.05) higher level of happiness on the Likert scale than those who are not satisfied.  145     Those who are married report a 0.37 (p<.05) higher score on the Likert-scale happiness variable than those who are not married. Finally, those who exercise frequently report a 0.35 (p≤.01) higher score on the Likert-scale happiness variable than those who do not. Thus, the overall hypothesis that “traditional” modes of success, such as employment and education satisfaction, income, family formation, and health, lead to happiness is supported in this model. Those participants who achieve “traditional” success, that is, who have a job they are satisfied with, a higher income than others, and children tend to also have increased happiness. The same is true of those who are satisfied with their educational choices, are married, and exercise regularly (used here as a subjective marker of good health). The presence of each of these is associated with general increases in “happiness,” supporting the notion that these stereotypes of the “good life” may indeed lead to greater happiness. When the analysis is divided by gender, slightly different patterns emerge (see Table 24). Employment plays a larger role in men’s happiness, while satisfaction with work and educational decisions plays a much larger role for women. Marriage is more important for men’s happiness, while children are more important to women’s happiness. Finally, exercise is more important for women’s happiness in this model. Both models are significant; however, the model for men does a better job of accounting for the variance in happiness scores than the model for women (R2=0.21 for men and R2=0.16 for women).  146     Table 24 The effect of employment, life choices, income, marital and family status on happiness by gender Predictors  Men  Women  Intercept  4.20 (0.00)***  5.31 (0.00)***  Employed (No=0) Choose Same Work Again (No=0) Household Income (in 1000s of CAD) Choose Same Education Again (No=0) Married (No=0) Children (No=0) Exercise (No=0)  1.57 (0.06)· 0.71 (0.01)** 0.00 (0.01)** 0.10 (0.66) 0.69 (0.03)* 0.44 (0.12) 0.30 (0.17)  0.71 (0.38) 0.70 (0.00)*** 0.00 (0.09)· 0.48 (0.01)** 0.22 (0.30) 0.55 (0.01)** 0.35 (0.06)·  R-square F-statistic  0.21 8.6  0.16 9.16  d.f.  192  288 (Paths on Life’s Way, 2010)  Although these analyses provides useful statistically- and substantively-significant findings, a second type of analysis is necessary for several reasons. Firstly, the associated increases in “happiness” on the Likert scale, such as the 0.53 increase for those participants who have children, are hard to interpret substantively. Are the distances between each of these values the same? Is a six “twice as happy” as a three? Most statistical analysts would suggest that this is not the case, although many researchers make the assumption that people’s responses on Likertscale happiness questions are “interpersonally comparable at an ordinal level” (van Praag et al., 2003, p.33). Secondly, the “happiness” measure was predicted better for middle and high values than low values in the OLS regression analysis (see Figure 6 and Figure 7), partly due to the fact that the responses are skewed, with the great bulk falling above seven on the ten-point Likert scale (M=7.8, SD=1.5; see Figure 5). Finally, the basic question arises: Is it reasonable to think of happiness in this linearly increasing fashion?  147     Figure 5. Histogram of happiness scores for the first model.  148     Figure 6. Standardized residuals versus fitted values for the first model.  149     Figure 7. QQ plot of standardized residuals for the first model. These questions are very difficult to answer; therefore, a complementary approach is necessary to look at “happiness” from another perspective. For this reason, a binary measure of happiness is introduced in the second analysis. The cut-off point was chosen as eight, to separate those who report significantly high levels of happiness while maintaining large enough sample sizes in each category for the analysis. While the first analysis examined how we can predict general increases in happiness, the second will enable us to predict very high levels of happiness from our markers of “traditional” success. In this approach, I follow statistically what Wilson (1967) and others have implied theoretically: I am predicting those who are “most happy,” as “the majority of people avow positive levels of happiness” both in this dataset and more generally in North America (Diener et al., 1999, p.286).  150     Regression analysis 10: logistic regression. The second analysis again regresses happiness on employment, work and educational life choices, income, marital status, family formation, health, and sex of the participant (see Table 25), but uses logistic regression and a binary measure of happiness. 18 The regression equation for this model is Logit(Y very happy ) = β 0 + β 1 x employed + β 2 x samework + β 3 x income + β 4 x sameeducation + β 5 x sex + β 6 x married + β 7 x children + β 8 x exercise +e  The binary measure allows the participants to be separated into two groups: Those who exhibit extremely high levels of “happiness” and those who do not (with the cut-off for “yes” as eight on the Likert scale). Using logistic regression, it is possible to compute the odds, percentage change in odds, and predicted probabilities of being “very happy” from the independent variables. This moves beyond the previous analysis, which is limited to linear numeric increases on the Likertscale measure of happiness.  18  Employment is excluded from the analyses run only on men, as the lack of variability in this sample (98% of the men were employed), meant that very large and unrepresentative betas resulted from analyses including this variable.  151     Table 25 Determinants of happiness in BC high school graduates Logit β Intercept Employed (Yes=1) Choose Same Work Again (Yes=1) Household Income (in 1000s of CAD) Choose Same Education Again (Yes=1) Sex (Female=1) Married (Yes=1) Children (Yes=1) Exercise (Yes=1)  -3.70*** 2.11· 0.87*** 0.00* 0.38· -0.03 0.52· 0.58* 0.40·  S.E. 1.19 1.15 0.24 0.00 0.22 0.21 0.27 0.26 0.23  p-value 0.00 0.07 0.00 0.03 0.08 0.87 0.06 0.03 0.08  Odds Exp(B)  Percentage change in Odds 100[exp(β x δ)-1]  0.02 -97.53 8.24 723.68 2.39 138.98 1.00 0.37 1.46 46.34 0.97 -3.39 1.67 67.40 1.79 79.40 1.49 49.47 (Paths on Life’s Way, 2010)  In this model, satisfaction with choice of work, household income, and having children were statistically significant (p<.05). The odds of reporting high levels of happiness increase by a factor of 2.39 when the participant is satisfied with their choice of work versus not, the odds of reporting high levels of happiness increase by a factor of 1.004 for each one thousand Canadian dollar increase in yearly household income, and the odds of reporting high levels of happiness increase by a factor of 1.79 when the participant has children versus when the participant does not have children. These correspond to a 139% increase in the odds of reporting being very happy for those who are satisfied with their choice of work versus not, a 4% increase in the odds of reporting being very happy for each additional $10,000 CAD in household income each year, and a 79% increase in the odds of reporting being very happy for those who have children versus those who do not. These results illustrate the importance of work and family in the participants’ likelihood of reporting being very happy, and the less important but still significant effect of income.  152     Satisfaction with educational choices, being married, and health as operationalized by exercise frequency are significant at a lower level (p<.10). However, these too increase participants’ odds of reporting being high levels of happiness. The odds of reporting high levels of happiness increase by a factor of 1.46 when the participant is satisfied with their choice of education versus not, the odds of reporting high levels of happiness increase by a factor of 1.67 when the participant is married versus not, and the odds of reporting high levels of happiness increase by a factor of 1.49 when the participant exercises frequently versus not. The overall model is significant with a log likelihood of -282.84 (df=487) as compared to an intercept-only model. The Akaike information criterion (AIC) for this model is 583.7, which is much larger than the AIC values for the models run separately for men (see Table 29) and for women (see Table 30). 19 The logistic regression model also allows comparisons of predicted probabilities of reporting high levels of happiness between different groups of respondents based on their standing on various independent variables. For example, examining the income variable, those who earn the lowest incomes per year have an 0.57 predicted probability of reporting being very happy while those who earn the highest incomes per year have an 0.95 predicted probability of reporting being very happy, holding all other variables constant (see Table 26). This illustrates the influence of income in a way that the linear regression and examination of the odds do not. Here, the significance of the income variable is readily apparent. The differences are most dramatic at either end of the range of the variable, suggesting that future research may want to investigate whether this variable could be better captured as a non-linear variable. 20  19  The AIC provides a measure of the relative goodness of fit of a model, with lower values indicating less information lost in the model. 20 Others, such as Kahneman (2011) have investigated the relationship between income and happiness in this way.  153     Table 26 Predicted probability of happiness from income Income  Predicted Probability of Happiness  3000 (Min) 70000 (Q1) 120300 (Median) 150000 (Q3) 750000 (Max)  0.57 0.63 0.67 0.70 0.95 (Paths on Life’s Way, 2010)  Family status, in terms of marriage and children, also changes participants’ probabilities of reporting high levels of happiness (see Table 27). The predicted probability of reporting being very happy if the participant is not married is 0.58 and is 0.70 if the participant is married. Likewise, for those participants who have children, their predicted probability of reporting high levels of happiness is significantly greater than those without children. There is no difference between men and women in predicted probabilities of reporting happiness in this analysis. Both are 0.67, which is the overall predicted probability for this sample, holding all variables at their means.  Table 27 Predicted probability of happiness from family status Family Status Not Married Married No Children Children  Predicted Probability of Happiness 0.58 0.70 0.57 0.70 (Paths on Life’s Way, 2010)  Lastly, the participants’ satisfaction with life choices is another way to group the participants and compare their predicted probabilities of high levels of happiness (see Table 28).  154     Those who would not choose the same work again, i.e. were not satisfied with their choice of work after high school, have an 0.51 predicted probability of reporting being very happy, holding all other variables constant. Those who would choose the same work again had a 0.72 predicted probability of reporting being very happy, on the other hand. The findings are similar, although less statistically significant (p<.10) for satisfaction with educational choices after high school.  Table 28 Predicted probability of happiness from life choices Life Choice Would not choose same work again Would choose same work again Would not choose same education again Would choose same education again  Predicted Probability of Happiness 0.51 0.72 0.62 0.71 (Paths on Life’s Way, 2010)  When separated by gender, slightly different findings emerge for men (see Table 29) than women (see Table 30). For men, satisfaction with choice of work, household income, and exercise were statistically significant (p<.05). The odds of reporting high levels of happiness increase by a factor of 3.03 when the male participant is satisfied with their choice of work versus not, the odds of reporting high levels of happiness increase by a factor of 1.01 for each one thousand Canadian dollar increase in yearly household income, and the odds of reporting high levels of happiness increase by a factor of 2.16 when the male participant exercises frequently versus not. These correspond to a 203% increase in the odds of reporting being very happy for those who are satisfied with their choice of work versus not, a 5% increase in the odds of reporting being very happy for each additional $10,000 CAD in household income each year, and a 116% increase in the odds of reporting being very happy for those who exercise frequently versus those who do not. These results illustrate the importance of work and physical health in 155     the male participants’ likelihood of reporting being very happy, and the less important but still significant effect of income. Satisfaction with educational choices and being married are significant at a lower level (p<.10). However, these too increase male participants’ odds of reporting being high levels of happiness. The odds of reporting high levels of happiness increase by a factor of 1.02 when the male participant is satisfied with their choice of education versus not, which is a substantively small difference, but the odds of reporting high levels of happiness increase by a factor of 2.25 when the male participant is married versus not, which a substantively large difference. The overall model has an AIC of 228.8, while the model for women (below) has an AIC of 365.5.  Table 29 Determinants of happiness in male BC high school graduates Logit β Intercept Choose Same Work Again (No=0) Income (in thousands of dollars) Choose Same Education (No=0) Married (No=0) Children (No=0) Exercise (No=0)  -2.29*** 1.11** 0.01* 0.02 0.81 0.65 0.77**  S.E. 0.58 0.42 0.00 0.38 0.49 0.45 0.35  p-value 0.00 0.01 0.04 0.10 0.10 0.15 0.03  Odds Exp(B) 0.10 3.03 1.01 1.02 2.25 1.92 2.16  Percentage change in Odds 100[exp(β x δ)-1] -89.87 203.44 0.50 2.02 124.79 91.55 115.98 (Paths on Life's Way, 2010)  In comparison, for the women in this sample, satisfaction with choice of work and choice of education were the only statistically significant variables (p<.05). The odds of reporting high levels of happiness increase by a factor of 2.32 when the female participant is satisfied with their choice of work versus not and the odds of reporting high levels of happiness increase by a factor of 1.80 when the female participant is satisfied with their choice of education versus not (see Table 30). These correspond to a 132% increase in the odds of reporting being very happy for 156     those who are satisfied with their choice of work versus not, and an 80% increase in the odds of reporting being very happy for those who are satisfied with their choice of education versus those who are not. Being married, having children, and exercising frequently are not significant in this model (p>.10). These results suggest that although educational attainments did not exert a significant influence upon women’s happiness in the linear models, it may be important in predicting very high levels of happiness for women. Surprisingly, although marriage and children emerged as important in the linear models, they were not significant in the logistic model. Again, it may be that these are useful in predicting linear increases in happiness, but not exceptionally high levels of happiness. These findings illustrate the importance of work and education in women’s lives, as well as men’s. However, rather than the key being “higher education” as such, whether or not the participant has chosen an education and career that she enjoys and is satisfied with is most important in predicting those who are most happy in life overall.  Table 30 Determinants of happiness in female BC high school graduates Logit β Intercept Employed (No=0) Choose Same Work Again (No=0) Income (in thousands of dollars) Choose Same Education (No=0) Married (No=0) Children (No=0) Exercise (No=0)  -2.61* 1.37 0.84*** 0.00 0.59* 0.36 0.52 0.09  S.E. 1.31 1.27 0.29 0.00 0.27 0.33 0.33 0.30  p-value 0.05 0.28 0.00 0.22 0.03 0.28 0.11 0.75  Odds Exp(B) 0.07 3.94 2.32 1.00 1.80 1.43 1.68 1.09  Percentage change in Odds 100[exp(β x δ)-1] -92.65 293.54 131.64 0.30 80.40 43.33 68.20 9.42 (Paths on Life's Way, 2010)  157     A year after she graduated from high school in 1988 one of the participants of the Paths on Life’s Way Project described the “good life” in the following way: Having a happy job, a good family, a good income so you don’t have to worry about anything, you’ve got your house paid off and everything, and you’ve gotta really nice career that you really enjoy and you’ve got a husband and that’s probably the good life. Just having everything set, good – very organized and paid for… that’d be the good life (female participant, as quoted in Andres & Wyn, 2010, p.61). These “traditional” markers of success, including “the suburban home with the lawn, the two car garage and two floors and kids,” were representative of 77% of the interviewees at this time (Andres & Wyn, 2010, p. 61). Based on this espousal of “traditional” values, the current analysis examined to what extent these markers of success contributed to happiness – 22 years later. Examining the influence of satisfaction with job choice, household income, satisfaction with post-secondary education, being married, having kids, and engaging in a healthy lifestyle on “happiness” scores, this analysis supports the hypothesis that “traditional” markers of success are indeed influential in predicting happiness within this group. Using both OLS and logistic regression, satisfaction with choice of work, household income, and having children proved to be particularly strongly associated with happiness. These conclusions support very early research into the correlates of happiness and also move further to suggest that if these goals are valued they may be instrumental in causing higher levels of happiness (Wilson, 1967; Diener et al., 1999; Kahneman, 2011).  Summary. These analyses examined the factors that are important for predicting happiness within the Paths on Life’s Way sample. Three emerged as consistently significant: Mental health, physical health, income, and marriage. When examining a model including many different demographic  158     variables, I found that increases in health and income are associated with general increases in happiness on the ten-point Likert scale, and being married results in an increase in happiness as compared to not being married, in line with previous findings (Diener et al., 1999; Helliwell & Putnam, 2004; Kahneman, 2011). Although gender does not exert a significant linear effect on happiness, the variables that predicting happiness for men and women were different in several ways: Although being married shows a significant positive affect both sexes, the men have a larger happiness gain than do the women; in contrast, mental health seems to be more important for women’s happiness than men’s; income has a modest affect on the happiness of both men and women, while stress does not seem to affect the happiness of women (although it may exert a slight negative affect on men’s happiness). When highest educational attainment is added into the regression equation, mental and physical health, as well as income and marriage, still remain the main predictors of happiness. This follows from other studies, which have found health to be the single greatest predictor of happiness, and social capital in the form of family and friends to be very influential as well (Helliwell & Putnam, 2004). Educational attainments, aspirations, and expectations after high school proved to be significant predictors of happiness in 2010, but only for the men in this sample. The level of the women’s desired and expected educational attainments, as well as the difference scores between these, were insignificant when added to the model, being not at all predictive of happiness scores. This, in and of itself, although not the expected findings for this study, is a fascinating “non-finding.” Higher education, beyond the secondary level, is predictive of men’s, but not women’s, happiness. This is an interesting puzzle in a time when women’s post-secondary participation is outpacing that of men. This finding both complements and contradicts Stevenson and Wolfers (2007) findings in their article “The Paradox of Declining  159     Female Happiness.” Although the women in this study report the same levels of happiness as men, the variables that emerge as important in predicting their happiness are different. In many ways, men’s and women’s “traditional” roles of marriage and family versus education and career are reflected in these findings. When looking at other areas of well-being, the results are similar in many ways, but include some interesting differences: For example, exercise and mental health are highly predictive of physical health for both men and women, but a gender difference emerges in postsecondary educational attainment, where women’s attainment exerts a significant influence on physical health. Thus, post-secondary education may have an indirect effect on women’s happiness through an effect on their physical health. When looking at mental health, physical health and stress are both predictive for men and women, stress is much more significant for women than men. It is particularly interesting that stress does not show a significant effect on either happiness or physical health, but does show an effect on mental health. This illustrates that although these variables are related, they tap into different underlying constructs. When looking at life satisfaction, I found that marriage (which includes common-law) is very important for women, but not men, in predicting life satisfaction levels. This showed a remarkable difference between life satisfaction and happiness as outcomes variables, as men’s marital status was highly significant in the baseline model with happiness as the outcome variable. When one includes happiness as an independent variable for predicting life satisfaction, it diminishes the effects of all other variables. This points to the strong interrelations between these variables, which, as stated in other parts of this thesis, is unavoidable and very much a part of studying and being human.  160     The final analyses in this series took a different approach by using two types of regression analyses to regress happiness onto employment, income, marital status, family status, exercise, and satisfaction with educational and employment decisions. The first was an ordinary least squares (OLS) regression like the previous ones, and the second was a logistic regression with a binary outcome variable constructed for happiness. The overall hypothesis was that “traditional” modes of success, such as employment and education satisfaction, income, family formation, and health, lead to happiness, and this was supported in this model. Those participants who achieve “traditional” success, that is, who have a job they are satisfied with, a higher income than others, and children tend to also have increased happiness. The same is true of those who are satisfied with their educational choices, are married, and exercise regularly. The presence of each of these is associated with general increases in “happiness,” supporting the notion that these stereotypes of the “good life” may indeed lead to greater happiness. This refutes the notion that “more education” or higher levels of degrees necessarily increase happiness, but rather that making the most of whatever education you do have – by getting a better-than-average-paying job that you enjoy, getting married, having a family, and exercising regularly – may be the best route to happiness for many people. However, for men, a higher education is more instrumental in achieving happiness than for women. This suggests that “traditional” gender roles may still influence happiness to a certain extent. However, a key finding is that higher educational attainment will not automatically lead to greater happiness if the other parts of one’s life don’t also move forward; family, friends, good health and exercise, and a spouse and children emerge as much more integral to happiness in these analyses than education. Perhaps Kahneman’s (2011) tongue-in-cheek definition of happiness is true after all,  161     perhaps it really is “the experience of spending time with people you love and who love you” (p. 395).  162     Chapter 5: Conclusion Happiness, however, is extremely important since being happy is a momentous achievement in itself. Happiness cannot be the only thing that we have reason to value, nor the only metric for measuring other things that we value, but on its own, happiness is an important human functioning. The capability to be happy is, similarly, a major aspect of the freedom that we have good reason to treasure. The perspective of happiness illuminates one critically important element of human living. (Sen, 2008, p. 26) A “hot topic” in academic research, popular books, and top-40 pop songs, happiness is the focus of more discussion than ever and has maintained its relevance from the writings of ancient Greece and the teachings of ancient India to the present day. It has become so pervasive that some term it a “modern obsession” (Burnett, 2011). Although most people in North America today have a standard of living beyond which our ancestors a millennium ago could even have imagined, advances in technology also present new challenges. For human beings, who evolved under much different circumstances, material comfort and a huge array of life choices may not be an automatic recipe for life satisfaction. However, as Jeffrey Sachs points out in the recently published World Happiness Report, this should not necessarily come as a surprise. He argues, These contradictions would not come as a shock to the greatest sages of humanity, including Aristotle and the Buddha. The sages taught humanity, time and again, that material gain alone will not fulfill our deepest needs. Material life must be harnessed to meet these human needs, most importantly to promote the end of suffering, social justice, and the attainment of happiness. The challenge is real for all parts of the world. (Sachs, 2012, p. 3) The aim of the present study was to highlight the importance of higher education for nonmonetary benefits and the pursuit of learning for the creation of a “better life” for the individual and society. This study found that what contributes to happiness and well-being is not so much “more” or “higher” post-secondary education, but rather achieving a level of education with which one can be satisfied and that leads to a career which allows for a balanced and healthy  163     lifestyle. This study contributes to the advancement of knowledge by creating a better understanding of how we can accurately define and measure happiness considering the lived experiences and perspectives of the research participants and also by highlighting how education can influence the happiness and well-being of individuals.  Summary of Research Findings The purpose of this study was to create definitions and conceptualizations of the constructs of “happiness” and “well-being” in a large sample of the high school graduate class of 1988 in British Columbia, Canada, and then explore the relationship between these concepts and postsecondary educational aspirations and attainment. In this thesis, I used data from the 22-year longitudinal Paths on Life’s Way Project. Data were collected using survey methods (n=574) and interviews (n=19). I employed a mixed methods approach by analyzing both quantitative and qualitative data: Specifically, I used the survey data extensively and also analyzed the qualitative interview data to better define and conceptualize “happiness” and “well-being” for members of the high school graduating class of 1988 in British Columbia, Canada. The overarching research question of this study was, “What constitutes “happiness” and “well-being” for the 1988 high school graduates of British Columbia?” Within this broad research question were several specific questions: i) How do Paths on Life’s Way interview participants define and describe “happiness”? How do they define and describe “well-being”? Are these constructs the same or different? Are there differences by gender?  164     ii) Do separate factors of “happiness” and “well-being” emerge from the numerical questionnaire data of the survey participants? Do other related sub-factors emerge as well? iii) What is the relationship among happiness, well-being, post-secondary aspirations, expectations, and attainment, and other control variables in the survey data? Does the nature of this relationship differ by gender?  Research Finding 1: Happiness is Not Well-being First, I examined the interview transcriptions to understand the ways participants approach the task of assessing their own happiness and well-being when answering survey questions and to define and conceptualize “happiness” and “well-being” using the participants’ explanations of their process of answering the survey questions as a guide. The aim was to define the concepts of “happiness” and “well-being” in terms of the participants’ own descriptions of these concepts. I used the theoretical framework of Sen’s (1985, 1993, 2005) conceptualization of functionings and capabilities in relation to people’s well-being and agency to inform the basic hypothesis of this analysis, which was that people’s perceptions of their own “happiness” and “well-being” are not only distinct, but also dependent on context, time, and life sphere (e.g., work vs. family). Based upon the participants responses, I defined happiness as a positive feeling towards and evaluation of one’s self and life at a particular point or period in time, which includes an optimal balance between achievement and acceptance. In contrast, I defined well-being as a positive and healthy overall state of being in many areas of life at a particular point or period in time, including one’s physical state, mental state, social state, work state, and others, in which all of  165     these domains interrelate and impact one another substantially. Both of these are influenced by people’s unique values, goals, and life circumstances, although some commonalities emerge as well. Sen’s (1993) capabilities approach provided a strong theoretical framework for this study because it pointed to potential differences in well-being and happiness, and also to areas of life and freedoms that might be important to people irrelevant of the potential impact on their happiness. Much like the interview participants pointed out, and contrary to much of the “happiness research” done today, Sen argues that happiness is only one (perhaps small) part of well-being and that well-being is not the only valued achievement human beings strive for. Much of what participants talked about in the interviews was centered on values, goals and notions of the “good life,” or what the participants wanted their life to be like and how it compared to that ideal at the present moment. These ideas fit nicely into Sen’s approach, especially within his distinction between functionings and capabilities. Interview participants not only focused on what they were doing and being already, but also on what they are able to be and do and could be and do. A tension existed here. People engage in an ongoing act of balancing acceptance and achievement in order to be happy. This balancing act requires that people be capable of achieving various valued states and goals, and also that they actually achieve some of these. However, they must also accept many areas of life that cannot be changed (or cannot be changed at this time) in order to achieve happiness. Some chose to put happiness “on hold” at various times in order to accomplish goals. Most viewed happiness as a life goal, an individual endeavor, and something that required personal freedom in order to attain it. I created this metaphor of a balance, and combined it with a larger metaphor for well-being: A simple machine of  166     interlocking gears, made from different life domains that participants value. One overwhelming finding was the importance of social relationships, which were mentioned by every participant in their interviews.  Research Finding 2: Happiness and Well-being in the Paths on Life’s Way Survey In the second half of this thesis, I used factor analysis to identify factors mapping onto the constructs of “happiness” and “well-being” from the many questions related to these concepts found in the Paths on Life’s Way survey. An initial descriptive analysis of the survey items presented some interesting trends: the participants’ on average desire more time and money, strongly value their personal relationships, strive for balance in their lives, attach great importance to their time with family, consciously focus on their psychological and physical health, exhibit concern for the environment and society in general, but are not keen on religion in general. This group is very cognizant of their well-being, particularly mental well-being, and attaches a great deal of importance to their social connections through family and marriage. In general, women seem to rate themselves as more stressed and less healthy, and desire more help in various parts of their lives to enhance their well-being. However, overall, the Paths on Life’s Way sample is happy and healthy, and generally satisfied with their lives. I performed an exploratory factor analysis of 53 of these items to determine the underlying relationships between them, and their groupings. Five factors emerged: 1) Overall Happiness and Life Satisfaction, 2) Time Spent with Family, Friends, and Self, 3) Social Support and Help, 4) Tensions (Family-Health-Work Balance), and  167     5) Satisfaction with Work, Education, and Finances. The first fits well with the traditional view and measurement of happiness as a meta-construct of both happiness and well-being, or “subjective well-being” (SWB). The other four categories are all areas highlighted by the participants’ in the interviews as well. The notions of balance and gears working in synchrony are useful metaphors when looking at these five factors and how they might relate to each other. The survey participants, just like the interview participants, engage in an ongoing act of balancing many areas of life, including family and friends, work and education, and physical health, and tensions arise between different aspects of well-being that must be balanced or shifted.  Research Finding 3: The Impact of Education and the “Conventionality” of Happiness I also attempted to trace the relationship between post-secondary educational aspirations and attainment and happiness (as well as various indicators of well-being) in the Paths on Life’s Way survey using regression analyses. I split these analyses into separate regression analyses for men and women in order to look at gender differences in these relationships. I hypothesized that happiness and well-being, and participants’ self-ratings of them, related to post-secondary educational aspirations in ways that differed by mental and physical health, marital status, and presence or absence of children. I also expected that the acts of defining and measuring one’s own “happiness” and “well-being” and attempting to change them was an iterative process that is both influenced by and influences one’s educational path. Although lifetime education measured in years of schooling has been found to be “a virtually universal correlate” of happiness and well-being (Helliwell & Putnam, 2004, p. 1436), even when other variables are controlled for in the analysis (Blanchflower & Oswald, 2004), I  168     did not find that post-secondary educational attainments significantly predicted happiness when a detailed breakdown of post-secondary degrees (10 ordinal categories) was included in the regression analysis. However, when limited to three ordinal categories, it was a significant predictor of men’s happiness. This was also true of educational aspirations, expectations, and the difference scores between these from 1989. These significantly impacted men’s 2010 happiness scores, but did not do so for women. These findings suggest that although women are beginning to dominate post-secondary education, they may receive less “happiness” benefit from their investment than do men. This illustrates an intriguing paradox that requires more in-depth investigation in future research. It may be that women are being “educated for stress” in that their further educational attainments may necessitate a difficult juggling act in which they will have to play the roles of worker, mother, wife, caregiver to extended family, and domestic organizer concurrently. These expectations may be “normalized” by society in ways that affect men’s and women’s identities (Robeyns, 2006). As pointed out by Elaine, one of the interview participants, “any working mother takes a huge hit career wise… I have to be there longer hours and just sort of be visible because there’s a lot of discrimination about working mothers… I’m very mindful of that stereotype and I’ve seen it a lot in the work-place with other women.” This may be why women’s satisfaction with their work and educational choices, but not their actual attainments, predicted their happiness. These findings tie in with Robeyns’ (2006) argument: if discrimination against women in education and employment is effectively eliminated, one may think that holding high-skilled jobs is now part of women’s capability sets. However, this is only the case if other sources of gender inequality would be simultaneously addressed, such as allowing parents to balance work and family commitments, and changing attitudes among both men and women which make women the primary parent responsible for the family, and which regard men’s jobs as more important than women’s. Such concerns bring us into the realm of social norms, and dominant codes of masculinity and femininity. (p. 79)  169     These gender differences operate alongside other differences not investigated here, such as race and cultural background, socio-economic status, and the participants’ various forms of social and cultural capital. These other relationships are integral to future research. One of the participants summed up the influential variables impacting happiness in this study very clearly in her interview when she described the good life – and her own life – in the following way: I have a job that I like and it challenges my brain. I don't have to worry about if I’m going to have food on the table. I know that I have shelter, I have food, [and] I have a happy life at home. I have support at home, and friends and family, somebody to share it with, and I think that's really important to have. I don't know what I would do without my friends and my family as well… I never realized before how important [they are] and you realize that when you move – you miss them. So, I think I was right way back then [in 1989] when I said [the good life was] a good job that challenges your brain… but that you can leave at work, and people to share it with. That makes you appreciate your life, and being secure enough that you’ve got your food and your shelter. (Lisa) Summed up like this, the ingredients to a happy life seem very simple indeed. The challenge of the future is to identify whether these capabilities are integral to the happiness of those outside of British Columbia, and if so, how more people can have the opportunity to gain these capabilities.  Research Limitations The first limitation of this study is the fact that, due to the secondary nature of the data and the limitations of time and space, some important variables were left out of the analysis. Race and cultural background were excluded from this study, as these constructs merit an entire study of their own in relation to happiness. As well, socio-economic status and social and cultural capital as passed on from parents, although available, were also not used because they were not central to this study. However, these could play important roles and need to be investigated in future  170     research. Occupations, as coded by type and prestige, were not available for this sample at the time of this study, so this variable was also excluded. My future work will include these variables in order to gain a more complete picture of these relationships. A second limitation – mainly of the quantitative analysis – is that, although causation is implied, it is misleading to claim any causal relationships in the data. As Helliwell and Putnam (2004) assert, because the disposition of being happy may itself affect a person’s social status and capital, “the correlations between social circumstance and subjective well-being might reflect the effects, not the causes of subjective well-being” (p. 1437). Therefore, I have tried to avoid the use of causal language. I describe happiness and well-being as “both an outcome of and a contributing factor to” other variables in the participants lives, such as employment, study, personal relationships, and family (Andres & Wyn, 2010, p. 190). Both the exploratory nature of this research and the fact that I did not use the longitudinal nature of the data as fully in my analyses as would have been possible with more time and advanced methods make this necessary. Although I had longitudinal data at my fingertips, as the Paths on Life’s Way Project is one of the only longitudinal studies of youth in Canada (Andres, 2002) and spans 22 years (from 1988 to 2010), this type of analysis was simply not feasible for a master’s thesis. However, I hope to use the longitudinal data to make stronger arguments for causation in my future doctoral work. The use of Likert-scale questions is a third limitation in this study, although leaders in the field support the use of this type of numerical scale. One of the difficulties of this type of measurement scale is that the researchers cannot control for people’s personalities and dispositions; thus, these factors become part of the error in measurement. Also, as mentioned in the interview findings, some participants feel that a ten is “impossible,” while others will readily  171     rate themselves a ten. On top of this, happiness is not constant, or even consistently valued, over a day, week, month, or decade. Sen’s (1999) example of the fasting versus starving man brings up an important question: Is the participant who is choosing to forgo happiness really equal in happiness (or lack thereof) to another participant who feels that happiness is absolutely unattainable? This could potentially lead to erroneous findings when comparing levels of happiness between individuals, although subjective measures will always face this difficulty. A fourth limitation concerns the outcome variables used in the regression analyses. The interview findings suggested that happiness is a separate construct from well-being; however, due to the constraints of the questions asked in the survey instrument, only questions related to happiness and well-being, but not actually built upon participants’ definitions of these concepts could be used to regress higher educational attainments upon. As well, as stated in that section, the models are vastly simplified in comparison to the realities of the social world. The huge role that chance and contingency play in all of our lives is largely ignored, and the models are simple representations of infinitely complex phenomena. I hope that these analyses at least reached bestcase scenario of being “wrong but useful” (Fox, 2008). In future analyses I would like to investigate the possibility of non-linear relationships amongst these variables, as well as the use of transformations on the variables to unearth more subtle relationships missed by the rather blunt approach of simple linear regression.  Implications and Directions for Future Research The current study falls in line with a recent trend in happiness research, which calls the definitions (or lack thereof) and measurement of this concept into question. Some researchers are also exploring the differences between “happiness” and “well-being” (see, for example, Raibley,  172     2011). Others are attempting to lay people’s understanding of happiness to inform their research, such as the Eudaimonic and Hedonic Happiness Investigation (EHHI) conducted by Delle Fave, Brdar, Freire, Vella-Brodrick, and Wissing (2011), and using mixed methods in the process as well. The current study took a first step towards investigating “one crucial topic has been neglected: what do lay people refer to, when they speak about happiness?” (Delle Fave et al., 2011, p. 187) However, more work needs to be done in refining the definitions that resulted from this study, considering how they relate to other definitions of happiness in the literature, and how to develop measures for these concepts. More research using mixed methods should be done in order to get a more full picture of people’s responses to questions about happiness. The trend towards using single number measures, huge international datasets, and ill-defined terms will not result in meaningful conclusions if we do not understand individuals’ real-life experiences and judgments of happiness and well-being. Using samples that do not consist of only college students will also help to make results transferable to a broader range of people. Another aspect of the current study that should be explored further is the use of Sen’s (1993) capabilities approach, which allows differentiation between well-being and happiness, and takes the unique approach that happiness is only one (perhaps small) part of well-being and that well-being is not the only valued goal people strive for. Although much of “happiness research” tends to idolize the concept, this approach incorporates happiness in a complex web of possibilities, values, and realities that is more reflective of the complex nature of human lives and human society. Researchers, such as Robeyns (2003b, 2006), are already using this approach to examine gender inequality in capabilities, and their example will be very helpful in paving the way for more research on happiness as a capability.  173     The Paths on Life’s Way Project presents a unique opportunity to examine how people describe their happiness levels from both qualitative and quantitative data over 22 years, and should be employed for more research into this topic. The findings from this project have already been instrumental in provincial government policy, and the findings of the present study can further aid policy-makers by suggesting that we cannot assume that higher education provides equal payoffs to men and women. More research needs to be done to determine whether this is related to the fields of study that men and women enter into, which are often different; the different trajectories of men’s and women’s lives, which may include more entrances and exits from the workplace for women; and/or signify a true difference in values and ideas of success between men and women. On a practical level, the repercussions of this in individuals’ lives can be examined.  Conclusion As an important area of research and public policy (Dolan & White, 2007; Greve, 2010; McMahon, 2009), this study will be of interest to scholars and policy makers who are attempting to enhance the lives of citizens and improve the higher education systems of British Columbia and Canada. This study attempted to fill several gaps in the literature on happiness and wellbeing. As yet, researchers are unable to agree upon definitions for happiness and well-being (Gilbert, 2006; Kahneman, 2011). This in itself is an important area of inquiry. Along with this, the perspectives and opinions of lay people, especially those who are not undergraduate psychology students, are largely missing in the literature (Delle-Fave et al., 2011). Gender comparisons have been few and inconclusive (Helliwell & Putnam, 2004). Effects of educational attainment have also varied widely depending on country and levels of education investigated  174     (Helliwell & Putnam, 2004). This study incorporated all of these areas and moved towards filling in these holes. Happiness is often used as an outcome measure of social welfare and public policy (Bergheim, 2007; Dolan & White, 2007; Greve, 2010; Kahneman & Kreuger, 2006). In fact, Helliwell and Putnam (2004) describe human well-being as “the ultimate dependent variable” (p. 1435). These positive measures in psychological, health, and economic research are integral for building better lives and a better society. Internationally, happiness is increasingly being used to measure progress, as in the example of the government of Bhutan, which uses Gross National Happiness (GNH) as its measurement of national progress. Researchers such as Helliwell and Barrington-Leigh (2010) recommend that direct measures of subjective well-being (SWB) be used in making public policy decisions. The findings of the current study will help inform future research on how to measure happiness in terms that are meaningful for people’s daily lives, and to help promote balance and a focus on all parts of life – social, familial, physical, as well as work-related and educational – as a way to promote happiness and well-being.  175     References Argwal, B., Humphries, J., & Robeyns, I. (2003). Exploring the challenges of Amartya Sen’s work and ideas: An introduction. Feminist Economics, 9(2-3), 3-12. Andres, L. (2012). Designing and doing survey research. Toronto, ON: Sage. Andres, L. (2010a). Educational homogamy, and inequality: A twenty-two year intergenerational perspective of Canadian men and women. Paper presented at the Society for Longitudinal and Life Course Studies Inaugural Conference, Clare College, Cambridge University, UK, September 22 -24. Andres, L. (2010b). Paths on Life’s Way: Transitions of British Columbia Young Adults in a Changing Society (Survey). Vancouver, British Columbia: University of British Columbia. Andres, L. (2009). The Dynamics of Post-Secondary Participation and Completion: A Fifteen Year Portrayal of BC Young Adults (Research Results). Vancouver, British Columbia: BC Council on Admissions & Transfer. Andres, L. (2009). The cumulative impact of capital on dispositions across time: A 15 year perspective of young Canadians. In K. Robson & C. Sanders (Eds.), Quantifying theory: Pierre Bourdieu (pp. 75-88). Toronto, ON: Springer. Andres, L. (1993). Paths on Life’s Way: Destinations, determinants, and decisions in the transition from high school. Unpublished doctoral dissertation, University of British Columbia, Canada. Andres, L., & Adamuti-Trache, M. (2008). Life-course transitions, social class, and gender: a 15year perspective of the lived lives of Canadian young adults. Journal of Youth Studies, 11(2), 115-145.  176     Andres, L., & Grayson, P. (2003). Parents, educational attainment, jobs and satisfaction : What’s the connection? A 10-year portrait of Canadian young women and men. Journal of Youth Studies, 6(2), 181-202. Andres, L., & Wyn, J. (2010). The making of a generation: The children of the 1970s in adulthood. Toronto, ON: University of Toronto Press. Becker, G.S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. Chicago, US: University of Chicago Press. Bergheim, S. (2007). The happy variety of capitalism: Characterised by an array of commonalities. Deutsche Bank Research. Retrieved from www.dbresearch.com on September 15, 2010. Bourdieu, P. (1980). The logic of practice. Stanford, CA: Stanford University Press. Box, G.E.P. (1979). Some problems of statistics of everyday life. Journal of the American Statistical Association, 74(365). Bruford, W.H. (1975). The German Tradition of Self-Cultivation: ‘Bildung’ from Humboldt to Thomas Mann. Cambridge, UK: Cambridge University Press. Bruni, L., Comim, F., & Pugno, M. (Eds.). (2008). Capabilities and Happiness. Oxford, UK: Oxford University Press. Retrieved 1 May 2012, from <http://lib.myilibrary.com.ezproxy.library.ubc.ca?ID=192540>. Burnett, S. (2011). The Happiness Agenda: A Modern Obsession. Basingstoke, US: Palgrave Macmillan. Campione, W. (2008). Employed women’s well-being: The global and daily impact of work. Journal of Family and Economic Issues, 29(3), 346-361.  177     Charmaz, K. (2006). Constructing grounded theory: A guide through qualitative analysis. London, UK: Sage. Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. New York, NY: Harper & Row. Delle Fave, A., Brdar, I., Freire, T., Vella-Brodrick, D., & Wissing, M.P. (2011). The eudaimonic and hedonic components of happiness: Qualitative and quantitative findings. Social Indicators Research, 100(1), 185-207. Diener, E. (2008). Myths in the science of happiness, and directions for future research. In M. Eid & R.J. Larsen (Eds.), The science of subjective well-being (pp. 403-514). New York, NY: The Guilford Press. Diener, E., & Biswas-Diener, R. (2002). Will money increase subjective well-being?: A literature review and guide to needed research. Social Indicators Research, 57(2), 119169. Diener, E., & Fujita, F. (1995). Resources, personal strivings, and subjective well-being: A nomothetic and idiographic approach. Journal of Personality and Social Psychology, 68(5), 926-935. Diener, E., & Suh, E. (1997). Measuring quality of life: Economic, social, and subjective indicators. Social Indicators Research, 40, 189-216. Diener, E., Suh, E.M., Lucas, R.E., & Smith, H.L. (1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 125(2), 276-302. Dolan, P., & White, M. P. (2007). How can measures of subjective well-being be used to inform public policy? Perspectives on Psychological Science, 2(1), 71-85.  178     Dolan, P., White, M., & Peasgood, T. (2008). Do we really know what makes us happy? A review of the economic literature on the factors associated with subjective well-being. Journal of Economic Psychology, 29, 94-122. Dunn, E., Aknin, L., & Norton, M. (2008). Spending money on others promotes happiness. Science, 21, 1687-1689. Elster, J.R. (2009). Reason and Rationality. Princeton, NJ: Princeton University Press. Elster, J.R. (2007). Explaining Social Behaviour: More Nuts and Bolts for the Social Sciences. Cambridge, UK: Cambridge University Press. Easterlin, R.A. (2001). Income and happiness: Towards a unified theory. Economic Journal, 111, 465-484. Easterlin, R.A. (1995). Will raising the incomes of all increase the happiness of all? Journal of Economic Behavior and Organization, 27, 35-47. Esping-Andersen, G. (1990). The three worlds of welfare capitalism. Cambridge, UK: Polity Press. Finn, J.D. (1997). Hypothesis testing. In J.P. Keeves (Ed.), Educational research, methodology, and measurement: An international handbook (Second edition) (pp. 556-561). Cambridge, UK: Elsevier Science Ltd. Fox, J. (2008). Applied Regression Analysis and Generalized Linear Models. Thousand Oaks, CA: Sage Publications, Inc. Fox, J., & Weisberg, S. (2011). An R Companion to Applied Regression. Thousand Oaks, CA: Sage Publications, Inc. Gilbert, D. (2006). Stumbling on happiness. Toronto, ON: Vintage Canada.  179     Goodwin, J., & O’Connor, H. (2005). Exploring complex transitions: Looking back at the ‘Golden Age’ of from school to work. Sociology, 39(2), 201-220. Greve, B. (Ed.) (2010). Happiness and social policy in Europe. Cheltenham, UK: Edward Elgar Publishing Limited. Hardy, M.A. (1993). Regression with dummy variables. Newbury Park, CA: Sage. Headey, B., Veenhoven, R., & Wearing, A. (1991). Top-down versus bottom-up theories of subjective well-being. Social Indicators Research, 24, 81-100. Helliwell, J.F. (2003). How’s life? Combining individual and national variables to explain subjective well-being. Economic Modelling, 20, 331-360. Helliwell, J., Layard, R., & Sachs, J. (Eds.). (2012). World Happiness Report. New York, NY: The Earth Institute, Columbia University. Helliwell, J.F., & Putnam, R.D. (2004). The social context of well-being. Philosophical Transactions of the Royal Society of London, 359, 1435-1446. Hill, R. (2004). Happiness in Canada since World War II. Social Indicators Research, 65(1), 109-123. Jaccard, J., & Turrisi, R. (2003). Interaction effects in multiple regression. Second edition. Thousand Oaks, CA: Sage. Kahneman, D. (2011). Thinking, Fast and Slow. Mississauga, ON: Doubleday Canada. Kahneman, D., & Krueger, A. B. (2006). Developments in the measurement of subjective wellbeing. The Journal of Economic Perspectives, 20(1), 3-24. Kahneman, D., Krueger, A.B., Schkade, D., Schwarz, N., & Stone, A.A. (2006). Would you be happier if you were richer? A focusing illusion. CEPS Working Paper, No. 125.  180     Keeves, J.P. (1997). Models and model building. In J.P. Keeves (Ed.), Educational Research, Methodology, and Measurement: An International Handbook (2nd ed.) (pp. 386-393). Cambridge, UK: Elsevier Science Ltd. Keeves, J.P. (1997). Multivariate analysis. In J.P. Keeves (Ed.), Educational Research, Methodology, and Measurement: An International Handbook (2nd ed.) (pp. 403-411). Cambridge, UK: Elsevier Science Ltd. Kim-Prieto, C., Diener, E., Tamir, M., Scollon, C., & Diener, M. (2005). Integrating the diverse definitions of happiness: A time-sequential framework of subjective well-being. Journal of Happiness Studies, 6, 261-300. Krueger, A. B., & Schkade, D. A. (2008). The reliability of subjective well-being measures. Journal of Public Economics , 92(8-9), 1833-1845. Lelkes, O. (2008). Happiness across the life-cycle: Exploring age-specific preferences. Policy Brief, 2. Vienna, Austria: European Centre. Lewis-Beck, M.S. (1980). Applied regression: An introduction. Newbury Park, CA: Sage. Livingstone, D.W. (1999). Exploring the icebergs of adult learning: findings of the first Canadian survey of informal learning practices. The Canadian Journal for the Study of Adult Education, 13(2), 49-65. Marar, Z. (2003). The Happiness Paradox. London, UK: Reaktion Books. McMahon, D.M. (2006). Happiness: A history. New York, NY: Grove Press. McMahon, W.W. (2009). Higher learning, greater good: The private & social benefits of higher education. Baltimore, Maryland: The Johns Hopkins University Press. Menard, S. (2002). Applied logistic regression analysis (2nd ed.). Thousand Oaks, CA: Sage.  181     Nagpal, R., & Sell, H. (1985). Subjective Well-being. New Delhi, India: World Health Organization. Nussbaum, M.C. (2011). Creating capabilities: The human development approach. Cambridge, MA: The Belknap Press of Harvard University Press. Nussbaum, M.C. (2002). Capabilities and social justice. International Studies Review; 4(2), 123137. Nussbaum, M.C. (2000). Women and human development: The capabilities approach. Cambridge, UK: Cambridge University Press. Nussbaum, M., & Sen, A. (Eds.). (1993). The Quality of Life: A Study Prepared for the World Institute for Development Economics Research (WIDER) of the United Nations University. Oxford, UK: Clarendon Press. Peiro, A. (2006). Happiness, satisfaction and socio-economic conditions: Some international evidence. The Journal of Socio-Economics, 35, 348-365. Pett, M.A., Lackey, N.R., & Sullivan, John, J. (2003). Making sense of factor analysis: The use of factor analysis for instrument development in health care research. Thousand Oaks, CA: Sage. Putnam, R. (2000). Bowling alone: The collapse and revival of American community. New York, NY: Simon & Schuster. Raibley, J.R. (2011). Happiness is not well-being. Journal of Happiness Studies (Research Paper), online: DOI 10.1007/s10902-011-9309-z. Robeyns, I. (2006). Three models of education: Rights, capabilities and human capital. Theory and Research in Education, 4(1), 69-84.  182     Robeyns, I. (2005). The capability approach: a theoretical survey. Journal of Human Development, 6(1), 93-117. Robeyns, I. (2003a, September). The capability approach: An interdisciplinary introduction. Paper presented at the 3rd International Conference on the Capability Approach, Pavia, Italy. Robeyns, I. (2003b). Sen’s capability approach and gender inequality: Selecting relevant capabilities. Feminist Economics, 9(2-3), 61-92. Rubenson, K., & Desjardins, R. (2009). The impact of welfare state regimes on barriers to participation in adult education: A bounded agency model. Adult Education Quarterly, 59(3), 187-207. Sandefur, G.D., Eggerling-Boeck, J., & Park, H. (2005). Off to a good start? Postsecondary education and early adult life. In R.A. Settersten, Jr., F.F. Furstenberg, & R.G. Rumbaut (Eds.), On the frontier of adulthood: Theory, research and public policy (pp. 356-395). Chicago, IL: University of Chicago Press. Schimmel, J. (2007). Development as happiness: The subjective perception of happiness and UNDP’s analysis of poverty, wealth and development. Journal of Happiness Studies, 10(1), 93-111. Schoon, I., Ross, A., & Martin, P. (2009). Sequences, patterns, and variations in the assumption of work and family-related roles: Evidence from two British birth cohorts. In I. Schoon & R.K. Silbereisen (Eds.), Transitions from school to work: Globalization, individualization, and patterns of diversity (pp. 219-242). New York, NY: Cambridge University Press.  183     Seligman, M. (2002). Authentic happiness: Using the new Positive Psychology to realize your potential for lasting fulfillment. New York, NY: Free Press. Sen, A. (2009). The idea of justice. Cambridge, MA: The Belknap Press of Harvard University Press. Sen, A. (2008). The economics of happiness and capability. In Bruni, L., Comim, F., & Pugno, M. (Eds.), Capabilities and Happiness (pp. 16-27). Oxford, UK: Oxford University Press. Sen, A. (2005). Human rights and capabilities. Journal of Human Development, 6(2), 151-166. Sen, A. (1999). Development as Freedom. Westminster, MD: Alfred A. Knopf Incorporated. Sen, A. (1993). Capability and well-being. In M. Nussbaum and A. Sen (Eds.), The quality of life (pp. 30-53). Oxford, UK: Clarendon Press. Sen, A. (1985). Well-being, agency and freedom: The Dewey lectures 1984. The Journal of Philosophy, 82(4), 169-221. Spearritt, D. (1997). Factor analysis. In J.P. Keeves (Ed.), Educational research, methodology, and measurement: An international handbook (Second edition) (pp. 528-539). Cambridge, UK: Elsevier Science Ltd. van Praag, B.M.S., & Ferrer-i-Carbonell, A. (2008). Happiness quantified: A satisfaction calculus approach. Oxford, UK: Oxford University Press. van Praag, B.M.S., Frijters, P., & Ferrer-i-Carbonell, A. (2003). The anatomy of subjective wellbeing. Journal of Economic Behavior & Organization, 51, 29-49. Veenhoven, R. (2010). How universal is happiness? In E. Diener, J.F. Helliwell, & D. Kahneman (Eds.), International differences in well-being. New York, NY: Oxford University Press.  184     Veenhoven, R. (2008). Sociological theories of subjective well-being. In M. Eid & R.J. Larsen (Eds.), The science of subjective well-being (pp. 17-43). New York, NY: The Guilford Press. Veenhoven, R. (2004). Happiness as a public policy aim: The greatest happiness principle. In A.P. Linley & S. Joseph (Eds.), Positive Psychology in practice. Hoboken, NJ: John Wiley. Veenhoven, R. (2000). The four qualities of life: Ordering concepts and measures of the good life. Journal of Happiness Studies, 1, 1-39. Waugh, B. (2012, February). Six things science tells us about happiness: UBC economist on a bold UN mission. UBC Reports, 58(2), 10-11. Wilson, E.G. (2008). Against happiness: In praise of melancholy. New York, NY: Farrar, Straus and Giroux. Wilson, W. (1967). Correlates of avowed happiness. Psychological Bulletin, 67(4), 294-306. Yang, Y. (2008). Social inequalities in happiness in the United States, 1972-2004: An ageperiod-cohort analysis. American Sociological Review, 73(2), 204-226.  185     Appendix A: Survey Instrument  186             Class of ‘88   Twenty‐Two Years After High School!       Thank you for agreeing to participate in the Class of ‘88 Twenty‐two Years After High School  questionnaire, a follow‐up to a study in which you have been a participant since 1989.     Your responses to the last four surveys provided vital information about the life transitions of your  generation. Your participation in this follow‐up will help us to continue to learn more about your  educational, work, and other life experiences.    This questionnaire should take about 45 minutes to complete. Please read the instructions for each  question carefully. If a written response is required, please ensure that your answer is easy to read.    This is a voluntary but important survey. All of the information that you provide in this questionnaire  is strictly anonymous. Questionnaires contain identification numbers for statistical purposes only. All  information that would permit identification of the individual will be removed.     You have the right to refuse to participate in this study. It is assumed that completion of this  questionnaire indicates that consent to participate has been given.       Please complete all relevant sections.       Lesley Andres  Professor        Department of Educational Studies  University of British Columbia                             tel  fax  email  web:         (604) 822‐8943  (604) 822‐4244  lesley.andres@ubc.ca  http://www.edst.educ.ubc.ca/paths/paths.htm   187     SECTION A  Note that the time period covered by many of the questions is seven YEARS (September 2003 to March 2010)  1.  HAVE YOU ATTENDED a post-secondary institution at any time since September 2003? (check one)  Yes ..............   1   Please go to SECTION B (next page)  No .................   2   Please go to SECTION C – Work (page 4)  188     SECTION B – Post-Secondary Education  Please note! Since the last survey, many post-secondary institutions have changed their names. Old Name  New Name  Capilano College.......................................... Capilano University University College of the Fraser Valley ........ University of the Fraser Valley Kwantlen University...................................... Kwantlen Polytechnic University Malaspina University College....................... Vancouver Island University Okanagan University College ...................... Okanagan College or University of British Columbia, Okanagan University College of the Cariboo................. Thompson Rivers University or Thompson Rivers University, Open Learning Emily Carr Institute of Art and Design .......... Emily Carr University of Art and Design Institute of Indigenous Government ............. Nicola Valley Institute of Technology (merged)  When reporting the post-secondary institutions that you have attended, use the new name (even if you attended under the old name.)  Please continue to Question 2, next page   189  2.     In any or all of the years since September 2003, what post-secondary institution(s) have you attended? (If you attended more than one type of school, check all that apply. Please include both full-time and part-time attendance and all courses taken, e.g., academic, vocational, career, college prep., adult basic education, upgrading). Sept. 2003 to Aug.2004  Sept. 2004 to Aug. 2005  Sept. 2005 to Aug. 2006  Sept. 2006 to Aug. 2007  Sept. 2007 to Aug. 2008  Sept. 2008 to Aug. 2009  Sept. 2009 March 2010  Community Colleges  Camosun ..................................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 College of the Rockies ........................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Douglas .....................................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 King Edward Campus V.C.C. ...........................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Langara ....................................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 New Caledonia.......................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 North Island .............................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Northwest .................................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Northern Lights ......................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Okanagan ................................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Selkirk ........................................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 V.C.C. City Centre ................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7  Institutes  B.C.I.T. ......................................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Justice Institute ......................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Nicola Valley Institute of Technology..........  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7  Universities Capilano University ..............................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Emily Carr University of Art & Design ...........  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Kwantlen Polytechnic University .....................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Royal Roads ...........................................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Simon Fraser University.....................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Thompson Rivers University ............................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Thompson Rivers University, Open Learning..  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Trinity Western University..................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 University of British Columbia, Vancouver......  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 University of British Columbia, Okanagan ......  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 University of the Fraser Valley ........................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 University of Northern British Columbia .......  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 University of Victoria............................................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Vancouver Island University .............................  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Other  Out of Province university (please specify)___________________ .....  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Out of Province community college (please specify)_____________ .....  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Out of Province university college (please specify)_____________ .....  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Private training institution inside B.C. (please specify)_______________ .....  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Private training institution outside B.C. (please specify)_______________ .....  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7 Other (please specify)______________ .....  1 ...................  2 .................... 3 ...................  4 .................... 5 ...................  6 ...................  7  190  3.     In what type of program or field of study were you enrolled? (Please give full description: e.g., medical and dental technologies, radio and television arts, carpentry, chemical engineering. If you attended more than one program in a given year, mention all that you attended).  4.a.  Sept. 2003 - Aug. 2004  1._________________________  2._________________________  Sept. 2004 - Aug. 2005  1._________________________  2._________________________  Sept. 2005 - Aug. 2006  1._________________________  2._________________________  Sept. 2006 - Aug. 2007  1._________________________  2._________________________  Sept. 2007 – Aug. 2008  1._________________________  2._________________________  Sept. 2008 – Aug. 2009  1._________________________  2._________________________  Sept. 2009 – Mar. 2010  1._________________________  2._________________________  Please describe the degree, diploma, or certificate program(s) from which you have graduated since September 2003 (e.g., Bachelor of Science, Master of Education, Certificate in Real Estate Studies, Diploma in Mining Technology). Please describe all degrees, diplomas, and certificates attained. Degree/Diploma/ Certificate  4.b.  1.______________  2.______________  3.______________  Length of Program (time it took you to complete) 1.______________  2.______________  3.______________  Name of Institution  1.______________  2.______________  3.______________  Year Completed  1.______________  2.______________  3.______________  If you have not graduated from your most recent program of study, when do you anticipate graduating? Month ____________  Year ________  SECTION C – Work 5.  Have you been employed in paid work at any time since September 2003? (check one) No  ........... 0    [If no, please go to Question 34]  Yes........... 1  6.  How many jobs have you held since September 2003? (Include full-time and part-time work) ____________ (total number of jobs)  7.  How many jobs do you currently hold? ____________ (total number of full-time jobs currently held) ____________ (total number of part-time jobs currently held)  191     8.  Please describe the jobs that you have held since September 2003. Start with your most recent job. Job 1. Current or Most Recent Job: Job title: Type of business or organization: Location (e.g., Kamloops) Total number of months employed at this job: Salary: ( $ amount before taxes & deductions ) Hours worked per week: Are(were) you self-employed Why did you leave?  ______________________________________________________ ______________________________________________________ ______________________________________________________ __________ months ___________ years ___________hourly ___________ weekly ___________ monthly _____________ Yes _____ No _____ ______________________________________________________  Job 2. Second Most Recent Job: Job title: Type of business or organization: Location (e.g., Kamloops) Total number of months employed at this job: Salary: ( $ amount before taxes & deductions ) Hours worked per week: Are(were) you self-employed Why did you leave?  ______________________________________________________ ______________________________________________________ ______________________________________________________ __________ months ___________ years ___________hourly ___________ weekly ___________ monthly _____________ Yes _____ No _____ ______________________________________________________  Job 3. Third Most Recent Job: Job title: Type of business or organization: Location (e.g., Kamloops) Total number of months employed at this job: Salary: ( $ amount before taxes & deductions ) Hours worked per week: Are(were) you self-employed Why did you leave?  ______________________________________________________ ______________________________________________________ ______________________________________________________ __________ months ___________ years ___________hourly ___________ weekly ___________ monthly _____________ Yes _____ No _____ ______________________________________________________  Job 4. Fourth Most Recent Job: Job title: Type of business or organization: Location (e.g., Kamloops) Total number of months employed at this job: Salary: ( $ amount before taxes & deductions ) Hours worked per week: Are(were) you self-employed Why did you leave?  ______________________________________________________ ______________________________________________________ ______________________________________________________ __________ months ___________ years ___________hourly ___________ weekly ___________ monthly _____________ Yes _____ No _____ ______________________________________________________  Job 5. Fifth Most Recent Job: Job title: Type of business or organization: Location (e.g., Kamloops) Total number of months employed at this job: Salary: ( $ amount before taxes & deductions ) Hours worked per week:  ______________________________________________________ ______________________________________________________ ______________________________________________________ __________ months ___________ years ___________hourly ___________ weekly ___________ monthly _____________  192    Are(were) you self-employed Why did you leave?  Yes _____ No _____ ______________________________________________________  We would like a few more details about your present or most recent job, as reported in Question 8. (If you have more than one job right now, please describe the one where you work the most hours.)  9.  What does your employer do or make? (What kind of business organization is it?)  ____________________________________________________________________ ____________________________________________________________________ 10.  In total, about how many people work in your business/company at all its locations? (check one) Less than 20 ............................................  1 Between 20 and 99 ..............................  2 Between 100 and 499 ..........................  3 More than 500 people ..........................  4  11.  What is your current status at this job? Are you (check one) an employee without supervisory responsibilities ...........................................................................  0 an employee with limited supervisory or management responsibilities (5 persons or less) ...................................................................................................................................  1 an employee with more extensive supervisory or management responsibilities (more than 5 persons) ............................................................................................................................  2 self-employed without employees .........................................................................................................  3 self-employed with employees ...............................................................................................................  4 homemaker (unpaid) ..................................................................................................................................  5  12.  How did you obtain this job?  ____________________________________________________________________ ____________________________________________________________________ 13.  Is this a temporary job, that is, a job with a specific end date? (check one) No  ...........  0  Yes...........  1  14.  How much longer do you expect you will stay with this job? ______ months  ______ years  193  15.     Do you think it is likely that you will lose your job or be laid off in the next year? (check one) No  ...........  0  Yes...........  1  16.  Does your job require you to regularly work rotating, evening, or night shifts? (check one) No  ...........  0  Yes...........  1  17. a.  Are you presently looking for another job? (check one) No  ...........  0    [If no, go to Question 18.a.]  Yes...........  1  17.b.  What is the main reason you are looking for another job?  ____________________________________________________________________ ____________________________________________________________________ 18.a.  In your current position, do you have an opportunity for promotion? No  ...........  0    [If no, go to Question 19]  Yes...........  1  18.b.  How many promotions have you had since you began working for your present or most recent employer? _________________(number of promotions)  19.  Are you currently job sharing? (Job sharing is when two or more employees share the hours and responsibilities of one job position) No  ...........  0  Yes...........  1  20.  Considering your experience, education, and training, in your current or most recent job do you feel you are: (check one) Underqualified ...........................................  1 Adequately qualified ................................  2 Overqualiified..............................................  3  194     21.  Given your education, training, and experience, do you feel that you are earning in your current or most recent job (check one) More than you deserve?  ...................... 1  About the right amount? ....................... 2 less than you deserve? .........................  3  22.a.  Would you prefer to work fewer or more hours each week, or about the same as now? Fewer hours ....................................  1 More hours ......................................  2 Same hours as now ........................  3  22.b.  Please explain your answer to 22.a. _________________________________________________________________ _________________________________________________________________  23.  Does/did your employer provide you with the following? (check one for each line)  Yes No A pension plan? .............................................................................  1 ..........  0 Medical insurance? .....................................................................  1 ..........  0 A dental plan? ...............................................................................  1 ..........  0 Paid parental leave (over and above UIC)? ......................  1 ..........  0 Child care benefits? ....................................................................  1 ..........  0 Sick leave? .....................................................................................  1 ..........  0 Long term disability? ...................................................................  1 ..........  0 Life insurance? ..............................................................................  1 ..........  0 Leave for personal reasons? ...................................................  1 ..........  0 Retirement planning programs? .............................................  1 ..........  0 Other (specify) ______________________________..................  1 ..........  0  24.  In your current or most recent job, have you received any informal training in the past 12 months? (Informal training refers to training provided by the supervisor or a co-worker, that is required for you to carry out your job.) (check one) No.............  0   [If no, go to Question 26]  Yes...........  1  25.  In total, how many hours of informal training did you receive in the past 12 months? ______________ (number of hours)  195     26.  In your current or most recent job, did you receive any formal training and education from your employer in the last 12 months? (Formal training and education refers to a structured training program provided by an instructor, video, or audio tape, computer, or manual that is designed to develop a worker’s skills and abilities.) (check one) No  ......................................................................  0   [If no, go to Question 30]  Yes, one course.............................................  1 Yes, more than one course .......................  2  27.  In total, approximately how many hours did this training involve? (If the course has not ended, include the number of hours you will be receiving)? ________ (Number of hours)  28.  Was the most recent training you received: (check one) Required by your employer ...............................  1 Required by your supervisor.............................  2 Optional or voluntary ...........................................  3 Specifically requested by you...........................  4 Other ..........................................................................  5  29.  To what extent do you agree that each of the following statements describes the most recent formal training you received: (check one for each line) Extent of Agreement: Strongly disagree  Disagree  Neutral  Agree  Strongly agree  a. I need this training to do my current job..................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 b. This training will help me to be promoted within my current organization. ...............................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 c. This training is helping me meet my career objectives. ...................  1 ...............  2 ............... 3 ...............  4 ...............  5 d. I need additional formal training to do my job effectively .................  1 ...............  2 ............... 3 ...............  4 ...............  5 e. This training will help me to find work elsewhere (e.g., another company or business). ......................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 f. I took this training because it was required, not because I was interested in it. ......................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 g. I received high quality training.  30.  ..................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5  Thinking back over the past 22 years, what would you say are the most useful job-related skills or knowledge that you learned? Please be specific. ____________________________________________________________________________________________________ ____________________________________________________________________________________________________  196     31.  To what extent do you agree that the following describes your present or most recent job? (If you are currently working at more than one job, answer with reference to the one you consider to be your primary job.) (check one for each line) Extent of Agreement: Strongly disagree  Disagree  Neutral  Agree  Strongly agree  a. The pay is good. ...............................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 b. I have the freedom to decide what I do in my job................................  1 ...............  2 ............... 3 ...............  4 ...............  5 c. The fringe benefits are good........................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 d. The job lets me use my skills and abilities .............................................  1 ...............  2 ............... 3 ...............  4 ...............  5 e. The chances for promotion are good .......................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 f. Job security is good ........................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 g. The work is interesting. ..................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 h. The physical surroundings are pleasant. ................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 i. My job gives me a feeling of accomplishment. .....................................  1 ...............  2 ............... 3 ...............  4 ...............  5 j. My work is psychologically stressful. ........................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 k. The job is directly related to my education and training. ..................  1 ...............  2 ............... 3 ...............  4 ...............  5 l. This is the kind of job I expected to have at this stage in my life. .................................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 m. I look forward to coming to work. ...............................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 n. My work is physically stressful ....................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 o. In my job, I have plenty of opportunity to participate in decision making ....................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 p. The physical surroundings of my work place are environmentally safe. .....................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 q. My work is challenging. .................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 r.  My job allows me to balance work and family/personal life. ...........  1 ...............  2 ............... 3 ...............  4 ...............  5  s. My workplace provides day care facilities for my children ..............  1 ...............  2 ............... 3 ...............  4 ...............  5 t.  32.a.  My workplace provides exercise facilities ..............................................  1 ...............  2 ............... 3 ...............  4 ...............  5  If you had the choice to make again would you choose the same line of work you now do? (check one) Yes...........  1 No.............  0  32.b.  Please explain your answer to 32.a.  _______________________________________________________________________ _______________________________________________________________________  197     33.  Do you think you might completely change careers or your line of work in the next 5 years? Yes...........  1 No.............  0  34.   [If no, go to Question 35]  What kind of career or job do you eventually want? Please be as specific as possible.  _______________________________________________________________________ _______________________________________________________________________ 35.  During the last 7 years (September 2003 to the present), were you ever (check one for each line) No  Yes  unemployed when you wanted to be employed........................................................................... 0 ..............  1 unemployed for at least 3 consecutive months ............................................................................ 0 ..............  1 working part-time when you wanted to be working full-time ................................................... 0 ..............  1  36.  During the last 7 years (September 2003 to the present), have you ever received (check one for each line) No  Yes  unemployment insurance benefits .................................................................................................... 0 ..............  1 social insurance or welfare income................................................................................................... 0 ..............  1 child care subsidy (MSSH) ................................................................................................................... 0 ..............  1  37.  Are you currently unemployed (that is, out of work and actively seeking work)? (check one) No ...........  0 Yes...........  1  38.a.  Do you think your unemployment had an effect on your career, either negatively or positively? No  ..............................................................  0  Yes...............................................................  1 I have not been unemployed .............  2  38.b.    [If you have not been unemployed, go to Question 39.a.]  How did unemployment affect your career (either negatively or positively)?  _______________________________________________________________________ _______________________________________________________________________    198  39.a.  Were you in a government-sponsored job creation or training program at any time during the past 7 years (since September 2003)? (check one) No  ......................................................................................  0    [If no, go to Question 40.a.]  Yes, a non-federal training program ......................  1 Yes, a federal training program ...............................  2  39.b.  If yes, how many months in total were you employed in such a program? _________________ (total number of months)  39.c.  What was the full name of the program(s)?  _______________________________________________________________________ _______________________________________________________________________ 40.  Have you ever completed an apprenticeship program? (check one) No  ...................................................................................................................... 0   [If no, go to Question 42]  Yes...................................................................................................................... 1 Currently enrolled, but not yet completed ........................................... 2  41.  In what line of work or trade is your apprenticeship?  _______________________________________________________________________ 42.  In 2009, what was your total household income (respondent and spouse/partner, if applicable) from all sources, before taxes or any deductions? _____________ (estimated total 2009 household income)  43.  Would you say that you are better off, worse off, or just the same financially than you were a year ago? (check one) Better off ..................................  1 Same .......................................  2 Worse off .................................  3  44.  Looking ahead, do you think that a year from now you will be better off, worse off, or just the same financially than you were a year ago? (check one) Better off ..................................  1 Same .......................................  2 Worse off .................................  3  199     45.a.     To what extent has the economic recession that began in 2008 affected you and your family? (check one for each line) Extent of Effect: Strong Negative Effect  Negative Effect  Positive Effect  Strong Positive Effect  Not Applicable  c. My work or career. ........................................................................  1 ..................  2 .......................  3 ....................... 4.....................................  5 a. My personal life..............................................................................  1 ..................  2 .......................  3 ....................... 4.....................................  5 b. My ability to provide the essentials for my family .............  1 ..................  2 .......................  3 ....................... 4.....................................  5 d. My ability to provide “extras” for my family . .......................  1 ..................  2 .......................  3 ....................... 4.....................................  5 e. My personal savings. ...................................................................  1 ..................  2 .......................  3 ....................... 4.....................................  5 f. My retirement savings (e.g., RRSPs) ...........................  1 ..................  2 .......................  3 ....................... 4.....................................  5 g. My children’s educational savings (e.g., RESPs).............  1 ..................  2 .......................  3 ....................... 4.....................................  5  45.b. Please explain your answers to Question 45.a.  __________________________________________________________________________________ __________________________________________________________________________________ __________________________________________________________________________________ __________________________________________________________________________________ 46.  Do you have a Registered Educational Savings Plan (RESP) for your children? No  Yes  Oldest child ..............................  0 ...................  1 Second oldest child..................  0 ...................  1 Third oldest child......................  0 ...................  1 Fourth oldest child ...................  0 ...................  1 Fifth oldest child.......................  0 ...................  1  47.  Do you plan to continue your education or training in any formal way in the future? (check one) Currently completing a program ................................................  1 Yes, within a year.......................................................................................... 2 Yes, in one year’s time ............................................................................... 3 Yes, after two years or more .................................................................... 4 Maybe, within a year .................................................................................... 5 Maybe, in one year’s time.......................................................................... 6 Maybe, after two years or more .............................................................. 7 No, I definitely do not intend to continue my education ................. 8  200     48.  Have you formally applied for or enrolled in any post-secondary institution for the 2010/11 year? (check one) No ............................  0 Yes ...........................  1    Name of Institution ________________________ Name of Program _________________________  49.  In the last two years, have you ever wanted to participate in an education or training program, but did not enrol in a course or program? (check one) No ............................  0 Yes ...........................  1    Type of program _________________________________ Reason for not participating _________________________  50.  With regard to your career (including homemaking), which best indicates your situation since leaving high school? (check one) a. b. c. d. e. g.  I had no planned career when I left high school, and still have none.............................................. 1 I have discarded my original career plan but have not chosen a new career yet....................... 2 I had no planned career when I left high school, but I have now chosen one ............................. 3 I have changed and chosen a new career since high school ............................................................. 4 I have retained the career plans that I had at high school graduation ............................................ 5 Other (please specify) ____________________________ ................................................................ 6  51.a. If you could choose again, would you make the same educational choices? (check one) No.............  0 Yes...........  1  51.b. Please explain your answer to Question 51.a.  ____________________________________________________________________ ____________________________________________________________________ 52.a. Have you ever had a student loan? (Please remember that all information provided on this survey will reported anonymously) (check one) No.............  0   [If no, go to Question 53]  Yes...........  1  52.b.  What is the total amount of student loans you personally accumulated? $_____________ (total student loans received)  201     52.c.  Approximately how much do you still owe for student loans? $____________ (student loan still owing)  53.  In your lifetime, what is the highest level of education that you WANT to achieve? (check one) a. b. c. d. e. f. g. h. i. j.  54.  Secondary school diploma ...............................................................................  1 Apprenticeship, vocational, or trade school ...............................................  2 Some community college, no diploma/certificate ....................................  3 Community college diploma/certificate ........................................................  4 Some university, no degree .............................................................................  5 Completed Bachelors Degree .........................................................................  6 Completed Professional Degree (medicine, law, engineering) .........  7 Completed Masters Degree .............................................................................  8 Completed Doctoral Degree ............................................................................  9 Other ( please specify) ____________________ ...................................  10  Given the realities of today’s educational system and work world, what is the highest level of education that you EXPECT to achieve? (check one) a. b. c. d. e. f. g. h. i. j.  Secondary school diploma ...............................................................................  1 Apprenticeship, vocational, or trade school ...............................................  2 Some community college, no diploma/certificate ....................................  3 Community college diploma/certificate ........................................................  4 Some university, no degree .............................................................................  5 Completed Bachelors Degree .........................................................................  6 Completed Professional Degree (medicine, law, engineering) .........  7 Completed Masters Degree .............................................................................  8 Completed Doctoral Degree ............................................................................  9 Other ( please specify) ____________________ ...................................  10  Continue to the next page   202  55.     Please indicate the extent to which you agree with the following statements about work, education and general well-being. (check one for each line) Extent of Agreement: Strongly disagree  Disagree  Neutral  Agree  Strongly agree  a. I can’t get ahead these days without post-secondary education. .................................  1 ...............  2 ............... 3 ...............  4 ...............  5 b. Canada’s future economic competitiveness is dependent on a highly skilled work force. ...............................................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 c. I have a well established career. ...............................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 d. To attain the lifestyle I want, I must have a university degree. ......................................  1 ...............  2 ............... 3 ...............  4 ...............  5 e. Post-secondary education is getting too expensive for people like me .....................  1 ...............  2 ............... 3 ...............  4 ...............  5 f. To stay gainfully employed in the future, I must be highly skilled in a given field/speciality ..............................................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 g. I have been able to get the post-secondary education and training that I wanted ............................................................................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 h. My education has helped me to be more concerned about social issues in Canada. ...............................................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 i. I believe that I am better off with a post-secondary education. .....................................  1 ...............  2 ............... 3 ...............  4 ...............  5 j. I expect to re-enter the post-secondary system more than once over my lifetime ................................................................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 k. Post-secondary education does not pay off as well as it did 15 years ago. .............  1 ...............  2 ............... 3 ...............  4 ...............  5 l.  My education has made me a well-informed citizen..........................................................  1 ...............  2 ............... 3 ...............  4 ...............  5  m. These days, people require higher levels of education than they did in the past ..  1 ...............  2 ............... 3 ...............  4 ...............  5 n. I need a university degree to earn a decent income..........................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 o. I believe I have the skills and abilities to get what I want out of life .............................  1 ...............  2 ............... 3 ...............  4 ...............  5 p. My education has improved my communication skills ......................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 q. Post-secondary education is not for me .................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 r. My self-respect has improved because of my job ..............................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 s. My education has made me more interested in the perspectives of other cultures ...............................................................................................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 t. My education has improved my career prospects..............................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 u. It is still more difficult for women to succeed in the work force......................................  1 ...............  2 ............... 3 ...............  4 ...............  5 v. It is important that my job be related to my field of study or specialization. .............  1 ...............  2 ............... 3 ...............  4 ...............  5 w. My self-respect has improved because of my education .................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 x. My education has improved my reasoning skills. ...............................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 y. My education has been useful in helping me find a job. ..................................................  1 ...............  2 ............... 3 ...............  4 ...............  5 z. Given the way things are, it will be much harder for people in my generation to live as comfortably as previous generations.............................................  1 ...............  2 ............... 3 ...............  4 ...............  5  203     SECTION D – Your Background and Household  56.  Are you (check one) Female ...............  1 Male.....................  0  57.  What is your birth date?  _______ year  58.  ______ _____ month  day  Who currently lives in your household? (check all that apply) I am living alone.....................................................................  1 My female spouse/partner .................................................  2 My male spouse/partner ....................................................  3 One or more children ...........................................................  4 One or both parents .............................................................  5 Brother or sister .....................................................................  6 In-laws .......................................................................................  7 Roommate or friends ...........................................................  8 Other relatives ........................................................................  9  59.  What is your current marital status? (check one) Single ................................................................................................................................. 1 Living in a marriage-like relationship with a partner .......................................  2 Married .............................................................................................................................  3 Divorced...........................................................................................................................  4 Separated .......................................................................................................................  5 Widowed ..........................................................................................................................  6  60.  Has your marital status (including marriage and marriage-like relationships) changed since September 2003? No.................................  0  [If No, go to Question 62] Yes...............................  1   61.a.  Since September 2003, how many times have you been ____________ legally married?  61.b.  _____________ in a marriage-like relationship?  Since September 2003, in what year(s) were your marriage(s)? 20____  marriage-like relationship(s)? 20____  20____ 20____  20____ 20____  204     61.c.  If you are/were divorced after September 2003, in what year(s) were you divorced? 20____ 20____  62.  How old is your current spouse/partner?   [If Not applicable, go to Question 65]  _________ (age in years)  63.a.  What does your spouse/partner do (e.g., high school English teacher, pharmacist, sales clerk, assembly line worker, homemaker)?  ____________________________________________________________________________________ 63.b.  More specifically, for what kind of business or industry does your spouse/partner work (e.g., retail shoe store, sawmill, provincial government agency)? ____________________________________________________________________________________  64.  What is the highest level of education that your spouse/partner completed? (check one only) a. b. c. d. e. f. g. h. i. j. k.  65.  Less than a high school diploma....................................................................  1 Secondary school diploma ...............................................................................  2 Apprenticeship, vocational, or trade school ...............................................  3 Some community college, no diploma/certificate ....................................  4 Community college diploma/certificate ........................................................  5 Some university, no degree .............................................................................  6 Completed Bachelors Degree .........................................................................  7 Completed Professional Degree (medicine, law, engineering) .........  8 Completed Masters Degree .............................................................................  9 Completed Doctoral Degree ............................................................................  10 Other ( please specify) ____________________ ...................................  11  Do you consider yourself to be heterosexual...............................................  1 gay..............................................................  2 lesbian ........................................................  3 bisexual ......................................................  4 other (specify)____________________ ....  5  205     66.  Do you have children?  No.................................  1   [If No, go to Question 68]  Yes...............................  2  67.  When were your children born? (please include all of your children) Most recent child Second most recent child Third most recent child Fourth most recent child Fifth most recent child  68.  ______ month ______ month ______ month ______ month ______ month  ______ year ______ year ______ year ______ year ______ year  If you do not have children, do you think you might begin starting a family within the next 3 years? No............................................................................................  1 Maybe ....................................................................................  2 Yes..........................................................................................  3  69.  In your household, who usually does the following? (check one for each line)  You  Your spouse/ partner  Shared equally with spouse/ partner  Someone else  Not applicable  a. Cooks meals .......................................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 b. Cleans up the kitchen......................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 c. Grocery shopping .............................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 d. House cleaning ..................................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 e. Automobile maintenance ...............................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 f. Household repairs/maintenance .................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 g. Laundry .................................................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 h. Looks after household finances ..................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 i. Small repairs .......................................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 j. Makes important family decisions ..............................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 k. Stays at home with a sick child ...................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 l. Finds a babysitter .............................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 m. Arranges for child care....................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 m. Takes the children to appointments (e.g., medical appointments)................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 n. Caregiver for my aging or ill parents .........................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 o. Caregiver for my spouse/partner’s aging or ill parents ...........................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 p. “Chauffeurs” the child(ren) to various activities (e.g., sport practices, school, birthday parties) ....  1 ....................... 2 .......................  3 ....................... 4 .......................  5  206  70.  When choosing a spouse or partner, to what extent do you believe it is important that both people share the following qualities? (check one for each line)     Extent of Importance: Not at all important  Not very important  Neutral  Somewhat important  Very important  a. Similar educational background ......................................................  1 ......................  2 .......................  3 ......................  4 .......................  5 b. Similar moral values ............................................................................  1 ......................  2 .......................  3 ......................  4 .......................  5 c. Similar political views ..........................................................................  1 ......................  2 .......................  3 ......................  4 .......................  5 d. Similar ethnic background .................................................................  1 ......................  2 .......................  3 ......................  4 .......................  5 e. Same racial group ................................................................................  1 ......................  2 .......................  3 ......................  4 .......................  5 f. Similar attitudes toward work and leisure....................................  1 ......................  2 .......................  3 ......................  4 .......................  5 g. Similar religion........................................................................................  1 ......................  2 .......................  3 ......................  4 .......................  5 h. Similar sense of humour ....................................................................  1 ......................  2 .......................  3 ......................  4 .......................  5 i. Similar social class (e.g., economic background/income) ....  1 ......................  2 .......................  3 ......................  4 .......................  5 j.  71.  Similar views about parenting .............................................  1 ......................  2 .......................  3 ......................  4 .......................  5  We would like information about all your places of residence since September 2003. Please fill in each row of information for each community in which you have resided. Start with the community in which you are currently living. Each row you fill in should correspond to the year in which you moved to that community. In cases where you had more than one place of residence within the same year, please list all locations under a given year. Community Name  e.g., Prince George  Province/ Country  Length of Residence (years/months)  e.g., B.C.  e.g., 8 months  Reason for leaving this location e.g., moved to a new job  Current (as of March 2010) 2009 2008 2007 2006 2005 2004 2003 (from September onward)  72.  What are your reasons for living in your current community?  207    _______________________________________________________________________________________________ _______________________________________________________________________________________________ _______________________________________________________________________________________________  73.  If you could choose, where would you most like to live today? [Be sure to name the community, if possible (e.g., Prince George) and include the type of community, (e.g., rural, urban/rural, metropolitan)] _______________________________________________________________________________________________ _______________________________________________________________________________________________  74.  If you could choose, where would you most like to live in 5 years? (Be sure to name the community, if possible [(e.g., Prince George) and include the type of community, (e.g., rural, urban/rural, metropolitan)] _______________________________________________________________________________________________ _______________________________________________________________________________________________  75.  Since September 2003, have you returned to live with your parents/guardians? (check one) No  ........... 0   [If no, go to Question 78.a., next page]  Yes........... 1  76.a.  In what year since September 2003 did you last return to live there? Year: ______  76.b.  Why did you return to live there? _______________________________________________________________________________________________ _______________________________________________________________________________________________  77.a.  Are you still living with your parents/guardians? (Check one) No .........  0   [If no, go to Question 78.a., next page]  Yes.........  1  77.b.  If yes, why have you made the decision to continue living with your parents/guardians? _______________________________________________________________________________________________ _______________________________________________________________________________________________  208     78.a.  Since September 2003, have one or more of parents/guardians or parents-in-law lived with you? (check one) No .........  0   [If no, go to Question 79.a.]  Yes.........  1  78.b.  If yes, why do/did your parents/guardians or parents-in-law live with you? _______________________________________________________________________________________________ _______________________________________________________________________________________________  79.a.  Since September 2003, have you been a first time home buyer? (check one) No  ...........  0  Yes...........  1  79.b.   [If no, go to Question 80]  [If yes, go to Question 79.b.]  In what year did you buy this home? Year _________  80.  If you have ever owned your own home, did you receive any financial assistance from your parents or other relatives specifically for purchasing your home? No ........................  0 Yes........................  1 Not Applicable ......  2  81.a.  Do you own a personal computer? (check one) No .........  0   [If no, go to Section E- Health and Well-being, Question 82]  Yes.........  1  81.b.  On average, how many hours per week do you normally use this computer at home? _____________(total hours per week)  81.c.  Do your children have their own computers? (check one only) I do not have children .......................................................................................................................................  0 No, my child/children does/do not have a computer designated for their use only ..........................................  1 Yes, I have one child and s/he has a computer designated for her/his use only..............................................  2 Yes, I have more than one child and they have one computer designated for their use only ..........................  3 Yes, I have more than one child and they have more than one computer designated for their use only........  4  209     81.d.  Do you have internet access in your home? No .........  0 Yes.........  1  Please continue to Section E.  SECTION E – Health and Well-being  82.  On a scale of 1 to 10, in general how happy would you say you are with your life? (circle one) Very unhappy  Very happy  1.................. 2 ..................3 ..................4 ..................5 ................. 6.................. 7.................. 8..................9 .................10  83.  On a scale of 1 to 10, how would you describe your life? (circle one) Very dull  Very exciting  1.................. 2 ..................3 ..................4 ..................5 ................. 6.................. 7.................. 8..................9 .................10  84.  On a scale of 1 to 10, how would you describe the extent to which your life is stressful? (circle one) Not at all stressful  Very stressful  1.................. 2 ..................3 ..................4 ..................5 ................. 6.................. 7.................. 8..................9 .................10  85.  How often do you participate in sports or engage in regular exercise? Not at all.........................................  1 Once a week..................................  2 Two to three times a week.............  3 Four to five times a week...............  4 More than five times a week ..........  5  210     86.  When you have problems, to what extent do you rely on the following people? Extent of Reliance: Not at all  A little  Sometimes  Very much  Not applicable  a. Your mother ........................................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 b. Your father ...........................................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 c. Your parents-in-law or equivalent...............................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 d. Your grandparents............................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 e. Your children.......................................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 f. Your brothers/sisters .......................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 g. Your spouse/partner ........................................................  1 ....................... 2 .......................  3 ....................... 4 .......................  5 h. Your girlfriend/boyfriend .................................................  1 ....................... 2 .......................  3 ....................... 4 ..............