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Relationships between the socio-economic characteristics of farmers in British Columbia and their contacts… Akinbode, Isaac Adefolu 1969

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THE RELATIONSHIPS BETWEEN THE SOCIO-ECONOMIC CHARACTERISTICS OF FARMERS IN BRITISH COLUMBIA AND THEIR CONTACTS WITH DISTRICT AGRICULTURISTS by ISAAC ADEFOLU AKLNBODE B. S c , University of I f e , Nigeria; 1966 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE i n AGRICULTURAL EXTENSION in the Department of A g r i c u l t u r a l Economics We accept t h i s thesi^as^conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA APRIL, 1969 In p r e s e n t i n g t h i s t h e s i s i n p a r t i a l f u l f i l m e n t o f t h e r e q u i r e m e n t s f o r an a d v a n c e d d e g r e e a t the U n i v e r s i t y o f B r i t i s h C o l u m b i a , I a g r e e t h a t t h e L i b r a r y s h a l l make i t f r e e l y a v a i l a b l e f o r r e f e r e n c e and S t u d y . I f u r t h e r a g r e e t h a t p e r m i s s i o n f o r e x t e n s i v e c o p y i n g o f t h i s t h e s i s f o r s c h o l a r l y p u r p o s e s may be g r a n t e d by the Head o f my Department o r by h i s r e p r e s e n t a t i v e s . It i s u n d e r s t o o d t h a t c o p y i n g o r p u b l i c a t i o n o f t h i s t h e s i s f o r f i n a n c i a l g a i n s h a l l n o t be a l l o w e d w i t h o u t my w r i t t e n p e r m i s s i o n . D e p a r t m e n t o f Agricultural Economics The U n i v e r s i t y o f B r i t i s h C o l u m b i a V a n c o u v e r 8, Canada Date April 11 , 1969 i i ABSTRACT The purpose of the study was to measure the communication between farmers and the A g r i c u l t u r a l Extension Service i n B r i t i s h Columbia by analyzing the nature and number of contacts, as well as the r e l a t i o n s h i p of such contacts to the socio-economic c h a r a c t e r i s t i c s of farm operators. Two hypotheses were tested to asc e r t a i n whether there were any s t a t i s t i c a l l y s i g n i f i c a n t differences i n the l e v e l and kind of contact with D i s t r i c t A g r i c u l t u r i s t s among farmers of varying socio-economic c h a r a c t e r i s t i c s . The a n a l y t i c a l survey method was used, and the data were c o l l e c t e d by personal interviews with 256 farm household heads. The areas studied included Peace River, Northern T i e r , North Thompson and Salmon Arm i n r u r a l B r i t i s h Columbia. In general, the respondents had s i m i l a r c h a r a c t e r i s t i c s to farm operators i n other r u r a l areas i n the province. The respondents had a median of eight years of schooling, median net farm income of $2,000 to $2,999, and about one h a l f of them had no off-farm jobs. Contacts between the respondents and the D i s t r i c t A g r i c u l t u r i s t were mainly through impersonal rather than personal sources of information, and the respondents reached by the two types of contact were not the same. The number of respondents who had personal contacts v a r i e d from 16 to 35 per cent, while the number obtaining information through the impersonal sources va r i e d from 81 to 93 per cent, depending on the type of contact. The farmers had an average of 3.71 d i f f e r e n t types of contact during the year 1966. These included an average of 1*05 personal $nd 2.66 impersonal contacts. Farmers with higher i i i socio-economic status reported more contacts thsn did lower status farmers. More personal contacts v/ith tho D i s t r i c t A g r i c u l t u r i s t were reported by fencers with more education. There were s t a t i s t i c a l l y s i g n i f i c a n t d i f f e r e n c e s between the users of £ll extension contacts and non-users, with respect to t h i r t e e n socio-economic c h a r a c t e r i s t i c s Four c h a r a c t e r i s t i c s , including years of school completed, distance t r a v e l l e d f or goods and cervices»social p a r t i c i p a t i o n and amount of gross farm income, accounted for 34 per cent of the v a r i a n t ! i n the use of a l l types of extension contact combined. Between 13 and 27 per cent of the v a r i a t i o n i n each i n d i v i d u a l type of contact was accounted f o r by d i f f e r i n g combinations of socio-economic c h a r a c t e r i s t i c s . ACKNOWLEDGMENTS I wish to express my warmest thanks to the Government of Canada, not only f o r the Commonwealth Scholarship award which enabled me to undertake t h i s study, but also f o r the f r i e n d l y and c o r d i a l r e l a t i o n s h i p s which the s t a f f of the Canadian International Development Agency (previously External Aid O f f i c e ) , Ottawa, extended to me so f r e e l y during my stay i n Canada. The study was c a r r i e d out under the supervision of Professor Coolie Verner and I am very appreciative of h i s advice and encouragement. I am also g r e a t l y indebted to Dr. M.J. Dorling, who served as my thes i s chairman, and who also made many invaluable suggestions on the analysis of the data. I also thank Doctors John A. Niemi, A. J . Renney and George R. Winter, who gl a d l y served as members of the thes i s committee and made many invaluable suggestions on the writing of the t h e s i s . I am g r a t e f u l to Messrs. A.G. Fowler and Ron H a l l , of the University of B r i t i s h Columbia Computing Centre, f o r t h e i r help with the computer a n a l y s i s . I acknowledge my debt to the Nigerian Federal Governments, for allowing me to take advantage of the Commonwealth award. And f i n a l l y , my deep gratitude goes to my wife, C h r i s t i e , f o r her patience i n typing the many dr a f t s of the th e s i s , and f o r her encouragement; I also acknowledge my gratitude to our chi l d r e n , 'Bayo and 'Bambo, for t h e i r perseverance throughout the period of the study. The debt which I owe to each and everyone of these i n d i v i d u a l s i s i n c a l c u l a b l e . - v -TABLE OF CONTENTS Page Abstract i i Acknowledgments iv List of Tables v List of Figures xiv CHAPTER I. INTRODUCTION 1 Purpose of the Study 1 Hypotheses 2 Definition of Terms 2 Agricultural Extension in British Columbia 3 The Study Setting 5 Procedure 8 Plan of the Study 14 II. REVIEW OF LITERATURE 16 The Roles of the Agricultural Extension Service 16 Problems of Contact with Extension Service 18 Previous Studies on Extension Contact 20 Factors Influencing Contact with Extension Service 22 The Concept of Socio-economic Status 24 III. CHARACTERISTICS OF THE SAMPLE 27 Personal Characteristics 27 Educational Characteristics 33 - v i CHAPTER Page III. Social Characteristics 42 Economic Characteristics 48 Summary 64 "IV. FARMERS' CONTACT WITH DISTRICT AGRICULTURISTS 65 Knowledge of District Agriculturist 65 Extension Contact Score 66 Type and Extent of Contacts 68 Summary 75 V. FACTORS ASSOCIATED WITH FARMERS' CONTACT WITH DISTRICT AGRICULTURIST 76 Differences Among Farmers at the Three Contact Levels 77 The District Agriculturist's Clientele 86 Prediction of Contact by Multiple Regression Methods 101 Summary 104 VI. SUMMARY AND CONCLUSIONS 107 Summary 107 Conclusions 113 BIBLIOGRAPHY 115 - v i i -Page APPENDIX I. The Interview Schedule with Univariate Frequency Distributions Added for Basic Socio-economic Characteristics and Frequency of Extension Contacts 122 APPENDIX II. Bivariate Tables of the Socio-economic Characteristics versus Contact Levels and Contact Methods for which Significant Chi-square values were obtained 144 APPENDIX III. Animal Unit 161 APPENDIX IV. Comparison of the Results of Simple and Spearman RHO Correlation Coefficients 163 APPENDIX V. Tests of Goodness of F i t for Normal Distribution 170 - v i i i -LIST OF TABLES TABLE I. I I . I I I . IV. V. VI. VII. V I I I . IX. X. Percentage D i s t r i b u t i o n of Farm and Non-farm Respondents by D i s t r i c t s Simple C o r r e l a t i o n C o e f f i c i e n t s Spearman Rank C o r r e l a t i o n C o e f f i c i e n t s Percentage D i s t r i b u t i o n D f Respondents by Kind of Further Training Desired Percentage D i s t r i b u t i o n of Respondents by Future Changes i n Farm Operations Contemplated Percentage D i s t r i b u t i o n of Respondents by Extension Contact Scores Percentage D i s t r i b u t i o n of Respondents by Contact Levels Percentage D i s t r i b u t i o n of Average Extension Contact Score by Personal and Impersonal Contacts Percentage D i s t r i b u t i o n of Farmer-D i s t r i c t A g r i c u l t u r i s t Contact by Type of Contact Percentage D i s t r i b u t i o n of Respondents by Personal Contacts with D i s t r i c t A g r i c u l t u r i s t 10 28 29 43 63 67 68 69 71 72 - ix -Page TABLE XI. XII. XIII. XIV. XV. XVI. XVII. XVIII. Percentage Distribution of Respondents by use of Impersonal Contacts with District Agriculturist 74 Chi-square Values for Distributions by Socio-economic Characteristics Among Respondents in Extension Contact Levels 78 Chi-square Values for Distributions by Socio-economic Characteristics Among Respondents in Personal Contact Levels 82 Chi-square Values for Distributions by Socio-economic Characteristics Among Respondents in Impersonal Contact Levels 84 Chi-square Values for Distributions by Socio-economic Characteristics Among Users and Non-users of Extension Contact Methods 87 Percentage of Variation in Contact Explained and the Socio-economic Factors Accounting for the Variation 102 Percentage Distribution of Years of School Completed by Contact Levels 145 Percentage Distribution of Adult Education Participation by Contact Levels 145 - x -Page TABLE XIX. XX. XXI. XXII. XXIII. XXIV. XXV. XXVI. XXVII. XXVIII. Percentage Distribution of Number of Improved Acres by Contact Levels Percentage Distribution of Gross Farm Income by Contact Levels Percentage Distribution of Adult Education Participation by Personal Contact Levels Percentage Distribution of Number of Improved Acres by Personal Contact Levels Percentage Distribution of Gross Farm Income by Personal Contact Levels Percentage Distribution of Adult Education Participation by Impersonal Contact Levels Percentage Distribution of Number of Improved Acres by Impersonal Contact Levels Percentage Distribution of Gross Farm Income by Impersonal Contact Levels Percentage Distribution of Years of School Completed by Knowledge of District Agriculturist Percentage Distribution of Adult Education Participation by Knowledge of District Agriculturist 146 146 147 147 148 148 149 149 150 150 - x i -Page TABLE XXIX. XXX. XXXI. XXXII. XXXIII. XXXIV. XXXV. XXXVI. Percentage Distribution of Number of Improved Acres by Knowledge of District Agriculturist 151 Percentage Distribution of Gross Farm Income by Knowledge of District Agriculturist 151 Percentage Distribution of Years of School Completed by V i s i t to District Agriculturist's Office 152 Percentage Distribution of Adult Education Participation by V i s i t to District Agriculturist's Office 152 Percentage Distribution of Number of Improved Acres by V i s i t to District Agriculturist's Office 153 Percentage Distribution of Gross Farm Income by V i s i t to District Agriculturist's Office 153 Percentage Distribution of Adult Education Participation by Telephone Calls to District Agriculturist 154 Percentage Distribution of Number of Improved Acres by Telephone Calls to District Agriculturist 154 x i i Page TABLE XXXVII, XXXVIII. XXXIX. XL. XLI. XLII. XLIII. XLIV. Percentage Distribution of Gross Farm Income by Telephone Calls to District Agriculturist Percentage Distribution of Adult Education Participation by Farm Vi s i t s by District Agriculturist Percentage Distribution of Number of Improved Acres by Farm Visits by District Agriculturist Percentage Distribution of Gross Farm Income by Farm Visits by District Agriculturist Percentage Distribution of Years of School Completed by Attendance at Agricultural Meetings and Field Days Percentage Distribution of Adult Education Participation by Attendance at Agricultural Meetings and Field Days Percentage Distribution of Number of Improved Acres by Attendance at Agricultural Meetings and Field Days Percentage Distribution of Gross Farm Income by Attendance at Agricultural Meetings and Field Days 155 155 156 156 157 157 158 158 - x i i i -TABLE XLV. Page XLVI. XLVII. XLVIII. XLIX. Percentage D i s t r i b u t i o n of Number of Improved Acres by Respondents' Use of Mails from the D i s t r i c t A g r i c u l t u r i s t as a Source of A g r i c u l t u r a l Information Percentage D i s t r i b u t i o n of Gross Farm Income by Respondents' Use of Mails from D i s t r i c t A g r i c u l t u r i s t as a Source of A g r i c u l t u r a l Information Percentage D i s t r i b u t i o n of Number of Improved Acres by Respondents* Use of Farm Newspaper A r t i c l e s as a Source of A g r i c u l t u r a l Information Percentage D i s t r i b u t i o n of Gross Farm Income by Respondents' Use of Farm Newspaper A r t i c l e s as a Source of A g r i c u l t u r a l Information Comparison of the Results of Simple and Spearman RHO C o r r e l a t i o n C o e f f i c i e n t s 159 159 160 160 164 - x i v -LIST OF FIGURES FIGURE Page 1 Organizational Chart of B r i t i s h Columbia Department of Agri c u l t u r e 4 2 The Study Areas 6 CHAPTER 1 INTRODUCTION Ag r i c u l t u r e today i s experiencing an accelerated rate of change as a r e s u l t of new a g r i c u l t u r a l technology. A g r i c u l t u r a l innovations have no value unless they get to farmers who have need f o r them, but farm people have l i t t l e d i r e c t contact with a g r i c u l t u r a l 1 s c i e n t i s t s . The Agriculturr.l Extension Service which serves as a l i n k between the laboratory and the farmer i s one of the p r i n c i p a l 2 channels of disseminating new technology from s c i e n t i s t s to farmers. Consequently, the nature of the r e l a t i o n s h i p between extension workers and farm operators i s c r u c i a l i n the d i f f u s i o n and adoption of a g r i c u l t u r a l innovations* I I . PURPOSE 07 THE STUDY The purpose of t h i s study i s to measure the degree of communica-t i o n between farmers and the A g r i c u l t u r a l Extension Service i n B r i t i s h Colum': i a by analyzing the nature and extent of contacts, as well as the r e l a t i o n s h i p of such contacts to the socio-economic c h a r a c t e r i s t i c s of farm operators. The s p e c i f i c purposes are (1) to determine the extent and types of contacts which farmers have with the D i s t r i c t A g r i c u l t u r i s t s (D.A.) i n selected communities i n B r i t i s h Columbia (B.C.); (2) :o determine the socio-economic c h a r a c t e r i s t i c s of farmers at .different j 1 Everett M. Rogers and Harold R. Capener, The County Extension Agent, and His Constituents. Wooster, Ohio A g r i c u l t u r a l Experiment Station Research B u l l e t i n 858, June 1960, p. 4. 2 The A g r i c u l t u r a l Extension Service c a r r i e s out i t s extension work through the a g r i c u l t u r a l extension agents. For pore d e t a i l s or. the r o l e s of extension agents, see Claude H. Job, "A Study of the Roles of Selected A g r i c u l t u r a l Extension Agents i n B r i t i s h Columbia", (unpublished M.S.A. Thesis, Department of A g r i c u l t u r a l Bionomics, University of B r i t i s h Columbia, Vancouver, 1965), pp. "-16 and 28-71* 2 contact l e v e l s ; and (3) to measure the degree of association between d i f f e r e n t contact l e v e l s and the socio-economic c h a r a c t e r i s t i c s of farmers. I I I . HYPOTHESES 3 The following two hypotheses are tested: 1, There are no s i g n i f i c a n t differences i n the l e v e l of contact with D i s t r i c t A g r i c u l t u r i s t s among farmers of d i f f e r i n g socio-economic status. 2. There are no s i g n i f i c a n t differences i n the kind of contacts with D i s t r i c t A g r i c u l t u r i s t s among farmers of d i f f e r i n g socio-economic status. IV. DEFINITION OF TERMS In t h i s study, c e r t a i n terms are used which require s p e c i f i c d e f i n i t i o n . Thus, f o r the purpose of t h i s study the following terms are used: 1. Socio-economic status r e f e r s to the p o s i t i o n assigned to an i n d i v i d u a l respondent on the basis of how much he possesses • of personal, educational, s o c i a l and economic c h a r a c t e r i s t i c s studied. This status r e f e r s to a l l or some of the c h a r a c t e r i s t i c s at any one time. Socio-economic l e v e l i s used interchangeably with socio-economic status. They both mean the same thing. 2. Socio-economic c h a r a c t e r i s t i c s or factors r e f e r to the personal, educational, s o c i a l and economic indices used i n t h i s atudy to measure the socio-economic status or l e v e l of the sample. 3 The hypotheses w i l l be phrased i n the n u l l form f o r s t a t i s t i c a l t e s t i n g where appropriate* - 3 -V. AGRICULTURAL EXTENSION IN BRITISH COLUMBIA The r e l a t i o n s h i p between a g r i c u l t u r a l extension and the farmer may be a r e f l e c t i o n of the organizational pattern developed to conduct extension work; therefore, i t i s appropriate to discuss the organization of a g r i c u l t u r a l extension i n B.C. The present organiza-t i o n a l pattern was established i n 1964*, (Figure 1) whereby, extension work i s performed by c e r t a i n branches of the P r o v i n c i a l Department of A g r i c u l t u r e , but only as ah adjunct to the several r o l e s performed by each branch. The H o r t i c u l t u r a l Branch does extension work with farmers producing f r u i t s , vegetables and ornamentals. The F i e l d Crops Branch, i n addition to performing advisory work r e l a t i n g to the production of such crops as cereals, pastures, hay and potatoes, c a r r i e s out s o i l analysis and experiments on the s u i t a b i l i t y of weedicides and commercial f e r t i l i z e r s . The Dairy Branch i s p r i m a r i l y concerned with the enforcement of the Milk Industry Act, including the sampling and t e s t i n g of milk and the issuance of licences to dairy operators. The Poultry Branch o f f e r s extension service to poultry producers.^ The Livestock Branch engages i n the promotion and supervision of the l i v e s t o c k industry, and provides veterinary services a f f e c t i n g disease c o n t r o l r e g u l a t i o n s ^ i t also supervises stock brands, inspects d a i r y and f u r farm p r a c t i c e s , and licensed abattoirs too small to q u a l i f y under f e d e r a l inspection 4 Claude H. Job, op. c i t . , p. 3. 5 Ibid, p. 4 FIGURE 1 ORGANIZATIONAL CHART OF BRITISH COLUMBIA DEPARTMENT OF AGRICULTURE* I n s t i t u t i o n a l Farms Ministe r I Deputy Minister). Markets & S t a t i s t i c s Branch Farm Economics Div. L Development and Extension Branch Director Supervising A g r i c u l -t u r i s t s D i s t r i c t A g r i c u l t u r i s t Service & Assistants <s-H Clubs D i v i s i o n /.gric. Engineering Land Clearing Div.  Ho r t i c u l t u r e Branch Prov. H o r t i c u l t u r i s t Supervising H o r t i -c u l t u r i s t s D i s t r i c t H o r t i c u l -t u r i s t s Ass't. D i s t . H o r t i -c u l t u r i s t s Special H o r t i c u l -t u r i s t s General] O f f i c e j F i e l d Crops Branch Dairy Branch I Plant Pathology ! Branch | S o i l Survey j Branch i ' — Farmers' I n s t i -tutes Crop Insurance i Entomology Branch . 1 , Apiary Inspection Branch j ARDA Accounts Branch j 2. Livestock Branch Commissioner Veterinary Inspectors Brand Inspectors DHIA Fieldman Animal Pathologist * Source: - modified from Canada's A g r i c u l t u r a l Extension Services, p. 76. s e r v i c e s . The Administrative Branch i s responsible f o r the general d i r e c t i o n of a g r i c u l t u r a l p o l i c i e s , the administration of l e g i s l a -t i o n a f f e c t i n g a g r i c u l t u r e , and the compilation of reports and p u b l i c a t i o n s . This branch also maintains d i r e c t supervision over other branches of the Department of Agriculture.'' Extension work i s a secondary a c t i v i t y f o r these branches, so that any educational work that they might do i s i n c i d e n t a l to t h e i r primary function. Furthermore, the p o l i c i n g function which the f i e l d worker i n these branches must perform i s undoubtedly a b a r r i e r to educational a c t i v i t i e s . The Development and Extension Branch i s the only one i n the Department whose function i s s o l e l y educational, i n that i t i s responsible f o r extension work of a general nature, including a l l types of crops and l i v e s t o c k , 4-H clubs and land development. This branch o f f e r s general information services to farmers through i t s 17 d i s t r i c t a g r i c u l t u r i s t s and 2 associate d i s t r i c t a g r i c u l t u r i s t s . ' VI. THE STUDY SETTING This study was conducted i n four r u r a l communities of B r i t i s h Columbia, namely: Peace River, Northern T i e r , North Thompson and Salmon Arm, a l l of which are representative of r u r a l B r i t i s h Columbia. (Figure 2). There i s a wide v a r i e t y of land-forms i n r u r a l B.C. varying from rugged mountains to low p l a i n s , with most of the area i n mountains. The temperature range i s wide and unpredictable. Broadly speaking, however, the summers are short 6 Dominion Bureau of S t a t i s t i c s , Canada Year Book: 1965. Ottawa, Queen's P r i n t e r , 1965, p. 460. 7 I b i d . - 6 -FIGURE 2 THE STUDY AREAS - 7 -but reasonably warm and the winters are long and c o l d . Annual t o t a l p r e c i p i t a t i o n ( r a i n and snow) are uniform on the p l a i n s . Rural B.C. has a d i v e r s i f i e d economy. At one time a g r i c u l t u r e was the main-stay of the economy but t h i s s i t u a t i o n has now changed. Today the economy i s much broader, involving both the primary and manufacturing phases of a g r i c u l t u r e , f o r e s t r y , mining and a v a r i e t y of secondary and t e r t i a r y service i n dustries such as transporation, 8 t o u r i s t - c a t e r i n g , and r e t a i l and wholesale trades. The t o t a l population of B.C. i n 1966 was 1,873,674 with 9 a r u r a l population of 463,181. Though the r e l a t i v e proportion of r u r a l to t o t a l population of the province has declined within the l a s t two and a h a l f decades, from 46 per cent i n 1941 to 25 per cent i n 1966, there has been an increase i n the population c l a s s i f i e d as r u r a l . The t o t a l population of B r i t i s h Columbia i n 1941 was 817,861 with a r u r a l population of 374,467. 1 0 Rural amenities vary considerably depending upon the distance from farm to trade centres. Paved roads, e l e c t r i c power and telephone services are generally well d i s t r i b u t e d to the r u r a l population w i t h i n close proximity of larger places, but as distance increases the a v a i l a b i l i t y of these amenities becomes l e s s . Other r u r a l amenities, including p u b l i c h o s p i t a l services, a g r i c u l t u r a l services and schools, follow the same pattern of d i s t r i b u t i o n . * * 8 Province of B r i t i s h Columbia,Department of Lands, Forestry and Water Resources, V i c t o r i a , B u l l e t i n Area Nos. 6, 7. 8 and 10. 1966, pp. 18-28, 17-25, 21-33, and 21-29 r e s p e c t i v e l y . 9 Dominion Bureau of S t a t i s t i c s , Census of Canada 1966..Advance  B u l l e t i n A-4, Ottawa, Queen's P r i n t e r , 1967, p. 2. 10 Dominion Bureau of S t a t i s t i c s , Eiphth Census of Canada: 1941, V o l . I I , Table 37, Ottawa, Queen's P r i n t e r , p. 548. 11 B r i t i s h Columbia Department of Lands, Forests and Water Resources, B u l l e t i n s , o£ c i t . . pp. 31; 28; 37-38; and 33 r e s p e c t i v e l y . - 8 -VII. PROCEDURE Source of Data This study i s part of a l a r g e r a n a l y t i c a l socio-economic survey conducted under the Canadian Land Inventory i n B r i t i s h Columbia. The Canadian Land Inventory i s a study of r u r a l land and the socio-economic survey i s a study of the people on that land. Accordingly, the basis f o r sampling was the land rather than the people, even though the data were c o l l e c t e d from people about themselves. This approach to sampling d i f f e r e d from that u s u a l l y encountered i n socio-economic studies of r u r a l areas, where the normal basis f o r sampling i s e i t h e r the population or the households. The r u r a l land area of B r i t i s h Columbia i s e i t h e r held i n t r u s t by the crown or pre-empted by p r i v a t e owners. Pre-empted land i s that land which has been transferred to pr i v a t e ownership through sale by government or through homesteading. Corporations, such as lumbering or pulpwood companies, may acquire pre-empted land i n the same way as p r i v a t e i n d i v i d u a l s . Pre-empted p l o t s of land may range i n si z e from r e s i d e n t i a l l o t s to ranches, farms or tree farms, and the land p l o t s may or may not contain residences or be owner-occupied." The Sample Pre-empted land p l o t s are numbered; the ownership i s recorded i n the P r o v i n c i a l Land O f f i c e and each numbered p l o t i s i d e n t i f i e d p r e c i s e l y on p r o v i n c i a l land maps, so that the number and l o c a t i o n of pre-empted p l o t s i n an area can be determined. 12 Coolie Verner, Planning and Conducting a Survey. A Case Study. Ottawa: Rural Development Branch, Department of Forestry and R u r r l Development, October, 1967, p. 8. - 9 -On the appropriate land maps f o r each survey d i s t r i c t the pre-empted pl o t s were re-numbered, and using a standard table of random numbers a ten per cent sample was drawn of the pre-empted r u r a l p l o t s i n the areas studied. A t o t a l of 640 household heads were interviewed i n the r u r a l areas included i n t h i s study. Of t h i s number, 265 (41.4 per cent) were c l a s s i f i e d as farmers and 375 (58.6 per cent) as nonfarmers (Table 1). The d i s t r i b u t i o n among the areas studied i s shown i n Table 1. This study i s concerned only with the farm household heads. A chi-square value of 34.65 obtained i s s i g n i f i c a n t at the .001 l e v e l , i n d i c a t i n g that there were differences between the respondents by farm end non-farm categories. The Interview Schedule The interview schedule used i n t h i s study i s found i n Appendix i . This schedule recorded pertinent socio-economic data about respondents, as well as s p e c i a l information r e l a t e d to the extent and type of contacts with the l o c a l D i s t r i c t A g r i c u l t u r i s t s . The schedule was used f i r s t i n the Prince George Sp e c i a l Sales Area i n the summer of 1966, and was subsequently r e v i s e d . The revised schedule was used i n t h i s study and the interviews conducted during the summer of 1966 served as a pre-test f o r the schedule. Interviews were conducted from May 7 to August 5, 1967. Each interview required from twenty to f o r t y minutes, and the majority were completed on the f i r s t c a l l . In a few instances, a second v i s i t was required to complete the interview. The completed schedules were checked i n the f i e l d i n case re-interviewing was necessary. 13 M.G. Kendall and S.B.. Babington, Tables of Random Sampling  NumbersT London, Cambridge U n i v e r s i t y Press, 1951, pp. 2-60. - 10 TABLE 1 PERCENTAGE DISTRIBUTION OF FARM AND NON-FARM RESPONDENTS BY DISTRICTS Tot a l Farm Non- farm D i s t r i c t s No. % No. % No. % Peace River 201 31.4 113 56.2 88 43.8 Northern T i e r 217 33.9 65 30.0 152 70.0 North Thompson 101 15.8 32 31.7 69 68.3 Salmon Arm 121 18.9 55 45.5 66 54.5 To t a l 640 100 265 41.4 375 58.6 X 2 - 34.65: d„f. = 3: p <.001, c = .35 - i i -Analysis of the Data The o r i g i n a l survey included both farm and non-farm r u r a l r e s idents. Hence, f o r the purposes of the present study those c l a s s i f i e d as farmers were extracted. The following c r i t e r i a were set f o r s e l e c t i n g the respondents included i n the analysis: 1. Respondents must be engaged i n farming at the time of the study. This ensured that the respondents were interviewed on a l l the relevant questions on the schedule. 2. Respondents must provide a l l the information asked on the schedule, since the program used f o r regression analysis does not allow for missing data. This ruled out respondents who d i d not provide c e r t a i n information as was the case with income i n some instances. The 256 respondents who s a t i s f i e d the f i r s t c r i t e r i o n were included i n the simple frequency d i s t r i b u t i o n and chi-square analyses. On the basis of the second c r i t e r i o n , the 222 respondents who f u l f i l l e d t h i s condition were included i n the c o r r e l a t i o n and regression analyses. The data were transferred to punch cards f o r machine processing a f t e r the schedules had been coded. A f t e r punching, the data processing was done on an IBM 7044 i n the Computing Centre at the Un i v e r s i t y of B r i t i s h Columbia. To t e s t f o r r e l a t i o n s h i p s between the contact with D.A. and the socio-economic c h a r a c t e r i s t i c s which presumably influence the contact, three types of analyses were used. A simple c o r r e l a t i o n analysis was used to examine the o v e r a l l r e l a t i o n s h i p between contact with the D.A. and the socio-economic c h a r a c t e r i s t i c s of the farmers. - 12 -The chi-square analysis was used to test the hypothesis that two d i s c r e t e v a r i a b l e s are independent i n the population from which the sample was drawn. The contigency c o e f f i c i e n t was c a l c u l a t e d f o r the s i g n i f i c a n t chi-square values obtained i n order to determine the degree of ass o c i a t i o n between the va r i a b l e s under i n v e s t i g a t i o n . The Spearman rank c o r r e l a t i o n c o e f f i c i e n t ^ was used to check the r e s u l t s obtained from the simple c o r r e l a t i o n a n a l y s i s . This method i s adapted f o r determining the c o r r e l a t i o n between p a i r s of c h a r a c t e r i s t i c s of the objects or i n d i v i d u a l s being studied, when the i n d i v i d u a l s are ranked accordins to a c r i t e r i o n of measurement of the c h a r a c t e r i s t i c s under i n v e s t i g a t i o n . Another advantage of the Spearman rank c o r r e l a t i o n i s that no assumptions whatsoever need be made about the d i s t r i b u t i o n s of the underlying population, as i s the case with simple c o r r e l a t i o n , which assumes that the population has a b i v a r i a t e normal d i s t r i b u t i o n . The formula used to determine the 2 rank c o r r e l a t i o n c o e f f i c i e n t R, i s : R = 1 - 6 j L d _ _ N(N*-1), where R » the rank c o r r e l a t i o n c o e f f i c i e n t d = the di f f e r e n c e between a p a i r of ranks N • the number of p a i r s of ranks In order to help resolve the problem of r e l i a b i l i t y between the r e s u l t s of the two c o r r e l a t i o n analyses, t e s t s of goodness of f i t f o r normal d i s t r i b u t i o n were c a r r i e d out f o r a p a i r of v a r i a b l e s selected a b i t r a r i l y . These were age and number of years farming. 14 This program was obtained from S o c i a l Sciences S t a t i s t i c a l Centre, Vancouver, U n i v e r s i t y of B r i t i s h Columbia. - 13 -Contact with the D i s t r i c t A g r i c u l t u r i s t i s probably influenced by numerous v a r i a b l e s , and the r e a l r e l a t i o n s h i p between contact and each independent v a r i a b l e may be obscured by the e f f e c t of the other v a r i a b l e s . The stepwise regression analysis was used to overcome t h i s problem. This s t a t i s t i c a l analysis was made by using T r i p multiple regression program-^ (Triangular Regression Package). This program handles several independent v a r i a b l e s . It determines t h e i r r e l a t i o n s h i p s with each of the dependent v a r i a b l e s and eliminates those which give l i t t l e explanation. The independent v a r i a b l e s are entered one at a time into the regression equation i n order of decreasing c o n t r i b u t i o n to the reduction of variance of the dependent v a r i a b l e under consideration. S p e c i f i c a l l y , at each step the following operations are c a r r i e d out. (1) The independent v a r i a b l e s already included i n the regression are tested f o r s i g n i f i c a n c e . If any are found to have dropped below the s i g n i f i c a n c e l e v e l designated (.05 l e v e l of s i g n i f i c a n c e ) , the le a s t s i g n i f i c a n t i s eliminated from the regression by reversing tho corresponding in v e r s i o n steps; (2) I f no v a r i a b l e needs be eliminated, the designated independent v a r i a b l e s not yet included i n the regression are tested f o r si g n i f i c a n c e of the contr i b u t i o n each would make i f included next. I f any are above the s i g n i f i c a n c e l e v e l designated, the most s i g n i f i c a n t i s included i n the regression by an appropriate inversion step. 15 J.H.R. Dempster, A.E. Gagne and R. Hogan, T r i p ; Triangular Regression Package. Vancouver, Computing Centre, U n i v e r s i t y of B r i t i s h Columbia, A p r i l , 1965, pp. 5-6. 14 -(3) The modified regression equation resulting from either step (1) or step (2) is printed. Output includes the regression coefficients, their standard errors, F ratios and F probabilities, together with the name of each variable as i t i s brought i n . (4) If neither of steps (1) and (2) calls for action, the process is terminated. The f i n a l regression equation should now contain just those independent variables (selected from the ones included in the analysis) which contribute significantly to the variance, of the dependent v a r i a b l e . 1 6 The tests of significance for regression coefficients are based on the ratio between the Y variance explained by the X i n question and the residual variance of Y after inclusion of X. Thus, significance tests for regression coefficients were carried out using the null hypothesis,^ « 0, at a .05 level of significance. The tests were based on the magnitude of F ratios. Thus, i f an F ratio was high, which consequently led to low F probabilities (which should be lower than .05) then the null hypothesis was rejected and p accepted as greater than ssro. The coefficient of determination, r*, was determined to show the proportion of variation in extension contacts accounted for by the socio-economic characteristics which showed association. VIII. PLAN OF THE STUDY Before analysing the relationships existing between the socio-economic characteristics of farm operators and their contacts with District Agriculturist i i t was necessary to examine the social 16 Ibid. - 15 -and economic factors which describe the farmers Included i n the study* Chapter I I I presents the socio-economic c h a r a c t e r i s t i c s of the sample and lays the ground-work f o r the examination of how these c h a r a c t e r i s t i c s influence the contacts made with D i s t r i c t A g r i c u l t u r i s t s * Chapter IV analyses the contact methods used by the sample and the frequency of use of each method* The p r i n c i p a l focus of the t h e s i s i s i n Chapter V, which analyses the r e l a t i o n s h i p e x i s t i n g between the socio-economic c h a r a c t e r i s t i c s of the sample and contacts with D i s t r i c t A g r i c u l t u r i s t s . It also examines the c h a r a c t e r i s t i c s of farmers who use contact media, as well as the c h a r a c t e r i s t i c s of the farmers at d i f f e r e n t contact l e v e l s . The f i n a l chapter summarises the findings of the study and draws some conclusions. CHAPTER II REVIEW OF LITERATURE In order to understand the theoretical setting in which the relationships between the Agricultural Extension Service and farm operators are being analyzed, i t is necessary to examine the roles of the Agricultural Extension Service, problems of contact with farmers and: the results of previous extension contact studies. I. THE ROLES OF THE AGRICULTURAL EXTENSION SERVICE The Agricultural Extension Service i s a public organization and i t s effectiveness depends upon the extent to which i t i s able to f u l f i l l i t s roles. Like many other public organizations, the objectives of the Extension Service are found in many o f f i c i a l documents.. Mellor* identified three roles of the Agricultural Extension Service. First, i t must stimulate a framework of farmer attitudes and aspirations conducive to acceptance of technological change. This role constitutes the most important function of 'the Service in the early stages of agricultural development... The second role is to disseminate to farmers the results of production-increasing research and to carry farmers' problems back to research organizations In order to perform each of these communication functions, extension programs must be closely tied to research organizations in such a manner that clear communication i n both directions is possible. The third function, which Mellor identified, was that the Agricultural Extension Service should provide training and guidance to farmers 1 John W. Mellor, The Economics of Agricultural Development. Ithaca, New York, Cornell University Press, 1966, pp. 356-358. - 17 -i n decisionmaking, since good farm management involves the acceptance of appropriate innovations, and perhaps more importantly, the r e j e c t i o n of i n a p p l i c a b l e and unprofitable innovations. The Cooperative Extension Service i s the o f f i c i a l educational agency of the United States Department of A g r i c u l t u r e and the extra-mural educational agency for each state college of a g r i c u l t u r e and home economics. As Coleman observed: I t s purpose i s to 'extend knowledge', p r i m a r i l y to people not reached through the schools and colleges, and to provide a continuing program to follow and supplement t r a i n i n g i n the regular school system. Extension t r i e s to t r a n s l a t e t e c h n i c a l information and research findings into everyday language and to get the information into the hands of the ordinary c i t i z e n s who can use i t . 2 Some writ e r s have emphasized that both r u r a l farm and non-farm people should be reached by extension work. . In recent times, some have advocated that the A g r i c u l t u r a l Extension Service should serve a l l people, regardless of place of residence or occupation. This a t t i t u d e i s an i n d i c a t i o n of the changing r o l e of extension s e r v i c e . 3 Fenley and Williams , writing on the organization of extension service i n Western Nige r i a , pointed out that the fundamental objective of extension was to r a i s e the l e v e l of l i v i n g and income of the farming population. Kelsey and Heame4 viewed the ultimate objective towards which extension work was being d i r e c t e d as more f r u i t f u l l i v e s and b e t t e r l i v i n g f o r a l l people. Siemens and Weir, 2 Lee Coleman, " D i f f e r e n t i a l Contact with Extension Work i n a New York Rural Community", Rural Sociology. 16: 1951, pp. 207-216. 3 John Fenley and S.K. Taiwo Williams, Background f o r Extension Workers  i n Western Nigeria. Ibadan, MANR Extension T r a i n i n g B u l l e t i n No. 3, Nigeria, February 1964, p. 9. 4 L i n c o l n D. Kelsey and Cannon C. Hearne, Cooperative Extension Work. Ithaca, New York, Comstock Publishing Associates, 1963, p. 124. - 18 -i d e n t i f y i n g one of the widely stated objectives of extension i n Canada, noted: Extension that does not have for i t s ultimate purpose the b u i l d i n g and growth of r u r a l men, women and youth has not caught the s p i r i t of extension but i s dealing with i t s bones. A l l extension work aims at changing the outlook towards t h e i r problems of people i n r u r a l areas. Its main r o l e i s to teach r u r a l people how to r a i s e t h e i r standard of l i v i n g by t h e i r own e f f o r t s , using t h e i r own resources of manpower and materials, with educational assistance from the government. Coleman^ stated: "Whether or not a l l r u r a l people are to be served, i t seems c l e a r that the intended c l i e n t e l e i s at l e a s t as broad as a l l farm people". This statement implies that the o f f i c i a l instruments which establistfd the A g r i c u l t u r a l Extension Service intended i t to serve a l l farm people, regardless of t h e i r s o c i a l and economic status. I I . PROBLEMS OF CONTACT WITH EXTENSION SERVICE The problem faced by the extension worker i n reaching h i s c l i e n t e l e i s not an easy one-. The extension worker, as an adult educator, i s attempting to influence the behavior of large numbers of people i n l i f e s i t u a t i o n s , which are subject to continual change, as the r e s u l t of economic and s o c i a l developments. Farm operators have diverse i n t e r e s t s and vary g r e a t l y i n education, t r a i n i n g , age,cultural background, l e v e l of l i v i n g and other socio-economic c h a r a c t e r i s t i c s . These c h a r a c t e r i s t i c s influence t h e i r response to educational s t i m u l i * 5 L.B. Siemens and J.R. Weir,"The R e s p o n s i b i l i t i e s of the U n i v e r s i t i e s , " Proceedings of the Canadian Society of Rural Extension. June. 1961, January, 1962, pp. 70-79. 6 Lee Coleman, op_. c i t . p. 208. - 19 -Id e a l l y , the A g r i c u l t u r a l Extension Service should have ei t h e r equal contact with a l l members of i t s constituency, or e l s e , more contact with those constituents who have the greatest need f o r educational assistance. Rogers and Capener^ noted that the people making the most use of a g r i c u l t u r a l extension are a c t u a l l y those segments of the r u r a l population which have the l e a s t need f o r educational assistance. Kurd** stated that a g r i c u l t u r a l extension had f o r the most part f a i l e d to reach the people who most needed help. Various reasons have been suggested to explain t h i s d i f f e r e n t i a l contact. Some a t t r i b u t e i t to the voluntary nature of 9 the educational service provided by extension. This a t t i t u d e implies that the Extension Service can only involve those who desire and seek help through i t s programs. Others have associated the phenomenon with a high c l i e n t e l e - a g e n t r a t i o . 1 0 A few others f e l t that because of the heterogeneous nature of extension c l i e n t e l e and the l i m i t s to i t s resources, i t was d i f f i c u l t f o r the Extension Service to give the type of a t t e n t i o n needed i n a l l cases. It had to choose those farmers to whom i t devoted most of i t s a t t e n t i o n . 1 1 7 Everett M. Rogers and Harold R. Capener, op_. c i t . p. 5. 8 Lome Hurd, "What Farmers Expect of Extension", Proceedings of the  Canadian Society of Rural Extension. S i x t h Annual Meeting and Convention, November, 1965, p. 10. 9 I b i d . 10 Province of B r i t i s h Columbia, Department of A g r i c u l t u r e , V i c t o r i a , A g r i c u l t u r a l Outlook Conference; 1966. Report of Proceedings, pp. 184-185 and Meredith C. Wilson, How and to What Extent i s the Extension  Service Reaching Low-Income Families. Extension Service C i r c u l a r 375, Washington, United States Department of A g r i c u l t u r e , December, 1941, p. 13 11 Claude H. Job, op_. c i t . . p. 115. - 20 -In recent years these views have been changing, and many are beginning to f e e l that the A g r i c u l t u r a l Extension Service should reach a l l segments of the r u r a l farm population. Hurd noted: ARDA, i f i t means anything, means that these reasons for not reaching the people who need help the most are no longer v a l i d . ARDA i s designed i n large part to provide the means to a s s i s t the provinces i n working i n an i n t e n s i f i e d way to overcome the problems of the people that, up t i l l now, the a g r i c u l t u r a l extension program has f a i l e d to reach.12 I I I . PREVIOUS STUDIES ON EXTENSION CONTACT Most of the extension contact studies that have been made were done i n the United States. A few studies i n B.C. have made reference to extension contact*^ in passing. Verner and M i l l e r d , *^and Verner and Gubbels,*-' i n t h e i r recent studies of the adoption of 12 Lome Hurd, op_. c i t . , p. 10 13 Claude H. Job, o£. c i t . , Paul B. Keeslng, "A Study of P r o v i n c i a l A g r i c u l t u r a l Extension Services i n Canada", (unpublished M.S.A. th e s i s , Department of A g r i c u l t u r a l Economics, U.B.C. 1965), pp. 159-162, and Coolie Verner, Frank W. M i l l e r d and Gary Dickinson, A Socio-economic Survey of the Prince George Special  Sales Area. Vancouver, Faculty of Education, U n i v e r s i t y of B r i t i s h Columbia, August, 1967, pp. 60-62. 14 Coolie Verner and Frank W. M i l l e r d , Adult Education and the  Adoption of Innovations. Rural S o c i o l o g i c a l Monograph # 1, * Vancouver, Department of A g r i c u l t u r a l Economics, U n i v e r s i t y of B.C., 1966, pp. 43-47. 15 Coolie Verner and Peter M. Gubbels, The Adoption or Rejection o f  Innovations by Dairy Farm Operators i n the Lower Fraser V a l l e y . P u b l i c a t i o n No. 11, Ottawa, A g r i c u l t u r a l Economic Research Council of Canada, 1967, pp. 53-54. - 21 -innovations i n B.C., reported contacts between the farmers and the a g r i c u l t u r a l extension agents i n r e l a t i o n to the adoption of innovations. In assessing extension contacts, researchers i n Canada and the United States used three classes of contacts: i n d i v i d u a l , group, and mass media. Rogers and Capener categorized contacts into "personal" and "impersonal" methods. 1 6 They defined personal contacts as those that " e n t a i l a face-to-face communication with the county extension agent", while impersonal contacts include reading or l i s t e n i n g to mass media communications. 1'' Both Rogers and Havens,! 8 a n < j Verner and M i l l e r d , 1 9 adopted t h i s two-contact-methods c l a s s i f i c a t i o n system. Some other investigators were content with looking at the contact methods i n terms of sources of a g r i c u l t u r a l 20 information, without categorizing them. Slocum* and others l i s t e d eighteen such sources. The concepts of personal and impersonal contacts were used f o r analysis i n t h i s study. 16 Everett M. Rogers and Harold R. Capener, op. c i t . . p. 10 17 Ibid. 18 Everett M. Rogers and A. Eugene Havens, Extension Contact of  Ohio Farm Housewives. Research B u l l e t i n 890, Wooster, Ohio A g r i c u l t u r a l Experiment Station, November, 1961, p. 4. 19 Coolie Verner and Frank W. M i l l e r d , op_. c i t . , p. 43. 20 Walter L. Slocum, Owen L. Brough J r . , and Murray A. Straus, Extension Contacts.Selected C h a r a c t e r i s t i c s . P r a c t i c e s and  attitudes of Washington Farm Families. A g r i c u l t u r a l Experiment Station B u l l e t i n 584, Washington,Institute of A g r i c u l t u r a l Sciences State College of Washington, A p r i l , 1958, p. 16. - 22 -IV. FACTORS INFLUENCING CONTACT WITH EXTENSION SERVICE 21 Wilkening developed the hypothesis that farmers of higher socio-economic status tend to u t i l i z e the formally organized sources of information, while those of lower socio-economic status tend to u t i l i z e to a larger extent those sources which are i n c i d e n t a l to the everyday contacts of the farmers. Consequently, those of lower status are more l i k e l y to obtain t h e i r information from neighbours, r e l a t i v e s , dealers and other persons with whom they have personal contact. Those of higher status, on the other hand, are more l i k e l y to u t i l i z e extension agencies and farm magazines as sources of information. "Reasons f o r t h i s a s s o c i a t i o n between status and sources of information u t i l i z e d " , 22 Wilkening explained, "probably l i e i n the r e l a t i o n s h i p of socio-economic status with other f a c t o r s " . Those of higher socio-economic status, f o r example, have the means as well as the desire f o r contacts with the formalized sources of information. The informal or i n d i r e c t type of contact, such as friends and neighbours, was not considered i n the present study. Lionberger, i n h i s attempt to explain the reason f o r the d i f f e r e n t i a l contacts with p o t e n t i a l sources of farm and home information, 21 E. A. Wilkening,"Sources of Information f or Improved Farm Practices", Rural Sociology. 15: 1950, pp. 19-30. 22 I b i d . - 23 -stated: Diffusion of information from college to farmer via the personal contact route is subject to the limitations of class and clique-imposed associational patterns. Mass communication media, on the other hand, are l i t t l e influenced by such factors. It i s , there-fore, possible that part of the isolation experienced by the low income farmers is a function of social distances which restrict free and spontaneous association and which causes the sorcalled " l i t t l e farmer" to feel that he has l i t t l e in common with his "big farmer" neighbors.23 Wilson, 2^ in his own study of the effectiveness of the agricultural extension program, pointed out that previous studies showed that owner families were reached by extension more often than tenant families (an advantage of 4 percentage points for the owner group); families on large farms participated more than those on small farms (an advantage of 11 percentage points in favor of those on large farms); and farmers with high school education were reached more often,(by 10 percentage points). Job 2^ reported a difference of 27 contact scores between the high and the low income farmers in favor of the former. High extension contact had also been reported by many r investigators to be associated with (1) the location of the farm (farms on all-weather roads having higher contact scores than those located on roads occasionally damaged by rain or bad weather); (2) length of residence in the same community (established residents being reached more frequently than newcomers); (3) land use class (farmers operating better land use class being reached more often); and (4) social participation (active participants being reached more frequently 23 H.F. Lionberger, Low-income Farmers in Missouri, Their Contacts with  Potential Sources of Farm and Home Information. Columbia, Missouri Agricultural Experiment Station Research Bulletin 441, 1949, p. 31. 24 Meredith C. Wilson, op_. c i t . p. 12 25 Job, op_. c i t . , Table XXX, p. 116.. than i n a c t i v e p a r t i c i p a n t s . ) 5 ' Parish^* also reported that beef f producers with non-rural background, or those who had spent some time i n non-rural occupations, had the highest extension contact score. V. THE CONCEPT OF SOCIO-ECONOMIC STATUS There i s a high degree of consensus i n the d e f i n i t i o n of "socio-economic status" used by s o c i a l s c i e n t i s t s . Chapin was the f i r s t to propose the d e f i n i t i o n now accepted i n h i s measurement of s o c i a l status. He defined socio-economic status as follows: The p o s i t i o n that a family occupies with reference to the p r e v a i l i n g average standards, of c u l t u r a l possessions, e f f e c t i v e income, material possessions, and p a r t i c i p a t i o n i n the group a c t i v i t i e s of the community.3° Thereafter, many other workers have accepted and u t i l i z e d t h i s d e f i n i t i o n i n various studies.3!>32,33 chapin's d e f i n i t i o n , however 26 Rogers and Capener, op. c i t . pp. 14-26 27 Walter L. Slocum, Owen L. Brough and Murray A. Straus, op. c i t . pp. 27-28. 28 L o i s Scantland, C.A. Svinth and M.J. Taves, A Square Look at Extension  Work i n Spokane County, Pullman, Washington.Agricultural Experiment Station, I n s t i t u t e of A g r i c u l t u r a l Sciences, State College of Washington, Extension B u l l e t i n No. 463, June 1952, pp. 54-59. 29 Ross Parish, "Extension Services and the Grazier on the South-west Slope", Review of Marketing and A g r i c u l t u r a l Economics. New South Wales, D i v i s i o n of Marketing and A g r i c u l t u r a l Economics, Department of A g r i c u l t u r e , 24: March 1956, pp. 223-235. 30 F. Stuart Chapin, "A Quantitative Scale f o r Rating the Home and S o c i a l Environment of Middle Class Families i n an Urban Community: A F i r s t Approximation of the Measurement of Socio-Economic Status", The Journal of Educational Psychology. 19: 1928, pp. 99-111. 31 W.H. Sewell, The Construction and Standardization of a Scale f o r the  Measurement of the Socio-Economic Status of Oklahoma Farm Families, S t i l l w a t e r , Oklahoma A g r i c u l t u r a l and Mechanical College Tech. B u l l . No. 9, 1940, pp. 14-15. 32 Hazel I n g e r s o l l and L.H. Scott, "A Group Scale f o r the Measurement of S o c i a l , C u l t u r a l and Economic Status of Farm Families of the Middle West", Rural Sociology. 9: 1944, pp. 349-363. 33 K-.L. Cannon, "The Relationships of S o c i a l Acceptance to Socioeconomic Status and Residence among High School Students", Rural Sociology, 22: 1957, pp. 142-148. - 25 -suggests that socio-economic status is a .complex concept composed of several distinct but interrelated aspects, a l l of which work together consistently to determine the status level of the family. A variety of indices has been used by many investigators to measure socio-economic status, but education, income and occupation occurred most frequently and were widely used by most students of this problem.^ Harris and Staab, in their study of the relationship of current net income to the socio-economic status of the southern farm families, remarked: Sociologists have recognized that income is one of the important factors in determining socio-economic status and that i t is also associated with other factors such as material possessions, cultural possessions and community participation, which are included in the d i f i n i t i o n of socio-economic status.35 Nam and Powers, reporting with a similar conception, stated that socio-economic status score was a simple average of occupation, education and family income scores. It is quite obvious that these three items are related. In this study, the education and income levels of the farmers constitute important variables. Other indices used in previous studies to determine socio-economic status included s i z e of farm.,' non-farm work experience, 34 Ellen S. Bryant, Socioeconomic Status Indexes for Mississippi  Counties, Mississippi State University Agricultural Experiment Station Bulletin 724, April 1966, pp.' 1-14. 35 Mary Jordan Harris and Josephine Staab, "The Relationship of Current Net Income to the Socio-economic Status of Southern Farm Families", Rural Sociology, 16: 1951, pp. 353-358. 36 Charles B. Nam and Mary G. Power, "Variations in Socio-economic Structure by Race, Residence, and the Life Cycle", American  Sociological Review. 1965, pp. 97-103. - 26 -participation in farm organizations, level of l i v i n g index and age.^ S t i l l other indices included farm land tenure, residential area, religion, ethnic groupings, leadership in organization and 38 39 opinions on matters as indicators of the socio-economic level. ' 37 E.A. Wilkening and Ralph K. Huitt, " P o l i t i c a l Participation Among Farmers as Related to Socio-economic Status and Perception of the P o l i t i c a l Process7', Rural Sociology. 26: 1961, pp. 395-408. 38 Edgar A. Schuler, "Social and Economic Status in a Louisiana H i l l s Community ", Rural Sociology. 5: 1940, pp. 69-87. 39 Ronald Freedman, Pascal K. Whlpton and John W. Smit, "Socio-economic Factors in Religious Differentials in F e r t i l i t y " , American Sociological ReyjLfiH, 26: 1961, pp. 608-614. 40 E.A. Wilkening, Joan Tully and Hartley Prasser, "Communication and Acceptance of Recommended Farm Practices Among Dairy Farmers of Northern Victoria", Rural Sociology, 27: 1962, pp. 116-197. CHAPTER III CHARACTERISTICS OF THE SAMPLE The socio-economic characteristics studied were grouped into personal* educational, social and economic characteristics. The factors in each of these categories were analysed by deriving the number and the corresponding percentage frequency distribution,* and by measuring the association between pairs of characteristics through the use of correlation analyses (Tables II and III)* I. PERSONAL CHARACTERISTICS Age The age distribution'of the sample was skewed toward the upper age groups. Only 12 per cent of the respondents were below 35 years of age, while about three-tenths (29 per cent) were over 55; Some 30 per c«nt of the sample were in the 35 to 44 age group, with another 29 per cent in the 45 to 54 age bracket. Forty-two per cent of the respondents were below 45 years of age and 58 per cent were above that age. The median was in the 45 to 54 age group. There were s t a t i s t i c a l l y significant correlation coefficients obtained between age and a number of socio-economic characteristics including education of the father (r = -*18), number of years in agriculture (r = .40), job satisfaction (r = -.18), desire for further education or training (r = -.36) and the number of weeks for which the respondents worked off farm during the year preceding this study (r = -.23 ). The above associations indicate that the 1 The interview schedule contained in Appendix I gives the frequency distribution for each characteristic. TADLE [I SIMPLE CORRELATION COEFFICIENTS Variables 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 1. Age 1.00 2. Years of school completed -.12 1.00 3. Wife's Education -.10 .23 1.00 4. Adult Education Participation -.09 .28 . 17 1.00 5. Number of Children .07 -.02 .29 .03 1.00 6. Father's Education -.18 .24 . 18 .10 .08 1.00 7. Length of Residence in the area .01 -.07 -.12 -.03 - . 10 .02 1.00 8. Distance travelled for services -.02 -.10 -.07 -.14 -.03 -.21 -.09 1.00 9. Level of Living .01 .30 .38 . 18 .02 . 13 .00 -.28 1.00 10. Social Participation -.11 .25 .17 .26 .01 .06 .12 -.10 .30 1.00 11. Attitudes to Change -.06 .00 .07 .00 . 18 . 10 -.05 -.15 .11 .09 1.00 12. Number of years farming .40 .00 -.12 -.05 -.09 -.06 .04 -.09 .06 .10 -.03 1.00 13. Months worked in 1966 -.11 . 12 . 11 .21 -.02 . 10 -.11 .00 .09 . 15 . 17 .01 1.00 14. Degree of involvement in farming . 17 .12 -.08 .02 - . 11 .01 .07 - . 14 . 14 . 17 - . 14 .54 .03 1.00 15. Job Satisfaction . 18 .02 .05 .02 -.06 .01 .06 -.11 . 12 .06 -.01 .23 .00 .31 1.00 16. Net Farm Income -.09 .24 . 18 .04 . 17 .01 .02 -.01 . 19 .16 .05 -.05 .03 - . 17 -.05 1.00 17. Desire for further education/training -.36 . 19 .08 .04 -.05 .11 .01 .02 .08 .07 . 17 -.18 .18 .06 - . 16 -.02 1.00 18. Number of total acres .01 .29 . 12 .02 .06 .02 -.03 .07 .12 .25 .06 . 14 .05 .15 .03 .39 -.02 1.00 19. Number of improved acres .07 .17 .00 .01 .06 -.04 . 10 .00 .13 . 18 -.04 . 16 .00 . 16 .04 .47 .00 .62 1.00 20. Approximate Gross Farm Income -.00 .22 .19 .09 .07 .10 .07 -.13 .28 .31 .07 .21 . 13 .32 .15 .49 -.03 .54 .56 1.00 21. Farm Value .08 .26 . 12 .07 .11 -.00 -.00 -.00 .22 .23 .03 . 18 .01 . 14 .07 .52 -.07 .81 .77 .65 1.00 22. Weeks worked off-farm in 1966 -.23 -.11 .06 .03 .10 -.01 -.04 . 14 -.11 -.18 .06 -.52 -.05 -.84 -.29 .21 .04 -.20 -.22 -.33 -.20 1.00 23. Knowledge of D .A . -.14 . 18 .16 .16 -.05 .07 .08 -.18 . 17 . 13 .01 -.04 . 14 . 14 .09 .16 .05 .11 .13 .18 .12 -.08 24. Visits to D.A.'S Office -.08 .28 . 12 .28 .02 . 10 .05 -.13 .11 .24 -.12 .04 -.02 . 14 -.00 . 17 .01 .24 .29 . 17 .28 - . 11 25. Telephone calls to D.A. -.00 .20 . 12 .18 .07 .29 .08 -.16 .28 . 12 .02 -.00 -.00 .11 .01 .23 .01 .26 .27 .37 .33 -.09 26. Farm Visits by D.A. -.08 .06 .06 .20 .11 .02 -.01 -.17 . 11 . 19 . 15 .01 .03 . 14 .01 .17 -.02 .10 .04 .28 .19 -.06 27. Attendance at Meetings/Field Days -.08 .19 .11 . 12 .09 .05 .05 -.26 .20 .36 . 13 .06 .06 .21 .11 .24 -.04 .19 .13 .32 .23 -.17 28. Mail from D.A. .03 .21 .05 . 15 . 15 .06 .20 - . 15 . 14 .25 . 18 . 10 .00 . 14 .00 .08 .08 . 17 . 10 . 15 . 13 - . 12 29. Farm Radio/T.V. Programs .03 .01 . 19 .03 -.03 .04 .06 -.09 .07 .03 -.04 .03 .05 .06 . 14 -.02 -.01 .06 .05 .08 .05 -.09 30. Farm Newspaper Articles .11 . 18 .13 .08 .09 -.03 . 10 -.00 .25 . 12 . 17 .04 .02 .09 .05 .02 .09 .16 .13 . 14 .13 - . 10 31. All Extension Contacts -.00 .29 .19 .24 .12 . 12 . 15 -.23 .28 .33 . 12 .08 .03 .22 .08 .20 .04 .29 .25 .35 .31 -.19 NOTE: The underlined coefficients show a high degree of association. A significance test for r was carried out using a null hypothesis of no correlation with a .01 level of significance. The test is based on the assump-tion that under the null hypothesis of no correlation, the sampling distribution of the correlation coefficient can be approximated closely with a normal curve having the mean zero and the standard deviation l/y a - i where n = the sample size. Therefore, the criterion is to reject the null hypothesis if r< - 2. 58/j/ a - I or *>2. 58yV n - 1 (i.e., if the correlation coefficient is less than - . 173 or greater than . 173, n being 222). 1.00 .27  .43 .70 1.00 .27 .53 1.00 .56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 to 00 TABLE III SPEARMAN RANK CORRELATION COEFFICIENTS Variables 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 1. Age 1.000 NOTE: The underlined coefficients show a high 2. Years of school completed . -. 144 1.000 1.000 degree of association. A significance test for R 3. Wife's Education -.144 .279 1.000 was carried out using~the hypothesis that the 4. Number of Children .021 .010 .252 1.000 correlation in the population was not significantly 5. Fathers' Education -.214 .199 . 184 .095 different from zero at . 01 level of significance. 6. Length of residence in the area -.025 -.025 -.088 -. 105 .040 1.000 The test does not assume that the bivariate 7. Distance travelled for services -.037 -.058 -.098 -.082 -.168 -.051 1.000 sampling distribution is normal, and hence it 8. Level of Living .044 .308 .401 .070 .128 -.011 -.337 1.000 allows the use of obtained correlation coefficients 9. Social Participation -.136 .280 .206 .043 .092 .126 -.042 .289 1.000 1.000 to test the null hypothesis when it is not possible 10. Attitudes to Change -.275 . 125 .193 .204 .181 -.052 -.164 .116 . 112 to ascertain the pattern of distribution of the 11. Number of years farming .424 -.019 -.127 -.076 -.071 .057 -.095 .067 .074 -. 189 1.000 sample with respect to the variables under study. 12. Months worked in 1966 -.151 .071 .016 -.043 .075 -.013 -.118 .056 .060 .073 -.098 1.000 Therefore, the criterionjs to reject the null 13. Degree of Involvement in farming .148 .104 -.042 -.083 .037 .078 -.193 .126 .176 -.194 .556 .023 1.000 hypothesis if R< -<1 - oa2 ) or 1 - oa2 14. job Satisfaction . 174 .058 .060 -.074 .037 .110 -.202 .171 .038 -.057 .238 -. 129 .330 1.000 15. Net Farm Income -.170 . 158 .190 .231 .014 .069 -.041 .172 .121 .165 -.202 .121 -.227 -.042 1.000 1.000 IN^IN I) i / (i.e., if the correlation coefficient is less than 16. Number of Total Acres -.036 .017 -.096 .039 -.072 .115 .186 -.190 .243 .056 .145 .125 .171 -.026 . 109 17. Number of Improved Acres -.004 .174 -.006 .043 -.004 .199 -.077 .073 .262 -.037 .203 .118 .292 . 114 . 193 .703 1.000 -. 171 or greater than . 171, d.f. = 220). 18. Approximate Gross Farm Income -.032 .195 .154 .030 .075 .110 -.186 .297 .365 .083 .313 .150 .454 . 171 .099 .420 .573 1.000 19. Farm Value -.038 .331 .233 .142 .074 .057 -.136 .351 . .383 .115 .243 .116 .321 . 185 .313 .430 .597 .708 1.000 20. Weeks worked off-farm -.212 -.096 .019 .119 -.028 -.083 . 152 -. I l l -.175 .177 -.547 -.055 -.826 -.320 .347 -.191 -.315 -.490 -.340 1.000 21. Visits to D.A. ' s Office -.086 .285 .116 .024 .083 .089 -.147 .093 .208 -.014 .047 .073 .135 .099 . 146 .239 .340 .232 .270 -.091 1.000 22. Telephone Calls to D.A. -.072 .164 .131 .104 .222 .085 -. 185 .300 . 153 .110 -.034 .007 .102 .063 .145 .083 .175 .244 .337 -.061 .308 1.000 23. Farm Visits by D.A. -.079 .056 .039 .121 .067 -.034 -.152 .106 .215 .229 .046 .078 .151 .035 .215 .166 .124 .261 .297 -.083 .161 .431 1.000 24. Attendance at Meetings/ Field days -. 139 .206 .133 .109 .097 .061 -.253 .256 .345 .179 .040 .172 .219 .117 .191 .179 .266 .327 .306 -.191 .327 .273 .375 1.000 25. Mail from D.A. -.007 .203 .106 .174 .081 .192 -.098 .175 .261 . 155 .064 .022 .155 .023 .118 .239 .330 .297 .285 -.123 .245 .123 .159 .311 1.000 26. Farm Radio/T.V. Programs -.003 -.019 .121 .050 .033 .056 -.072 .040 .031 .031 -.008 .097 -.018 .085 -.013 .011 .054 .034 .034 -.050 .144 .073 .014 .117 .325 1.000 27. Farm Newspaper Articles .131 .203 .125 .093 -.038 .108 -.005 .258 .109 .112 .073 -.055 .067 .023 .060 .105 .179 .173 .206 -.090 .134 . 077 . 012 .166 . 488 .321 1.000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 - 30 -older respondents were more involved i n a g r i c u l t u r e , and they had been working as farmers f o r more years than had the younger respondents. These data suggest that a g r i c u l t u r e i n B r i t i s h Columbia i s an occupation f o r older men. The data are consistent with the general trend-reported i n the l i t e r a t u r e of r u r a l sociology to the e f f e c t that the median age of farmers i s r i s i n g . The desire for further education tended to decrease with age and t h i s f i n d i n g was not unexpected. A poss i b l e explanation i s that the older respondents have passed the stage i n t h e i r l i f e c ycle when they consider education as necessary to f u l f i l l t h e i r r o l e s . They did not consider education a necessity to meet the demands and aspirations of t h e i r present period of l i f e . Furthermore, the older household heads were more s a t i s f i e d with farming as an occupation, and they tended to spend less time at off-farm jobs than did the younger farmers. These data suggest that the higher job s a t i s f a c t i o n i n l a t e r years may be related to the fact that the older farmers have ei t h e r reconciled themselves to t h e i r occupational choices, or have moved into more desirable jobs. The rank c o r r e l a t i o n analysis showed consistent r e s u l t s with the simple c o r r e l a t i o n with regard to the association between age and father's education (R = -.214), number of years farming (R = .424), job s a t i s f a c t i o n (R - .174) and number of weeks worked off-farm i n 1966 (R » -.212). The analysis d i f f e r e d with regard to the asso c i a t i o n between age and attitudes to change (R= _. 275) which showed s i g n i f i c a n t c o r r e l a t i o n only i n the rank c o r r e l a t i o n analysis (Table III) but not 2 Edmund deS. Brunner, The Growth of a Science. New York, Harper and Brothers Publishers, 1957 p. 47. - 31 -i n the simple. This l a t t e r a s s o c i a t i o n indicates that the older respondents showed l e s s readiness to change than the younger. The f i n d i n g i s not unexpected since i t follows the normal pattern of s t a b i l i z a t i o n of employment with increased age. The comparison of the r e s u l t s of the two analyses i s summarized i n Appendix IV. M a r i t a l Status The majority of the respondents were married with 84 per cent i n t h i s category. Some 14 per cent were s i n g l e , 2 per cent were widowed and 2 per cent were divorced or separated. Since most of the respondents were married, m a r i t a l status was not tested f o r r e l a t i o n s h i p s with other c h a r a c t e r i s t i c s . Number of Children The majority of the respondents had le s s than four c h i l d r e n with 58 per cent of the farmers i n t h i s category. More than four c h i l d r e n were reported by 23 per cent of the respondents, while 18 per cent reported four c h i l d r e n . The median number of c h i l d r e n was three. S i g n i f i c a n t c o r r e l a t i o n s were obtained between the number of c h i l d r e n and at t i t u d e s to change (r - .18) and between the number of c h i l d r e n and net farm income (r = .17), but the c o r r e l a t i o n c o e f f i c i e n t s are very low. Therefore, no r e l i a b l e conclusions could be drawn from such data. There was complete agreement i n the r e s u l t s of the simple and rank c o r r e l a t i o n analyses with respect to the as s o c i a t i o n between the number of c h i l d r e n and attitudes to change, and between the number of c h i l d r e n and net farm income. Number of People i n the Household The respondents were asked about the t o t a l number of people l i v i n g i n the household. Forty-two per cent of the household heads reported three or less people, 18 per cent reported four, while another - 32 -42 per cent reported f i v e or more people i n the household. The median number of people l i v i n g i n the household was four. This v a r i a b l e was not tested for r e l a t i o n s h i p s with other c h a r a c t e r i s t i c s . Place of B i r t h Over h a l f of the farmers i n the sample were born i n Canada with 68 per cent i n t h i s category. Of these one hundred and seventy-four Canadians, 35.5 per cent were born i n B r i t i s h Columbia while the remaining 64.5 per cent migrated to B r i t i s h Columbia from other provinces. Some 10 per cent of the respondents were born i n U.S. and another 6 per cent i n the United.Kingdom. Sixteen per cent of the sample were born i n other countries not c l a s s i f i e d i n t h i s study. Place of b i r t h was not tested f or r e l a t i o n s h i p s with other socio-economic v a r i a b l e s . Length of Residence i n the Area A s u b s t a n t i a l proportion of the farmers studied had migrated to the area from elsewhere i n Canada. Only 16 per cent of the respondents had l i v e d i n the area t h e i r e n t i r e l i f e . F i f t y - f i v e per cent of the farmers had l i v e d i n the present area for more than twenty years, and another 20 per cent had l i v e d i n the area from s i x to sixteen years. Some 10 per cent had l i v e d i n the area from seventeen to twenty years, and only 16 per cent had l i v e d i n the area for less than s i x years. The median number of years l i v e d i n the area was i n the 17 to 20 year category. Length of residence i n the area showed no r e l a t i o n s h i p with any other socio-economic c h a r a c t e r i s t i c s studied when the simple c o r r e l a t i o n a nalysis was used, but the rank c o r r e l a t i o n showed that length of residence i n the area was s i g n i f i c a n t l y correlated with number of improved acres the farmer operated (R = .199). These data suggest that the farmers who had l i v e d longer i n the area reported larger farms than the newcomers. - 33 -I I . EDUCATIONAL CHARACTERISTICS Respondent's Education The education that an i n d i v i d u a l receives i n h i s pre-adult years exerts a considerable influence on h i s s o c i a l and economic status. The data c o l l e c t e d f o r the years of school completed by respondents showed that the median education^level was eight years. Eighty-six per cent of the farmers had less than high school education, some 9 per cent had graduated from high school, and the remaining 5 per cent had at l e a s t one year of u n i v e r s i t y education. Of the nine respondents who had u n i v e r s i t y education, about 60 per cent had one to three years while the remaining 40 per cent had u n i v e r s i t y degree.. Nine per cent of the respondents had completed f i v e or less years of school, meaning that they could be c l a s s i f i e d as functional i l l i t e r a t e s . ^ The proportion of f u n c t i o n a l i l l i t e r a t e s i n t h i s survey was consistent with 8.7 per cent reported by Verner^ f o r r u r a l B r i t i s h Columbia as of 1961. As one would normally expect, there was a s i g n i f i c a n t c o r r e l a t i o n (r = .23) between the education of the husband and that of the wife. This c o r r e l a t i o n suggests that marriage partners tended to marry within the same educational l e v e l . The household heads reporting a higher l e v e l of education also p a r t i c i p a t e d more i n adult education, thereby, supporting the conmon b e l i e f that the desire to further one's education i s a function of the formal educational background.^ A s i g n i f i c a n t c o r r e l a t i o n (r = .24) was also obtained between the education of the respondent and that 3 Coolie Verner, "Adult I l l i t e r a c y 1921-1961", Journal of Education of the Faculty of Education of the University of B r i t i s h Columbia, Vancouver, 10: 1964, pp. 99-109. 4 Ibid, p. 103. 5 Edmund deS. Brunner, et a l . An Overview of Adult Education Research, Chicago, Adult Education Association of the U.S.A., I l l i n o i s , 1959, pp. 92-93. - 34 -of the father. This correlation implies that the well educated fathers understood the vlue of education and had the means to educate their children. The respondents with more education had a significantly higher level of living (r = .30). A further significant correlation (r = .25) was found between the education of the respondent and his social participation, meaning that the respondents with more education had better understanding and appreciation of community activities and were prepared to participate. Other socio-economic factors which showed significant correlation coefficients with years of school completed by the respondents included net farm income (r = .24), total size of farm (r = .29), size of improved acreage (r = .17), approximate gross farm income (r = .22) and farm value (r =. .26). A l l these are economic factors and their associations with formal education are not unexpected. The results of the rank correlation analysis agreed with a l l but two of the findings of the simple correlation, with respect to the associations between years of school completed and the other socio-economic factors. The former analysis showed no significant relationship as did the latter analysis between years of school completed and net farm income, and between the years of school completed and number of total acres. Wife's Education The data on the wife's education indicate that the spouses of the farmers in the sample had more education than their husbands. The median educational level of the spouses was from nine to eleven years of school completed. Fifteen per cent of the wives completed high school, 7 per cent had one to three years of university education, but none completed university training. Of the one hundred and sixty wives who had not completed high school, 6.9 per cent had five or less - 35 -years of school, and as such, could be c l a s s i f i e d as functional i l l i t e r -ates, 16.3 per cent had s i x to seven years of school, while another 76.8 per cent had eight to eleven years of school completed. There were s t a t i s t i c a l l y s i g n i f i c a n t c o r r e l a t i o n c o e f f i c i e n t s obtained between the education of the spouse and a number of socio-economic f a c t o r s , including the education of the husband (r = .23), respondents p a r t i c i p a t i o n i n adult education (r = .17), number of c h i l d r e n (r = .29), father's education (r = *18), l e v e l of l i v i n g (r = .38), s o c i a l p a r t i c i p a t i o n (r = .17), net farm income (r = .18) and approximate gross farm income (r = .19). The association between the education of the spouse and that of the respondent supports a previous conclusion that marriage partners tended to marry within the same educational l e v e l . The other associations indicate that the respondent's p a r t i c i p a t i o n i n adult education was associated with high educational achievement of the wife, attd also that the education of the wife was a f a c t o r influencing the possession of the items l i s t e d on the l e v e l of l i v i n g s c a l e . The wife's education was also associated with the respondent's p a r t i c i p a t i o n i n community a c t i v i t i e s . Contrary to expectation, however, the data revealed a p o s i t i v e c o r r e l a t i o n between the education of the wife and the number of c h i l d r e n i n the family. This association suggests that spouses with more education had larger number of c h i l d r e n . This unexpected r e s u l t might be due to incomplete data on wife's education. The r e s u l t s of further analysis with rank c o r r e l a t i o n were con-s i s t e n t with those of the simple c o r r e l a t i o n , with respect to the a s s o c i a t i o n betxv-een wife's education on the one hand, and years of school completed by the respondent (R = .279), number of c h i l d r e n (R = .252), 6 Coolie Verner, op. c i t . - 36 -father's education (R = .184), level of living (R = .401), social participation (R = .206) and net farm income (R = .190) on the other hand. The result differed with regard to the association between the wife's education and gross farm income. These were correlated in the simple correlation and not in the rank, whereas attitudes to change (R = .193) and farm value (R = .233) were correlated in the rank correlation but not in the simple. These last two correlations indicate that the respondents whose wives had higher education were more favourably inclined to change, and valued their farms higher than those who married spouses with low education. These associations are not unexpected. Father's Education The data describing the educational achievement of the fathers of the respondents indicate that only 5 per cent of the fathers completed high school. Twenty-nine per cent had less than eight years of school, while 18 per cent completed five or less years of school and so could be classified as functional illiterates,'' This latter figure is double the number of functional i l l i t e r a t e s found among the respondents, indicating that they were better educated than their fathers. Another 22 per cent of the fathers had eight to eleven years of schooling, and only 3 per cent had the high school diploma. Some 2 per cent of the fathers obtained university education. A significant correlation was obtained between the father's education and socio-economic factors such as the age of the respondents (r = .18), respondent's education (r = .24), education of the spouse (r = ,18) and distance the respondents travelled to obtain their goods and services (r = -.21). The above associations suggest that 7 Ibid. - 37 -the fathers of the younger respondents received more education than the fathers of the older farmers, and that education was a family t r a i t . Furthermore, the fathers of the respondents who t r a v e l l e d l e s s distance for t h e i r goods and services received more education. These data intimate that the respondents from more educated f a m i l i e s might have migrated to or near the service centres. The rank c o r r e l a t i o n analysis showed that the same c h a r a c t e r i s t i c s discussed above, except distance t r a v e l l e d f or goods and services, c o r r e l a t e d with father's education. There was also s t a t i s t i c a l l y s i g n i f i c a n t p o s i t i v e c o r r e l a t i o n between father's education and attitudes to change (R = .181). These data suggest that the farmers whose fathers completed more years of school were more apt to change than those whose fathers d i d not. This f i n d i n g i s not unusual since the fathers with more education are more l i k e l y to give t h e i r c h i l d r e n more education than are fathers with l e s s education, and education i s presumed to i n s t i l l a favourable a t t i t u d e toward change.** There i s some evidence of upward educational m o b i l i t y among the farm operators since the median educational l e v e l of the respondents was eight years of school, while the fathers showed a median educational achievement of s i x to seven years of school completed. The f a c t that 44 per cent of the respondents did not know the educational achievement of t h e i r fathers makes any inference drawn from these figures inconclusive. Adult Education Recent studies have stressed the importance of adult education by showing i t s r e l a t i o n s h i p to other socio-economic c h a r a c t e r i s t i c s beyond the r e l a t i o n s h i p accounted f o r by years of school completed. The data 8 Herbert F. Lionberger, Adoption of New Ideas and P r a c t i c e s . Ames, The Iowa State U n i v e r s i t y Press, Iowa, 1960, p. 97. - 38 -g in this study also support the findings of these previous studies. In many previous studies adult education activities such as courses in agriculture and meetings conducted by agricultural agents are grouped together. This technique offers a single dimensional approach to the measurement of adult educational activities of the respondents. In this procedure specific adult education programs rate low with respect to their relationship to other socio-economic characteristics. Although the isolation of specific educational activities is not always easy, this study deals with three principal activities in which the respondents participated. General Adult Education The public school d i s t r i c t s in rural British Columbia operate adult classes for farm operators in a variety of subjects other than agriculture. The majority of the respondents had not participated in such classes as only 12 per cent reported attendance in these activities during the year preceding the survey. Participation in adult educational activities showed significant correlation coefficients with a number of socio-economic factors including years of school completed (r = .28), social participation (r = .26), level of living (r = .18) and number of months spent in agriculture in 1966 (r = .21). The above correlations indicate that the respondents who attended general adult education classes derived their motivation for continuous learning from their pre-adult educational experience. Usually, these respondents who participated in adult education are the leaders in their communities, and hence, they were more involved in social activities than those who did not take part in adult education courses. By virtue of their 9 Verner and Millerd, op. c i t . pp. 13-19 and Edmund deS. Brunner, op_ c i t . pp» 84-87. - 39 -educational experience, they could afford to provide decent standards of living for their families. The positive correlation between participation in adult education and the number of months spent in agriculture is unusual, but this correlation may be due to a feeling of obsolescence on the part of the farmers. They might have recognized the need to update their practices. Adult Courses in Agriculture Various agencies, including the British Columbia Department of Agriculture, occasionally offer courses in agricultural subjects to farmers. Attendance at such courses was reported by 10 per cent of the sample. Three per cent of the respondents had taken such courses in high school, and another 7 per cent had these courses either in the vocational or agricultural school and agricultural college, or in a university. Of the fifty-eight reporting participation, thirty (51.7 per cent) had taken a course related to their jobs. This factor was not tested for relationship with the other socio-economic characteristics. District Agriculturist Meetings and Field Day Data were collected on the attendance and the frequency of attendance at agricultural meetings and field-days. Most of the respondents (66 per cent) had not attended any meetings.. Of the eighty-seven respondents who reported attendance, fifty-nine (67.8 per cent) attended once or twice, twenty (22.9 per cent) attended thrice or four times, and eight (9.3 per cent) attended such meetings five or more times during the year preceding the survey. S t a t i s t i c a l l y significant correlation coefficients were obtained between attendance at agricultural meetings and f i e l d days and such factors as years of school completed (r = .19), - 40 -distance travelled for goods and services (r = -.26), level of liv i n g (r = .20), social participation (r = .36),degree of involvement in farming (r = .21), net farm income (r = .24), total size of farm (r = .19), approximate gross farm income (r = .32), farm value (r = .23) and weeks worked off farm (r = -.17). The above correlations suggest that the farmers who attended agricultural meetings conducted by the agricultural agents had more education, lived closer to the service centres where such meetings were lik e l y to be held, and provided higher standards of liv i n g for their families ; than those who did not attend. These household heads were also more active in community activities and earned more from their agricultural produce. They operated larger farms which might have resulted in their higher income. The s t a t i s t i c a l l y significant correlations between attendance at agricultural meetings and f i e l d days and the other three personal contacts indicate that the respondents reporting more frequent contacts of one type were more lik e l y to have more contacts of the other types. In addition to the factors discussed above, further analysis with rank correlation showed s t a t i s t i c a l l y significant correlation coefficients between attendance at agricultural meetings and f i e l d days and such factors as attitudes to change (R = .179),number of months worked on the farm in 1966 (R = .172) and number of improved acres (R = .266). These data indicate that the respondents who attended the meetings and f i e l d days were more favourably inclined to change, spent more time on farming, and owned larger size of improved farms than those who did not. The analyses suggest that specific agricultural program, such as would be covered in agricultural meetings and f i e l d days, showed higher correlation coefficients than either educational level alone - 41 -or general adult education programs. Specific agricultural program was also correlated with larger number of socio-economic factors. These data imply that the amount of education is not as significant a factor as the specific relevancy with respect to the content.^ Desire for Further Education or Training An individual's desire for further education or training is a strong indication of his aspirations and willingness to improve his present standard of living, by participating in educational activities provided by the agricultural extension service. The respondents were asked about their desire for further education or training. The alternative responses were as follows: 'yes 1, 'no', or 'undecided'. The responses indicated that 46 per cent wanted to further their education or training, another 46 per cent did not want any further education or training, while 7 per cent of the household heads were undecided. Four respondents (1 per cent) did not answer the question. There were s t a t i s t i c a l l y significant correlation coefficients obtained between desire for further education or training and such factors as age (r = -.36), years of school completed (r = .19), number of years in agriculture (r = -.18) and number of months spent in agriculture in 1966(r = .18). The above associations indicate that the younger respondents desired more education or training than did the older farmers, meaning that desire for further education decreases with age. Previous training also appeared to be a factor influencing desire for more education, as the respondents with more years of school completed desired further education. The data also show that the desire for further 10 This is in agreement with the work of Verner and Millerd, Ibid. - 42 -education tended to decrease with years of involvement in agriculture. The farmers who had spent more years in agriculture were the older respondents, and since the desire for more education decreases with age, i t is a logical corollary that desire for further education decreases with number of years in agriculture. Contrary to expectation, the respondents who "spent more time in farming in the year preceding this study expressed desire for further education. However, this expressed desire for further education might indicate that the respondents f e l t they were out-of-date in agricultural practices, and might be prepared to up-date their farming techniques by participating in educational ac t i v i t i e s . On the other hand, the expressed desire for education may represent a wishful thinking. The specific kinds of training desired by the respondents are shown in Table IV. The kind of further training most frequently noted related to farm mechanization with forty-three respondents expressing a desire for such training. Thirty respondents said that they were willing to take training in agriculture, including such courses as animal and crop husbandry. Other training mentioned, in order of frequency,included welding (twenty-one respondents), recreation (thirteen respondents), carpentry (ten respondents), academic training purposely for certificates (seven respondents), non-credit courses in commerce (seven respondents) and business management (six respondents). One hundred and thirty-nine respondents were undecided regarding their desire to take some further education. III. SOCIAL CHARACTERISTICS Three indices of social behaviour, including level of living, social participation and distance travelled for goods and services, - 43 -TABLE IV PERCENTAGE DISTRIBUTION OF RESPONDENTS BY KIND OF FURTHER TRAINING DESIRED Respondents Kind of Training Desired No. %. Farm mechanization 43 16 Agriculture (animal and crop husbandry) 30 11 Welding 21 7 Recreation 13 5 Carpentry 10 4 Academic Training for certificate 7 3 Non-credit commerce courses 7 3 Business Management 6 2 Undecided 139 50 TOTAL 276* 100 * Twenty respondents gave more than one response - 44 -were studied i n order to determine the s o c i a l c h a r a c t e r i s t i c s of the respondents. Level of L i v i n g A short form of Sewell's Farm Socio-Economic Status S c a l e 1 1 was used to assess the l e v e l of l i v i n g of the farmers i n the sample. Most of the respondents received t o t a l scale scores above seventy, and the median score was i n the eighty-one to ninety c l a s s . Only two per cent of the respondents scored le s s than sixty-one, while 39 per cent scored sixty-one to eighty, and 59 per cent of the sample obtained eighty-one and over. The above data ind i c a t e that the l i v i n g conditions of majority of the farm f a m i l i e s included i n t h i s study appeared to be s a t i s f a c t o r y . S t a t i s t i c a l l y s i g n i f i c a n t c o r r e l a t i o n c o e f f i c i e n t s were obtained between l e v e l of l i v i n g and such factors as years of school completed (r = .30), wife's education (r = .38), p a r t i c i p a t i o n i n adult education (r » .18), distance t r a v e l l e d f o r goods and services (r - -.28), s o c i a l p a r t i c i p a t i o n (r = .30), net farm income (r = .19), approximate gross farm income (r - .28) and farm value (r = .22). The above associations suggest that the educational l e v e l of farm f a m i l i e s and the p a r t i c i p a t i o n of respondents i n adult educational programs were some of the f a c t o r s i n f l u e n c i n g the possession of the items tabulated on the l e v e l of l i v i n g s c a l e . Furthermore, the farmers who obtained high l i v i n g scale scores were l e s s dependent on external sources f o r the supply of goods and ser v i c e s , showed more active i n t e r e s t i n community programs, and 11 W.H. Sewell. "A Short Form of the Farm Family Socio-Economic Status Scale", Rural Sociology, 8: 1943, 161-170. The socio-economic status i s measured by the number of household equipments, type of housing, l e v e l of education, and church or Sunday school attendance score obtained by the farm family at the time of the study. The score f o r d i f f e r e n t items v a r i e s from 2 to 8 (Appendix I, Questions 15-28). The t o t a l score ranges from 40 to 92, and the minimum score of 40 indicates the lowest l e v e l of l i v i n g , while the maximum score of 92 r e f l e c t s the highest l e v e l of l i v i n g . - 45 -earned more from farming. When the data were subjected to rank c o r r e l a t i o n analysis, a l l the socio-economic factors which showed c o r r e l a t i o n i n the simple c o r r e l a t i o n analysis, plus two addi t i o n a l f a c t o r s , including job s a t i s -f a c t i o n (R = .171) and number of t o t a l acres (R = -.190), showed s i g n i f i c a n t c o r r e l a t i o n c o e f f i c i e n t s with l e v e l of l i v i n g . The associations with these two a d d i t i o n a l factors indicate that the farmers who reported higher l e v e l of l i v i n g tended to enjoy farming more, but reported fewer number of t o t a l acres than those who reported lower l e v e l of l i v i n g . The former association was not unusual, but the l a t t e r suggests that the s i z e of t o t a l acres i s not as relevant a f a c t o r as the siz e of improved acres, although the rank c o r r e l a t i o n analysis did not show s i g n i f i c a n t c o r r e l a t i o n between siz e of improved acres and l e v e l of l i v i n g . S o c i a l P a r t i c i p a t i o n The degree of s o c i a l p a r t i c i p a t i o n was measured by using the Chapin S o c i a l P a r t i c i p a t i o n S c a l e , 1 2 which was modified by eliminating church attendance. The range of the scale was from zero to over t h i r t y -f i v e , and the median category, as revealed by the data, was one to f i v e . Almost one h a l f of the respondents (47 per cent) scored zero, and 72 per cent had a score of le s s than eleven. Only t h i r t y - f o u r respondents (14 per cent) scored above twenty, and another t h i r t y - e i g h t respondents (15 per cent) had scores ranging from eleven to twenty. S o c i a l p a r t i c i p a t i o n was co r r e l a t e d with such f a c t o r s as years 12 F. Stuart Chapin, " S o c i a l P a r t i c i p a t i o n Scale", Minneapolis, Minnesota, Un i v e r s i t y of Minnesota Press, 1937, reprinted i n F. Stuart Chapin, Experimental Designs i n S o c i o l o g i c a l Research (revised e d i t i o n ) , New York: Harper and Brothers, 1955, pp. 276-278. The extent of p a r t i c i p a -t i o n i s measured by the number of memberships held during the previous year and each membership counts as one point toward the t o t a l scale score. Intensity, or degree of involvement i s measured by attendance at meetings, f i n a n c i a l contribution, committee memberships and the holding of o f f i c e s . A higher scale score r e f l e c t s a higher rate of p a r t i c i p a t i o n . - 46 -of school completed (r = .25), the education of the spouse (r = .17), p a r t i c i p a t i o n i n adult education ( r = .26), l e v e l of l i v i n g (r = .30), t o t a l number of acreage farmed (r = .25), improved farm acreage (r = .18), approximate gross farm income (r = .31), farm value (r = .23) and number of weeks spent at off-farm jobs (r = -.18). These c o r r e l a t i o n s suggest that the house-hold heads who were more active p a r t i c i p a n t s i n community a c t i v i t i e s had a higher l e v e l of education, p a r t i c i p a t e d more i n adult education, operated more acreage., earned more from farming, and spent less time i n off-farm job than the le s s active p a r t i c i p a n t s . The education of the spouse also influenced the respondents' s o c i a l a t t i t u d e s . The respondents who married wives with higher l e v e l of education had more favourable attitudes toward s o c i a l a c t i v i t i e s . The r e s u l t s obtained from rank c o r r e l a t i o n analysis were consistent with those discussed above, but showed, i n addition, that s o c i a l p a r t i c i p a t i o n was correlated with degree of involvement i n farm-ing (R = .176)„ These data indicate that the respondents who were more active i n community a c t i v i t i e s tended to be more involved i n ag r i c u l t u r e than those who were les s a c t i v e . Distance T r a v e l l e d for Goods and Services In order to obtain a measure of the phys i c a l i s o l a t i o n of the farm f a m i l i e s i n the study areas, respondents were asked how many miles they t r a v e l l e d to purchase or receive selected types of goods and ser v i c e s . The median distance t r a v e l l e d for a l l the items studied was eleven to f i f t e e n miles. Forty-four per cent of the respondents t r a v e l l e d less than eleven miles, and only four per cent t r a v e l l e d - 47 -forty-one miles or more for the items. Twenty-seven per cent of the household heads t r a v e l l e d eleven to twenty miles, and another 15 per cent t r a v e l l e d twenty-one to f o r t y miles. These data revealed that the goods and services studied were within easy access of most of the farmers included i n the sample, meaning that most of the respondents d i d not s u f f e r p h y s i c a l i s o l a t i o n . There were s i g n i f i c a n t negative c o r r e l a t i o n c o e f f i c i e n t s obtained between distance t r a v e l l e d f o r goods and services and such factors as the educational achievement of the father ( r - -.21) and l e v e l of l i v i n g (r = -.28). These c o r r e l a t i o n s imply that the respondents whose fathers had lower educational achievement t r a v e l l e d longer distance to obtain t h e i r goods and services, and also that the respondents who were more dependent on d i s t a n t sources for t h e i r goods and services could not provide most of the items on the l e v e l of l i v i n g s c a le. S t a t i s t i c a l l y s i g n i f i c a n t rank c o r r e l a t i o n c o e f f i c i e n t s were also obtained between distance t r a v e l l e d f o r goods and services and such factors as l e v e l of l i v i n g , degree of involvcmnt i n farming (R = -.193) job s a t i s f a c t i o n (R = -.202), number of t o t a l acres (R = .186) and approximate gross farm income (R = -.186), but not with father's education. The above associations suggest that the farmers who were more i s o l a t e d from s e r v i c e centres reported le s s involvement i n farming, enjoyed a g r i c u l t u r e lees, owned larger number of t o t a l acres, and earned le s s gross income from farming than those who l i v e d c l o s e r to the service centres. These findings are not unexpected, because the tendency i s f o r the low socio-economic residents to move into the countryside as the housing lands i n the service centres become expensive. - 48 -IV. ECONOMIC CHARACTERISTICS According to previous research, the economic s i t u a t i o n of the farmer tends to exert a major influence on h i s r e l a t i o n s h i p with the formalized sources of a g r i c u l t u r a l information i n h i s area. In t h i s study, the indices of economic status used included the p r i n c i p a l and secondary a g r i c u l t u r a l products sold by the farmer during the year preceding t h i s survey, siz e of farm enterprise ( e i t h e r as t o t a l acreage farmed or animal u n i t s owned), degree of involvement i n farming, farm income,.farm value, land tenure, farm labor used, number of weeks worked off-farm i n 1966 and the changes contemplated i n the farming operations. Size of Enterprise Two indices were used to e s t a b l i s h the s i z e of enterprise. The s i z e of farm i n acres was used f o r those farm operators engaged i n the production of tree and vegetable crops, while the number of animal u n i t s was used to measure the s i z e of l i v e s t o c k farming. Size of Farm i n Acres The median t o t a l s i z e of farm was i n the 320 to 639 acre c l a s s . The median s i z e of improved acreage i J was i n the 100 to 159 acre category. These data indi c a t e that most of the respondents' land was i n bush or timber. The t o t a l s i z e of farm 1* was s i g n i f i c a n t l y c o r r e l a t e d with such f a c t o r s as years of school completed (r = .29), s o c i a l p a r t i c i p a t i o n (r = .25), net farm income (r = .39), improved acreage (r = .62), 13 Improved acreage includes area cleared and put under crops. 14 T o t a l acreage figures were c a l c u l a t e d by m u l t i p l y i n g the midpoint of each acreage category by the number of respondents i n that category and summing the resultant products. - 49 -approximate gross farm income (r = .54), farm value (r = .81) and number of weeks spent off-farm (r = -.20). These c o r r e l a t i o n s indicate that the respondents who possessed larger size of farm tended to have a higher l e v e l of education, p a r t i c i p a t e d more i n community a c t i v i t i e s , earned more from a g r i c u l t u r e , owned more improved acreage and spent l e s s time i n off-farm jobs. The siz e of farm improved also showed s t a t i s t i c a l l y s i g n i f i c a n t c o r r e l a t i o n c o e f f i c i e n t s with years of school completed (r = .17), s o c i a l p a r t i c i p a t i o n (r = .18), net farm income (r = .47), t o t a l s i z e of farm (r = .62), approximate gross farm income (r - .56), farm value (r = .77) and number of weeks spent off-farm i n 1966 (r = -.22). The r e s u l t s of rank c o r r e l a t i o n analysis agreed with those of the simple c o r r e l a t i o n discussed above, with respect to the asso c i a t i o n between number of t o t a l acres and such factors as s o c i a l p a r t i c i p a t i o n (R = .243), number of improved acres (R = .703), gross farm income (R = .420), farm value (R = .430) and number of weeks spent at o f f -farm jobs i n 1966 (R = -.191). But the rank c o r r e l a t i o n showed no association with years of school completed and net farm income as di d the simple c o r r e l a t i o n . The rank c o r r e l a t i o n did show s i g n i f i c a n t c o r r e l a t i o n with distance t r a v e l l e d f o r goods and services (R = .186), l e v e l of l i v i n g (R = -.190) and degree of involvement i n ag r i c u l t u r e (R - .171). These l a t t e r associations indicate that the farmers who reported larger number of t o t a l acres tended to be more i s o l a t e d from service centres and had lower standard of l i v i n g than "those who reported l e s s . These findings support an e a r l i e r conclusion that ownership of large t o t a l acres seems not to be a relevant f a c t o r as the number of - 50 -improved acres. The farmers who reported larger number of t o t a l acres were also more involved i n a g r i c u l t u r e than those who reported l e s s , and t h i s f i n d i n g i s not unexpected. The socio-economic factors which were s i g n i f i c a n t l y c o r r e l a t e d with number of improved acres were consistent i n the two c o r r e l a t i o n analyses regarding seven factors, including years of school completed (R = .174), s o c i a l p a r t i c i p a t i o n (R - .262), net farm income (R = «193), number of t o t a l acres (R ,703), gross farm income (R = .573), farm value (R =..597) and number of weeks spent at off-farm jobs i n 1966 (R = -.215). However, rank c o r r e l a t i o n showed s i g n i f i c a n t c o r r e l a t i o n s between numbers of improved acres and some other socio-economic factors not reported i n the simple c o r r e l a t i o n . These include length of residence i n the area (R = .199), number of years i n a g r i c u l t u r e (R = .203) and degree of involvement i n farming (R = .292). These l a t t e r associations suggest that the respondents who reported larger number of improved acres tended to have l i v e d i n the area for longer periods, had been farming f o r more years, and were more involved i n farming than those who reported smaller farms. Animal Units. Most of the l i v e s t o c k farmers were small scale operators. The median t o t a l animal u n i t s 1 ^ was i n the 20 to 29 category. Only 29 per cent of the 215 l i v e s t o c k farmers owned f i f t y u nits of animal and over, while 41 per cent reported less than twenty animal u n i t s . Seventeen per cent of the l i v e s t o c k farmers owned t h i r t y to forty-nine 15 The t o t a l animal units f or each respondent were determined by m u l t i p l y i n g the average number of each type of animal on the farm i n 1966 by an animal unit f a c t o r . A f u l l y grown horse or beef cow, fo r example, had an animal unit factor of 1.0, while a c a l f under one year old was valued at 0.25, and a h e i f e r between one and two years at 0.66. For f u l l d e t a i l see Appendix I I I . - 51 -animal units. Since 16 per cent of the sample reported no animal units, this variable was not tested for relationships with other characteristics. Agricultural Products Sold In order to determine the type of farm enterprise in which the respondents were engaged, the farmers were asked to name the agricultural product from which they obtained the largest gross revenue in 1966. Secondary products were checked for those who gave more than one response. The majority of the respondents were engaged in beef pro-duction since 40 per cent of the respondents reported that they obtained their largest gross revenue from the production of beef cattle. Field crops other than fruits and vegetables were second in rank since 35 per cent of the household heads obtained their largest gross revenue from such products. Dairy produce ranked next with 14 per cent of the respondents reporting their largest gross revenue from the sale of milk and/or cream. Other products mentioned as the principal agricultural products included livestock (excluding beef and dairy), fruits and vegetables (including potatoes), poultry products and woodlot products. Fourteen per cent of the farmers sold beef as their secondary farm product and an equal number of farmers reported f i e l d crops (other than fruits and vegetables) as their secondary products. Since i t was not possible to put these products on an interval scale, they were not tested for relation-ships with other variables. Farm Income and Value The net*6 and the approximate gross farm incomes*^ were recorded for each respondent. Farm value was measured in terms of what the farmer 16 The net income was the money earned from the sale of farm product after deducting a l l farm expenses. 17 The approximate gross farm income was the value received from the sale of a l l farm products. This income does not include the value of produce raised and consumed by the farmers; therefore, any correlations with gross farm income should be interpreted with this limitation in mind. - 52 -said he would pay to own and operate h i s farm as a going concern. The median net farm income claimed by the respondents was i n the $2,000 to $2,999 group. F i f t y - s i x per cent of the farmers earned le s s than $3,000 i n the year preceding t h i s study. Another 30 per cent reported a net farm income of $3,000 to $5,999, while 10 per cent of the sample earned $6,000 to $9,999. Some 4 per cent of the farmers earned $10,000 and over. The net farm income correlated s i g n i f i c a n t l y with such factors as years of school completed (r = .24), education of the spouse ( r = .18), number of c h i l d r e n (r = .17), l e v e l of l i v i n g (r = .19), t o t a l s i z e of farm (r = .39), improved acreage (r = .47), approximate gross farm income (r = .49), farm value (r = .52) and weeks spent at off-farm jobs (r = .21). These c o r r e l a t i o n s indicate that the farm operators who earned more from a g r i c u l t u r e tended to have more educational achievement than those who earned l e s s . The s i g n i f i c a n t p o s i t i v e c o r r e l a t i o n between the education of the wife and net farm income indicates that the farmers whose wives had more education earned more from a g r i c u l t u r e . However, the c o r r e l a t i o n between net farm income and number of c h i l d r e n i s unexpected except under such conditions that labor was the only l i m i t i n g factor, and the c h i l d r e n were engaged on the farm up to a point where marginal return equals the cost of an a d d i t i o n a l unit of labor. The respondents who earned more from farming also had higher standards of l i v i n g , possessed larger acreage of farm ( t o t a l and improved), obtained more gross income from the sale of farm produce, and valued t h e i r farms higher than those who earned l e s s . The above data also 18 Marginal return i s the addition to t o t a l income r e s u l t i n g from the use of an a d d i t i o n a l unit of factor of production, ( i n t h i s case, l a b o r ) . - 53 -indicate that the farmers who earned more from a g r i c u l t u r e spent more time working off-farm. This a s s o c i a t i o n i s also contrary to expectation unless the respondents spent part of the money earned from non-agricultural jobs to develop t h e i r farms. Further analysis with rank c o r r e l a t i o n disagreed with the r e s u l t s of simple c o r r e l a t i o n with respect to the associations between net farm income and three f a c t o r s , including years of school completed, number of t o t a l acres and gross farm income. These factors were not associated with net farm income i n the rank c o r r e l a t i o n a n a l y s i s . The two analyses, however, showed associations between net farm income and such factors as wife's education (R = .190), number of c h i l d r e n (R = .231), l e v e l of l i v i n g (R = .172), number of improved acres (R - .193), farm value (R = .313) and number of weeks worked off-farm i n 1966 (R = .347). The rank c o r r e l a t i o n also showed s i g n i f i c a n t associations between net farm income and two other f a c t o r s , including number of years farming (R = -.202) and degree of involvement i n a g r i c u l t u r e (R = -.227), neither of which factors i s co r r e l a t e d i n the simple c o r r e l a t i o n a n a l y s i s . These l a s t two associations indicate that the respondents who earned more "take-home" d o l l a r s from a g r i c u l t u r e tended to have spent l e s s years i n a g r i c u l t u r e and were les s involved i n a g r i c u l t u r e . This i n t e r p r e t a t i o n implies that these farmers were engaged i n occupations other than farming. The median gross farm income reported by the farmers was i n the $3,000 to $3,999 c l a s s . F o r t y - s i x per cent of the respondents earned l e s s than $3,000, another 36 per cent earned $6,000 and over, while forty-nine respondents (20 per cent) reported a gross farm .income of $3,000 to $5,999. There were s t a t i s t i c a l l y s i g n i f i c a n t c o r r e l a t i o n s obtained between gross farm income and such factors as years of school - 54 -completed (r = .22), wife's education (r = .19), level of living (r = .28), social participation (r = .31), number of years in agriculture (r = .21), degree of involvement in farming (r = .32), net farm income (r = .49), total size of farm (r = .54), improved acreage (r = .56), farm value (r = .65). and weeks worked off-farm in 1966 (r = -.31). Number of children was not associated with gross farm income. The above associations indicate, among other things, that the farmers who earned more income from agriculture spent less time at off-farm jobs. The results of the rank correlation analysis were consistent with those of the simple regarding the associations between gross farm income and such factors as years of school completed (R = .195), level of living (R = .279), social participation (R = .365), number of years farming (R = .313), degree of involvement in farming (R = .454), number of total acres (R = .420), number of improved acres (R = .573), farm value (R = .708) and number of weeks spent at off-farm jobs in 1966 (R = -.490). But the rank correlation did not show associations, as did the simple, between gross farm income and wife's education, and between gross farm income and net farm income. However, the rank correlation, unlike the simple, showed that gross farm income was significantly correlated with two other factors, including distance travelled for goods and services (R = -.186) and job satisfaction (R = .171). These last two associations suggest that the respondents who earned more gross farm income lived closer to the service centres and expressed more satisfaction in farming than those who earned less, The majority of respondents valued their farms highly with a l i t t l e over half (51 per cent) valuing their farms at more than $39,999. The median value reported for a l l the farms w a s in the $40,000 to $49,999 - 55 -range. Only eighteen farmer«(7 per cent) valued t h e i r farms at less than $10,000, while 40 per cent valued t h e i r farms from $10,000 to $39,999. Some 24 per cent of the farmers said they would pay $40,000 to $69,999 to own t h e i r farms, and another 9 per cent valued t h e i r farms at $70,000 to $99,999. Sixteen per cent of the respondents valued t h e i r farms at $100,000 and over. The respondents who valued t h e i r farms higher tended to have higher l e v e l s of education (r = .26), higher standards of l i v i n g (r = .22), more favourable attitudes toward community a c t i v i t i e s (r = .23), and had been i n a g r i c u l t u r e f or more years (r = .18) than those who valued t h e i r farms l e s s . These farmers also earned more from a g r i c u l t u r e , operated larger farms, and spent less time at off-farm jobs (r = -.21). Net farm income was studied further by asking the respondents to in d i c a t e whether the year 1966 (the year for which data on income was c o l l e c t e d ) was t y p i c a l , better or poorer than average. F o r t y - s i x per cent said i t was better than average, while 33 per cent said i t was poorer than average. Ten respondents were not farming previous to 1966, and hence they could not give any opinion, while three respondents declined to give any opinion. Land Tenure The majority of the respondents (79 per cent) owned t h e i r farms, 9 per cent rented more than h a l f and owned the remainder, while 8 per cent owned more than h a l f and rented the remainder. Only one respondent rented the whole farm and one was a h i r e d manager. The respondents were asked another question about the method of acquiring t h e i r farms. The data revealed that 30 per cent of the respondents bought t h e i r farm land as i t was at the time of t h i s study, - 56 -while some 16 per cent acquired t h e i r land p r i v a t e l y as unimproved land. About 14 per cent (37 respondents) purchased t h e i r land from the Crown. Other methods of a c q u i s i t i o n included pre-empted or homestead p l o t s (with 11 per cent of the respondents i n t h i s category), purchased as fallow (with another 11 per cent), while 8 per cent i n h e r i t e d t h e i r farm land as a going concern. Land tenure was not tested f or r e l a t i o n s h i p s with other v a r i a b l e s . Farm Labor The farmers i n r u r a l B r i t i s h Columbia generally employed no labor other than members of the farm family u n i t . One hundred and f i f t y -eight respondents (62 per cent) reported that they used no h i r e d labor, while about three-tenths (32 per cent) used seasonal workers only. Some 2 per cent h i r e d labor on a one-year basis and another 2 per cent h i r e d labor s t e a d i l y . Time Spent at Off-farm Jobs Almost one h a l f of the respondents had no off-farm employment 1 9 since 49 per cent were i n t h i s group. One fourth (25 per cent) were employed for h a l f of the year or more o f f the farm. Nineteen per cent of the farmers worked o f f t h e i r farms from f o u r to twenty-five weeks, while fourteen farmers (5 per cent) were employed o f f t h e i r farms for le s s than four weeks i n the year preceding t h i s survey. Number of weeks spent at off-farm jobs showed s t a t i s t i c a l l y s i g n i f i c a n t c o r r e l a t i o n c o e f f i c i e n t s with such factors as age (r = -.23), 19 Off-farm employment was the work for which payment was received. Therefore, exchange work between neighbors and friends was not considered off-farm employment„ - 57 -s o c i a l p a r t i c i p a t i o n (r = -.18), number of years i n a g r i c u l t u r e (r = -.52), degree of involvement i n farming (r = -.84), job s a t i s f a c t i o n (r = -.29), net farm income (r = .21), t o t a l acreage farmed (r = -.20), improved acreage (r = -.22), gross farm income (r = -.33) and farm value (r = -.20). These c o r r e l a t i o n s indicate that the farmers who spent more time at off-farm jobs tended to be younger and less active i n community organizations than those who spent less time. These farmers were also newcomers and were les s involved i n a g r i c u l t u r e . They derived less s a t i s f a c t i o n from farming but^ contrary to expectation, they obtained more net income from farming. Furthermore, these respondents operated le s s acreage, t h e i r gross farm income was l e s s , and they valued t h e i r farm less than those who spent le s s time working off-farm. Further analysis with rank c o r r e l a t i o n showed associations which were consistent with those discussed above. One a d d i t i o n a l factor ( a t t i t u d e s to change) was also c o r r e l a t e d with time spent at off-farm jobs (R = .177). This l a s t a s s o c i a t i o n indicates that the farmers who spent more time at off-farm jobs were more l i k e l y to change than those who spent le s s time. This f i n d i n g i s not unexpected since part-time farmers u s u a l l y earn more income and are more w i l l i n g to take r i s k s than f u l l -time farmers. Degree of Involvement i n Farming In order to assess the extent to which the farmers were involved i n a g r i c u l t u r e ^ the respondents were asked to indicate whether they were farmers only, farmers p r i n c i p a l l y with secondary off-farm jobs, non-farmers p r i n c i p a l l y with farming as a secondary job, or just s t a r t i n g 20 The degree of involvement i n farming was spread over a four point scale, with "farmer;only" having the highest score of four and "just s t a r t i n g a farm"-the lowest spore of one. - 58 -a farm. Most of the respondents were highly involved i n a g r i c u l t u r e with almost h a l f (49 per cent) of the sample reporting farming as t h e i r only occupation. T h i r t y - e i g h t per cent of the respondents were non-farmers p r i n c i p a l l y but had farming as a secondary job. Another 12 per cent reported farming as t h e i r p r i n c i p a l occupation and a non-farm job as secondary. Only three respondents (1 per cent) were j u s t s t a r t i n g a farm at the time of the survey. Degree of involvement i n farming showed s i g n i f i c a n t c o r r e l a t i o n s with such factors as number of years i n a g r i c u l t u r e (r = .54), job s a t i s f a c t i o n (r = .31), approximate gross farm income (r = .32) and weeks spent at off-farm jobs (r = -.84). These associations suggest that the respondents who were more involved i n a g r i c u l t u r e had been farming for more years and expressed more s a t i s f a c t i o n i n a g r i c u l t u r e . These farmers also earned more from farming and spent le s s time working off-farm. With rank c o r r e l a t i o n analysis, s i g n i f i c a n t c o r r e l a t i o n co-e f f i c i e n t s were obtained between degree of involvement i n farming and the socio-economic c h a r a c t e r i s t i c s discussed i n the foregoing paragraph. Seven other f a c t o r s , including distance t r a v e l l e d f o r goods and services (R = -.193), s o c i a l p a r t i c i p a t i o n (R = .176), attitudes to change (R = -.194), net farm income (R = -.227), number of t o t a l acres (R = .171), number of improved acres (R = .292) and farm value (R = .321) were co r r e l a t e d with-degree of involvement i n farming. These c o r r e l a t i o n s suggest that the respondents who were more involved i n farming l i v e d c l o s e r to the se r v i c e centres; they were more active i n community organizations, l e s s w i l l i n g to change, earned l e s s net farm income, owned larger farms (both t o t a l and improved acres), and valued t h e i r farms higher than those who were less involved. The associations between degree of involvement i n farming and d i s t ance t r a v e l l e d f o r goods and services, and between degree of involvement i n farming and s o c i a l p a r t i c i p a t i o n , are unusual and d i f f i c u l t to explain. - 59 -Over two-fifths of the farmers (41 per cent) had been farming f o r more than twenty years, and only 19 per cent had been farming f o r less than s i x years. Twelve per cent of the respondents reported that they had been i n a g r i c u l t u r e f o r s i x to ten years, 14 per cent f o r eleven to f i f t e e n years, and 13 per cent had been farming f o r sixteen to twenty years. The median number of years i n farming was in the sixteen to twenty year category. There were s t a t i s t i c a l l y s i g n i f i c a n t p o s i t i v e c o r r e l a t i o n c o e f f i c i e n t s between number of years i n ag r i c u l t u r e and such factors as age (r = .40), degree of involvement i n farming (r = .54), job s a t i s f a c t i o n (r = .23), approximate gross farm income (r = .21) and farm value (r = .18)., These associations suggest, among other things, that the older farmers had been i n a g r i c u l t u r e f o r more years than the younger ones. The respondents who had been farming f o r more years were also more involved i n farming, and were more favourably i n c l i n e d toward a g r i c u l t u r e than those who entered a g r i c u l t u r e more recen t l y . S i g n i f i c a n t negative c o r r e l a t i o n s were obtained between number of years i n a g r i c u l t u r e and two f a c t o r s , including desire f o r further education or t r a i n i n g (r = -.18) and number of weeks worked off-farm i n 1966 (r = „52). These negative correlationsmight be a function of age since the household heads who had been i n a g r i c u l t u r e f o r more years were the older farmers. With respect to time spent at off-farm jobs, since the respondents who had been farming f o r more years tended to be more involved i n a g r i c u l t u r e , i t i s l o g i c a l to expect these farmers to spend les s time at off-farm jobs. Further analysis using rank c o r r e l a t i o n showed that the same socio-economic factors discussed i n the foregoing paragraph, plus three other f a c t o r s , including attitudes to change (R = -.189), net farm income - 60 -(R = -.202)and number of improved acres (R = .203) were s i g n i f i c a n t l y correlated with number of years farming. These l a s t three associations in d i c a t e that the farmers who had been i n a g r i c u l t u r e f o r longer periods tended to have les s favourable attitudes toward change, earned le s s net farm income but reported more number of improved acres than those who have recently come into a g r i c u l t u r e . The ass o c i a t i o n between number of years farming and number of improved acres i s questionable but d i f f i c u l t to explain. One possible explanation, however, i s that the l e s s favourable a t t i t u d e s toward change may cancel the benefits accruing from large improved acres. Job S a t i s f a c t i o n A revised v e r s i o n of B r a y f i e l d and Rothe's Index of Job 21 S a t i s f a c t i o n was administered to a l l the farmers included i n the study. The median score was i n the t h i r t y - t h r e e to t h i r t y - s i x point range. Only three respondents had a score of less than twenty-five, and none had less than twenty. More than t h r e e - f i f t h s (62 per cent) of the respondents scored t h i r t y - t h r e e and over. These data indicate that the majority of the farmers were s a t i s f i e d with farming as an occupation. There was a s t a t i s t i c a l l y s i g n i f i c a n t p o s i t i v e c o r r e l a t i o n (r = .18) between job s a t i s f a c t i o n score and age, suggesting that the older respondents tended to be more s a t i s f i e d with t h e i r work than were the younger farmers. This 21 A.H. B r a y f i e l d and H.F. Rothe, "An Index of Job S a t i s f a c t i o n " , Journal of Applied Psychology. 35: 1951, pp. 307-311. This scale consists of eighteen statements such as "My job i s l i k e a hobby to me", and "Each day of work seems l i k e i t w i l l never end". The scale was reduced to nine items for t h i s study by eliminating the ha l f - s t e p items. Five responses ranging from "strongly agree" to "strongly disagree" were available f or each item, and each response was scored from one to f i v e points. A maximum scale score of 45 points would indicate a highly favourable job a t t i t u d e , whereas a minimum score of 9 points would be i n d i c a t i v e of extreme job d i s s a t i s f a c t i o n . - 61 -r e s u l t i s inconsistent with the findings of previous research i n another 22 area of the province. A possible explanation i s that these older farm operators might have reached the l i m i t of t h e i r aspirations i n l i f e . Therefore^ they f e l t contented with t h e i r present occupation since i t was no longer possible f o r them to move out of a g r i c u l t u r e , either f o r health reasons or from lack of s k i l l t r a i n i n g . Furthermore, job s a t i s f a c t i o n score was p o s i t i v e l y correlated with two other f a c t o r s , i.e.^ number of years i n ag r i c u l t u r e (r - .24) and degree of involvement i n farming ( r = .31), meaning that the respondents who were more s a t i s f i e d with f arming had been i n agri c u l t u r e f o r more years and were more involved i n farming. These two c o r r e l a t i o n s are functions of age. The household heads who expressed more s a t i s f a c t i o n i n ag r i c u l t u r e (r = -.29) spent less time at off-farm jobs, and t h i s f i n d i n g appears normal. There were s t a t i s t i c a l l y s i g n i f i c a n t c o r r e l a t i o n c o e f f i c i e n t s i n the rank c o r r e l a t i o n analysis between job s a t i s f a c t i o n and the four factors discussed i n the preceding paragraph. Four other f a c t o r s , including distance t r a v e l l e d f o r goods and services (R = -.202), l e v e l of l i v i n g (R = .171), gross farm income (R = .171) and farm value (R = .185) were corr e l a t e d with job s a t i s f a c t i o n score. These l a s t four associations indicate that the respondents who expressed more s a t i s f a c t i o n i n a g r i c u l t u r e l i v e d c l o s e r to service centres, had higher standards of l i v i n g , earned more gross farm income, and valued t h e i r farms more than those who expressed le s s s a t i s f a c t i o n . These findings are not unexpected. 22 Coolie Verner, Gary Dickinson and E. Patrick Alleyne, A Socio-Economic Survey of the East Kootenay Area i n B r i t i s h Columbia, Vancouver, Faculty of Education, U.B.C., 42-43 (Jan. 1968)j Coolie Verner and Gary Dickinson, A Socio-Economic Survey of The ' Pemberton Valley, Vancouver, Faculty of Education, U.B.C, 44-45, ( A p r i l , 1968). - 62 -Plans for Change in Farm Operations The respondents were asked to indicate whether they planned to make any changes in their farm operations within the next five years, and, i f so, what changes they planned. One hundred and ninety-six farmers (77 per cent) indicated their intention to make some changes. The changes reported are shown in Table V. The emphasis was on land clearance and drainage since 35 per cent of the respondents contemplated such changes. The next prominent change reported was increase in farm size as 11 per cent contemplated this change. Ten per cent of the farmers planned to increase their stock. Other changes contemplated include change in the nature of enterprise (2 per cent), change of building and total retirement from farming (3 per cent each), decrease in time spent at off-farm jobs (1 per cent), while 4 per cent of the respondents reported changes which defied classification under any of the categories discussed above. Some f i f t y -nine respondents (23 per cent) did not respond to this question. The changes contemplated by the respondents indicate a mixed feeling toward the future of agriculture. A number of changes involved expanding farm operations, a finding which would suggest a basically optimistic attitude. This attitude is further borne out by the fact that the most frequently mentioned change involved improvement in farm operations. Optimisim was also indicated by those who planned to improve their farm building or decrease their off-farm work. These data are inconsistent with an earlier study in another part of the province.^ However, the large proportion of the respondents (23 per cent) who did 23 Ibid. - 63 TABLE V PERCENTAGE DISTRIBUTION OF RESPONDENTS BY FUTURE CHANGES IN FARM OPERATIONS CONTEMPLATED Respondents Changes Planned No. % Increase farm size 28 11 Change nature of enterprise 5 2 Clear and drain land 89 35 Change buildings 7 3 Retire from farming 9 3 Increase stock 21 10 Decrease off-farm work 3 1 Others 10 4 No response 59 23 TOTAL 256 100 - 64 -not answer t h i s question makes inconclusive any inference drawn from these data. The v a r i a b l e s which involved dichotomous responses, such as "Yes" or "No", were not included i n the Spearman rank c o r r e l a t i o n analysis because the respondents could not be ranked on the basis of such data. V. SUMMARY The farm operators included i n t h i s sample are generally s i m i l a r to those i n other r u r a l areas of B r i t i s h Columbia with respect to the socio-economic c h a r a c t e r i s t i c s studied. The household heads were o l d and had been i n a g r i c u l t u r e for a considerable length of time. A substantial number of the respondents were born i n Canada, but a majority of the farmers were born outside of B r i t i s h Columbia. Their educational achievement was associated with most of the other socio-economic factors studied, and the l e v e l of education achieved depended upon the family into which the farmer was born. The median siz e of improved acreage was i n the 100 to 159 acres group, and the median net farm income was i n the $2,000 to $2,999 category; but the median value reported f o r a l l the farms was i n the $40,000 to $99,999 range. The standard of l i v i n g of majority of the farmers was s a t i s f a c t o r y and they l i v e d close to the s e r v i c e centres, but they were les s active p a r t i c i p a n t s i n community a c t i v i t i e s . Most of the respondents were s a t i s f i e d with a g r i c u l t u r e as an occupation and had an o p t i m i s t i c outlook toward the future of a g r i c u l t u r e i n B r i t i s h Columbia. CHAPTER IV FARMERS' CONTACT WITH DISTRICT AGRICULTURISTS The D i s t r i c t A g r i c u l t u r i s t i s usu a l l y one of the main sources of information and education f o r farm operators. In B r i t i s h Columbia, several means are used to disseminate information about new farm p r a c t i c e s to farmers. These methods include v i s i t s and telephone c a l l s by farmers to the D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e , farm v i s i t s , a g r i c u l t u r a l meetings, f i e l d - d a y s , c i r c u l a r l e t t e r s , mailed announcements or b u l l e t i n s , farm radio, t e l e v i s i o n programs and farm newspaper a r t i c l e s . Data were obtained on the type and extent of contacts which each respondent had with the D i s t r i c t A g r i c u l t u r i s t through these media during the year preceding the survey. The r e s u l t s of the analysis of these data are given i n t h i s chapter. I. KNOWLEDGE OF DISTRICT AGRICULTURIST The assessment of farmers' knowledge of the D i s t r i c t A g r i c u l t u r i s t involved asking each respondent to give the name of the D i s t r i c t A g r i c u l t u r i s t i n h i s area. Some 53 per cent of the respondents could give the name of the D i s t r i c t A g r i c u l t u r i s t s , 44 per cent could not make a guess, while 3 per cent made wrong guesses. Knowledge of the D i s t r i c t A g r i c u l t u r i s t was s i g n i f i c a n t l y correlated with such factors as v i s i t s to the D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e ( r = .30), telephone c a l l s to D i s t r i c t A g r i c u l t u r i s t (r = .23), farm v i s i t s , (r = .19), attendance at meetings and f i e l d days (r = .25), reading of c i r c u l a r l e t t e r s and b u l l e t i n s (r = .31), l i s t e n i n g to or viewing farm radio and t e l e v i s i o n programs (r = .23), reading of farm newspaper a r t i c l e s (r = .19) and - 66 -the use of a l l extension contacts combined (r = .43). These c o r r e l a t i o n s suggest that the respondents who knew the D i s t r i c t A g r i c u l t u r i s t tended to have more extension contacts than those who did not know him. I I . EXTENSION CONTACT SCORE An extension contact scale established by Rogers and Capener* was used to measure the contacts between the farmers and the D i s t r i c t A g r i c u l t u r i s t . The d i s t r i b u t i o n of the scores i s shown in Table VI. Four respondents (1.5 per cent) reported no contact of any kind with the D i s t r i c t A g r i c u l t u r i s t during the year preceding t h i s study, and only 5.9 per cent of the respondents had a l l seven types of contact. Some 48.8 per cent of the farmers had one to three types of contact, while the remaining 43.8 per cent had four to s i x types. On the average, each respondent i n the sample had 3.71 types of contact with the D i s t r i c t A g r i c u l t u r i s t . This average score v a r i e d with the contact l e v e l s " as follows: low 2.52, medium 4, and high 5.51 contacts (Table V I I ) . The o v e r - a l l average contact score obtained i n t h i s study i s greater than 2.53 obtained by Verner and Gubbels 3 i n another part of the province. This f i n d i n g suggests that each of the farmers 1 Rogers and Capener, op. cit.) pp. 13-14. 2 Three contact l e v e l s were established by c l a s s i f y i n g the farmers who had from 0 to 3 scores as low, 4 scores as medium, and 5 to 7 scores high. 3 Verner and Gubbels, o_p_. c i t . p. 21 - 67 -TABLE VI PERCENTAGE DISTRIBUTION OF RESPONDENTS BY EXTENSION CONTACT SCORE Extension Contact Respondents Score Noe %_ 0 4 1.5 1 9 3.5 2 28 10.9 3 88 34.4 4 59 23.1 5 38 14.8 6 15 5.9 7 15 5.9 TOTAL 256 100 Average Contact Score (Score x Frequency) ^ Total No. of Respondents = 3.71 - 68 -TABLE VII PERCENTAGE DISTRIBUTION OF RESPONDENTS BY CONTACT LEVELS Contact Levels Respondents No. % Average Contact Score Low 129 50.3 2.52 Medium 59 23.1 4.00 High 68 26.6 5.51 TOTAL 256 100 3.71 in this sample had more types of contact with the District Agriculturist than did the dairy farmers studied by Verner and Gubbels. This finding may be attributed to the fact that the dairy farmers included in the latter study were not representative of the farmers in British Columbia. The average contact made by the farmers with the District Agriculturist was further analyzed on the basis of personal and impersonal contacts, using the contact scores as shown in Table VI. The use of the impersonal sources of information accounted for 72 per cent of the over-all average contact score, while personal contacts accounted for the remaining 28 per cent (Table VIII). This finding indicates that the respondents used the impersonal sources of information more than they used personal contacts. III. TYPE AND EXTENT OF CONTACTS The type and extent of contact which farmers have with the - 69 -TABLE VIII PERCENTAGE DISTRIBUTION OF AVERAGE EXTENSION CONTACT SCORE BY PERSONAL AND IMPERSONAL CONTACTS Average % of Total Type of Contact Score Average Score Personal 1.05 28 Impersonal 2.66 72 TOTAL 3.71 100 agricultural change agents have a great influence on the decision farm families make with respect to the day-to-day running of their farms. Personal contacts, such as farm v i s i t s by District Agriculturist, while allowing for face-to-face discussion between the agent and the farmers, also have the psychological effect of establish-ing rapport between the two discussants, and the farmers may develop greater confidence in the agent. Impersonal contacts, on the other hand, are abstract and more effective in reinforcing existing attitudes 4 than in bringing about change. The respondents were asked about the types and numbers of contact they had with District Agriculturist during the year preceding this survey. The type which had the highest frequency of use was farm newspaper articles, with 93 per cent of the respondents reporting this 4 Joseph T. Klapper, "The Social Effects of Mass Communication", in Wilbur Schramm, (ed.), The Science of Human Communication, New York, Basic Books, Inc., Publishers, 1963, pp. 65-76. - 70 -contact. Farm radio and t e l e v i s i o n programs ranked second since 91 per cent of the respondents reported watching such programs. Eighty-one per cent of the farmers had contact with the D i s t r i c t A g r i c u l t u r i s t through c i r c u l a r l e t t e r s and mailed announcements or b u l l e t i n s . The next most frequently reported contact was farmers' v i s i t s to the D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e , with 35 per cent of the respondents, while another 34 per cent reported attendance at a g r i c u l t u r a l meetings and fi e l d - d a y s . Seventeen per cent of the farmers had telephone c a l l s to the D i s t r i c t A g r i c u l t u r i s t , and only 16 per cent reported farm v i s i t s by D i s t r i c t A g r i c u l t u r i s t (Table IX). The above data indicate that the main form of contact between the farmer and h i s D i s t r i c t A g r i c u l t u r i s t was impersonal. This f i n d i n g i s i n agreement with other research conducted elsewhere i n the province? Personal Contacts The number of farmers who reported no personal contact with the D i s t r i c t A g r i c u l t u r i s t i n the year preceding the study ranged from 65 to 84 per cent, depending on the type of contact (Table X). Twenty-four per cent of the farmers v i s i t e d the D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e once or twice, while only 4 per cent made such v i s i t s f i v e or more times. Some 7 per cent v i s i t e d the D i s t r i c t A g r i c u l t u r i s t s o f f i c e three or four times,and 65 per cent made no such v i s i t s . Eighty-three per cent of the household heads reported no telephone c a l l s to the D i s t r i c t A g r i c u l t u r i s t , 11 per cent made such c a l l s once or twice, 3 per cent c a l l e d three or four times, and another 3 per cent reported making such c a l l s f i v e or more times i n 1966. Only one respondent was v i s i t e d by the •* Verner and Gubbels, op_. c i t . . pp. 21-23. - 71 -TABLE IX PERCENTAGE DISTRIBUTION OF FARMER-DISTRICT AGRICULTURIST CONTACT BY TYPE OF CONTACT Type of Contact Respondents who used the contact No. % Respondents who did not use the contact No. % Tot a l No. 7» V i s i t s to D.A.'s o f f i c e 90 Telephone c a l l s to D.A. 44 Farm v i s i t s with D.A. 42 Attendance at meet-ings and f i e l d days 87 Mails from D.A. Farm radio and T.V. programs Farm newspaper a r t i c l e s Average 206 233 239 35 17 16 34 81 91 93 166 212 214 169 50 23 17 65 256 83 256 66 19 9 256 256 256 '256 100 100 84 256 100 100 100 100 100 134.4 52.4 121.6 47.6 256 100 Note : X = 731.81, d.f. -(oj, p < .001, c = . 86 - 72 -TABLE X PERCENTAGE DISTRIBUTION OF RESPONDENTS BY PERSONAL CONTACTS WITH DISTRICT AGRICULTURIST Respondents Never Frequency per year Tot a l Type of Contact 1 or 2 3 or 4 5 or more No. % No. % No. 7o No, % No. % V i s i t s to D.A.'s o f f i c e Telephone c a l l s to D.A. Farm v i s i t s by D.A. Attendance at meetings and f i e l d days 166 65 62 24 18 7 10 4 256 100 212 83 29 11 7 3 8 3 256 100 214 84 36 14 5 2 1 0.39 256 100 169 66 59 23 20 8 8 3 256 100 Average 190.3 74.5 46.5 18 12.5 5 6.8 2.5 256 100 Note: X = 49.18, d.f.=;9, p< .001, c • .40 - 73 -D i s t r i c t A g r i c u l t u r i s t i n h i s farm f i v e or more times. Eighty-four per cent reported no such v i s i t , 14 per cent reported being v i s i t e d once or twice, and 2 per cent were v i s i t e d three or four times. The number of respondents who attended a g r i c u l t u r a l meetings and field-days i s reported i n Chapter I I I of t h i s t h e s i s . <s The farmers who v i s i t e d the D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e tended to make more telephone c a l l s to the D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e (r = .36), had more farm v i s i t s by the D i s t r i c t A g r i c u l t u r i s t ( r = .23 , R = .308), and attended more meetings and field-days (r = .34, R = .327) as s i g n i f i c a n t p o s i t i v e c o r r e l a t i o n c o e f f i c i e n t s were obtained among these contact methods. These associations suggest that the use of personal contacts follows a pattern, and the farmers who have one type of personal contact are more l i k e l y to have the others. The Spearman rank c o r r e l a t i o n a n alysis d i d not show asso c i a t i o n between v i s i t s to D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e and farm v i s i t s by the agent. The farmers who v i s i t e d the D i s t r i c t A g r i c u l t u r i s t i n h i s o f f i c e also tended to read more mail from the D i s t r i c t A g r i c u l t u r i s t (r = .23, R = .245) as these two v a r i a b l e s were also p o s i t i v e l y c o r r e l a t e d . Impersonal Contacts Impersonal information sources were used more frequently by farmers than were personal contacts. (Table XI). The number of farmers reporting frequent use of the three impersonal sources v a r i e d from 81 to 93 per cent. F o r t y - f i v e per cent reported reading the mail from the D i s t r i c t A g r i c u l t u r i s t 'often', 26 per cent read such mails 'sometimes', 10 per cent 'rarely d i d ' and 19 per cent reported that they never read mail from the D i s t r i c t A g r i c u l t u r i s t . F i f t y per cent of the respondents watched farm radio and T.V. programs 'often', 35 per cent did 'sometimes', 6 per cent - 74 -TABLE XI PERCENTAGE DISTRIBUTION OF RESPONDENTS BY USE OF IMPERSONAL CONTACTS WITH DISTRICT AGRICULTURIST Frequency Type of Never Rarely Sometimes Often T o t a l Contact No. 7, No. 7, No. % No. 7. No. % Mails from D.A. 50 19 25 10 76 26 116 45 256 100 Radio and T.V. programs 23 9 15 6 90 35 128 50 256 100 Farm newspaper a r t i c l e s 17 7 14 5 56 22 169 66 256 100 Average 30 11.6 18 7 70.3 27.6 137.6 53.6 256 100 Note: 43.83, d.f;6, p < .001, c - .38 ' r a r e l y ' d i d , and 9 per cent d i d not watch such programs at a l l . Newspaper a r t i c l e s were the most frequently used of the three impersonal sources of information. S i x t y - s i x per cent of the respondents reported that they read such a r t i c l e s 'often', 22 per cent did 'sometimes', 5 per cent ' r a r e l y ' did, and only 7 per cent reported no use of t h i s medium. The farmers who read mail from the D i s t r i c t A g r i c u l t u r i s t tended to l i s t e n more to radio and to watch t e l e v i s i o n programs (r » .27, R = .325) and to read more farm newspaper a r t i c l e s (r = .43, R = .483) as s i g n i f i c a n t p o s i t i v e c o r r e l a t i o n c o e f f i c i e n t s were obtained among these three sources of information. Again, the use of the impersonal sources of information formed a pattern, since personal contacts - 75 -did not c o r r e l a t e s i g n i f i c a n t l y with any of the impersonal sources, except reading of mail from the D i s t r i c t A g r i c u l t u r i s t . Thus, the farm operators who used one type of impersonal contact ware more l i k e l y to use the others, but not to use personal contacts. IV. SUMMARY , The farmers had an average of 3.71 types of contact with the D i s t r i c t A g r i c u l t u r i s t including 2.66 impersonal and 1.05 personal contacts. Mostof them knew the D i s t r i c t A g r i c u l t u r i s t , and those who knew him were more l i k e l y to have a l l extension contacts. These respondents were more l i k e l y to use impersonal than personal sources when they sought a g r i c u l t u r a l information. This f i n d i n g suggests that a need exi s t s i n B r i t i s h Columbia, f o r a more r e a d i l y a v a i l a b l e personal source of a g r i c u l t u r a l information, to f a c i l i t a t e a more l a s t i n g change i n the a t t i t u d e s of the farmers toward a g r i c u l t u r a l p r a c t i c e s i n p a r t i c u l a r , and toward r u r a l l i f e i n general. The farmers who used one type of personal source of information were more l i k e l y to use the others, but not impersonal sources, and v i c e versa. This f i n d i n g i s i n complete disagreement with the usual findings of d i f f u s i o n s t u d i e s . 6 6 Ibid., p. 22. CHAPTER V FACTORS ASSOCIATED WITH FARMERS' CONTACT WITH THE DISTRICT AGRICULTURIST The type and number of contacts which farmers have with the D i s t r i c t A g r i c u l t u r i s t may be re l a t e d to c e r t a i n of the socio-economic c h a r a c t e r i s t i c s discussed i n Chapter I I I . Factors which influence a farmer's d e c i s i o n to seek advice from the D i s t r i c t A g r i c u l t u r i s t , through any of the contact methods included i n th i s study, may stem from h i s own background and from the p o s i t i o n he occupies i n h i s community. In p a r t i c u l a r , h i s educational background, a g r i c u l t u r a l t r a i n i n g and experience, f i n a n c i a l p o s i t i o n and attitudes towards h i s job w i l l influence h i s desires to seek assistance. This chapter measures the differences i n the socio-economic c h a r a c t e r i s t i c s of the farmers i n the d i f f e r e n t contact l e v e l s established i n Chapter IV, using the chi-square s t a t i s t i c . The r e l a t i o n s h i p s between the socio-economic c h a r a c t e r i s t i c s of the respondents and each of the contact methods were determined, using c o r r e l a t i o n analyses. Further analysis, using multiple regression, was done to determine the proportion of the v a r i a t i o n i n the use of contact methods explained by those socio-economic factors which were s i g n i f i c a n t l y r e l a t e d to the method under consideration. This l a t t e r analysis makes i t possible to eliminate i n t e r a c t i o n s between the independent v a r i a b l e s , and also to predict whether a farmer with c e r t a i n socio-economic c h a r a c t e r i s t i c s i s l i k e l y to have a p a r t i c u l a r type of contact with the D i s t r i c t A g r i c u l t u r i s t . 77 -I. DIFFERENCES AMONG FARMERS AT THE THREE CONTACT LEVELS The three contact l e v e l s * established i n Chapter IV were used as the basis of studying the socio-economic c h a r a c t e r i s t i c s which d i f f e r e n t i a t e d the respondents who had low contact with the D i s t r i c t A g r i c u l t u r i s t from those with high contact. However, only the four socio-economic factors which researchers have shown to be most frequently used as indices of socio-economic status were included i n t h i s a n a l y s i s . (Table Xii) These fac t o r s , years of school completed, adult education p a r t i c i p a t i o n , s i z e of enterprise and family income, cor r e l a t e d with one another and with the other socio-economic f a c t o r s . Years of School completed The formal education of the respondent was defined as the number of years of school completed. Of the 129 farmers who had low contact with the D i s t r i c t A g r i c u l t u r i s t , 78 per cent had completed eight or le s s years of school, 21 per cent completed high school, and only one respondent had at le a s t one year of u n i v e r s i t y education. This d i s t r i b u t i o n indicates that the majority of the farmers who had low contact with the D i s t r i c t A g r i c u l t u r i s t had low educational achievement. 1 B i v a r i a t e tables of three contact l e v e l s , set against some of the socio-economic c h a r a c t e r i s t i c s that were s i g n i f i c a n t l y c o r r e l a t e d with the contact methods, were prepared. Since some c e l l s i n the o r i g i n a l b i v a r i a t e tables were zero or les s than f i v e , i t was necessary to combine classes of data. The r e s u l t i n g chi-square values are shown i n Table XII, and Appendix I I contains the b i v a r i a t e tables f o r which s i g n i f i c a n t chi-square values were obtained. - 78 -TABLE XII CHI-SQUARE VALUES FOR DISTRIBUTION BY SOCIO-ECONOMIC CHARACTERISES CHARACTERISTICS AMONG RESPONDENTS IN EXTENSION CONTACT LEVELS Socio-economic c h a r a c t e r i s t i c s Chi-square values Degree of freedom Contigency c o e f f i c i e n t Years of school completed 14.56 Adult education p a r t i c i p a t i o n 16.01 Number of im-proved acres 52.66 Approximate gross farm income 57.75 < .001 <.001 <.001 <.001 .23 .24 .41 .43 Note: The underlined values are s i g n i f i c a n t at the .01 l e v e l of confidence. A n u l l hypothesis of no s i g n i f i c a n t d i f f e r e n c e i n the socio-economic c h a r a c t e r i s t i c s of the farmers i n the three contact l e v e l s was used at .05 l e v e l of s i g n i f i c a n c e . - 79 -Of the f i f t y - n i n e respondents c l a s s i f i e d as having medium contact with the D i s t r i c t A g r i c u l t u r i s t , 61 per cent had completed eight or les s years of school, 34 per cent graduated from high school, while three respondents (5 per cent) had at l e a s t one year of u n i v e r s i t y t r a i n i n g . A comparison of the d i s t r i b u t i o n of farmers i n the low and medium contact l e v e l s showed that the proportion i n the l a t t e r group who did not complete high school decreased, while there was a correspond-ing increase i n the number of farmers with higher educational achievement. Of the si x t y - e i g h t farmers who were c l a s s i f i e d as having high contact with the D i s t r i c t A g r i c u l t u r i s t , 53 per cent had eight or l e s s years of school, 40 per cent completed high school, and f i v e farmers had at le a s t one year of u n i v e r s i t y education. The tendency for the number of farmers who had higher educational achievement to increase with l e v e l of contact was further borne out when the d i s t r i b u t i o n of farmers i n the three contact l e v e l s was compared. Adult Education P a r t i c i p a t i o n The influence of active p a r t i c i p a t i o n i n general adult education programs on the l e v e l of contact which farmers had with the D i s t r i c t A g r i c u l t u r i s t was also assessed. Of the 129 farmers who had low contact, 6 per cent had p a r t i c i p a t e d i n such adult education programs, while 94 per cent reported no p a r t i c i p a t i o n . Eight per cent of the farmers who had medium contact p a r t i c i p a t e d ; 92 per cent d i d not. Of the si x t y - e i g h t farmers who reported high contact, 25 per cent had taken adult education courses, while 75 per cent had not. The figures above show that there i s an increase i n the percentage of p a r t i c i p a n t s , with a corresponding decrease i n the percentage of non-p a r t i c i p a n t s as one moves from low contact l e v e l to high contact l e v e l . - 80 -This d i s t r i b u t i o n indicates that more of the respondents who p a r t i c i p a t e d i n general adult education courses had more contacts with the D i s t r i c t A g r i c u l t u r i s t , and v i c e versa. Size of Farm In order to determine the impact of size of farm on the number of contacts which farmers had with the D i s t r i c t A g r i c u l t u r i s t , the number of improved acres was used since the c o r r e l a t i o n analyses done i n t h i s study suggest that the number of t o t a l acres i s not as important as the number of acres improved. Of the 129 respondents who reported low contact, almost h a l f (49 per cent) owned 99 acres or l e s s , 19 per cent owned 100 to 159 acres, 18 per cent owned 160 to 639 acres, and 14 per cent reported 640 acres and over. Of the f i f t y - n i n e farmers who had medium contact, 37 per cent owned 99 acres or l e s s , 24 per cent owned 100 to 159 acres, another 24 per cent owned 160 to 639 acres, and 15 per cent owned 640 acres and over. Some six t y - e i g h t respondents reported high contact, and 13 per cent of th i s number owned 99 acres or l e s s , 12 per cent owned 100 to 159 acres, 19 per cent reported 160 to 639 acres, and more than h a l f (56 per cent) owned 640 acres and over. A comparison of the foregoing data also indicates that more of the farmers who operated l a r g e r farms had high contact with the D i s t r i c t A g r i c u l t u r i s t than those who reported smaller units of farm. Gross farm income The d i s t r i b u t i o n of the respondents i n the three contact l e v e l s also d i f f e r e d s i g n i f i c a n t l y with respect to t h e i r farm income. Of the 129 respondents who had low contact with the D i s t r i c t A g r i c u l t u r i s t , almost t h r e e - f i f t h s (59 per cent) earned $2,999 or l e s s , 18 per cent earned $3,000 to $5,999, 7 per cent earned $6,000 to $8,999, and 16 per - 81 -cent reported $9,000 and over. F i f t y - n i n e respondents were c l a s s i f i e d as having had medium contact, and, of t h i s number, 41 per cent earned $2,999 or l e s s , 30 per cent earned $3,000 to $5,999, 10 per cent earned $6,000 to $8,999, while 19 per cent reported $9,000 and over. Of the si x t y - e i g h t respondents who had high contact, 15 per cent earned $2,999 or l e s s , 12 per cent earned $3,000 to $5,999, 6 per cent earned $6,000 to $8,999. and 68 per cent earned $9,000 and over. The foregoing data support the conclusion made i n the preceding paragraphs, that the D i s t r i c t A g r i c u l t u r i s t paid more attention to farmers i n the high socio-economic status than to those who were socio-econimically disadvantaged. Personal Contacts Further analyses were c a r r i e d out to determine the differences between the respondents who had low and high personal contacts. Table XIII contains the socio-economic factors f o r which s i g n i f i c a n t c h i -square values were obtained. Adult Education P a r t i c i p a t i o n Of the 224 respondents who reported low personal contact with the D i s t r i c t A g r i c u l t u r i s t , 9 per cent p a r t i c i p a t e d i n general adult education programs, while 91 per cent did not. Thirty-two respondents reported high personal contact, and, of t h i s number, 28 per cent p a r t i c i p a t e d i n general adult education courses, and 72 per cent reported no such p a r t i c i p a t i o n . High personal contact with the D i s t r i c t A g r i c u l t u r i s t occurred with more of the adult education p a r t i c i p a n t s than onon-p a r t i c i p a n t s . Size of Farm Only the number of improved acres was considered because of the - 82 -TABLE XIII CHI-SQUARE VALUES FOR DISTRIBUTIONSBY SOCIO-ECONOMIC CHARCTERISTICS AMONG RESPONDENTS IN PERSONAL CONTACT LEVELS Socio-economic c h a r a c t e r i s t i c s Chi-square Degrees of Contigency values freedom p coef f i c ient Years of school completed 4.58 Adult Education p a r t i c i p a t i o n 9.51 Number of improved acres 13.38 Approximate gross farm income 11.16 2 N.S. 1 < .01 1 <.001 1 <C-001 .19 .22 .20 Note: The underlined values are s i g n i f i c a n t at the .01 l e v e l of confidence. A n u l l hypothesis of no s i g n i f i c a n t d i f f e r e n c e i n the socio-economic c h a r a c t e r i s t i c s of the farmers i n the t w o personal contact l e v e l s was used at .05 leve'l of s i g n i f i c a n c e . N.S. = not s i g n i f i c a n t reason stated on page 80. Of the 224 respondents who had low personal contact with the D i s t r i c t A g r i c u l t u r i s t , 41 per cent owned 99 acres or l e s s , 19 per cent owned 100 to 159 acres, 20 per cent owned 160 to 639 acres, and another 20 per cent owned 640 acres and over. Of the thirty-two respondents who had high personal contact, 9 per cent owned 99 acres or l e s s , 16 per cent owned 100 to 159 acres,12 per cent owned 160 to 639 acres, and 63 per cent reported 640 acres and over. This analysis also reveals that the farmers who had high personal contact were con-centrated among owners of larger farms. - 83 -Gross farm income A trend similar to that reported in the preceding paragraph was observed from an examination of the low and high personal contact farmers among the various income groups. Of the 224 respondents who reported low personal contact, 47 per cent earned $2,999 or less, 21 per cent earned $3,000 to $5,999, 8 per cent earned $6,000 to $8,999, and 24 per cent earned $9,000 and over. On the other hand, of the thirty-two respondents who had high personal contact, 16 per cent earned $2,999 or less, 6 per cent earned $3,000 to $5,999, 3 per cent earned $6,000 to $8,999, and three-quarters (75 per cent) earned $9,000 and over. Impersonal Contacts Analyses were also carried out to determine the differences in the socio-economic characteristics of the respondents who had low and high impersonal contacts. Table XIV contains the socio-economic factors for which significant chi-square values were obtained. Adult Education Participation Of the sixty-four respondents who reported low impersonal extension contact, 5 per cent had taken general adult education courses and 95 per cent had not; whereas of the 192 respondents who had high impersonal contact, 14 per cent had taken such courses and 86 per cent had not. These low and high impersonal contact farmers, among the adult education participants and non-participants, were significantly different only at the .05 level of confidence. Size of Farm Of the sixty-four respondents who had low impersonal contact, 52 per cent owned 99 acres or less, 25 per cent owned 100 to 159 acres, 14 per cent owned 160 to 639 acres, and 9 per cent owned 640 acres and - 84 -TABLE XIV CHI-SQUARE VALUES FOR DISTRIBUTIONS BY SOCIO-ECONOMIC CHARACTERISTICS AMONG RESPONDENTS IN IMPERSONAL CONTACT LEVELS Socio-economic Chi-square Degrees of Contigency c h a r a c t e r i s t i c s values freedom p_ c o e f f i c i e n t Years of school completed 4.14 2 N.S. Adult education p a r t i c i p a t i o n 4.07* 1 <^.05 .13 Number of improved acres 17.10 3 <^001 .25 Approximate gross farm income 13.38 2 ^ . 0 1 .22 Note: The underlined values are s i g n i f i c a n t at the .01 l e v e l and the value with an as t e r i s k at the .05 l e v e l of confidence. A n u l l hypothesis of no s i g n i f i c a n t d i f f e r e n c e i n the socio-economic c h a r a c t e r i s t i c s of the farmers i n the two impersonal contact l e v e l s was used at .05 l e v e l of si g n i f i c a n c e N.S. = not s i g n i f i c a n t - 85 -over. On the other hand, of the 192 respondents who reported high impersonal contact, 32 per cent owned 99 acres or l e s s , 16 per cent owned 100 to 159 acres, 21 per cent owned 160 to 639 acres, and 31 per cent owned 640 acres and over. Gross Farm income Of the s i x t y - f o u r respondents who reported low impersonal contacts with the D i s t r i c t A g r i c u l t u r i s t , 61 per cent earned $2,999 or l e s s , 19 per cent earned $3,000 to $5,999, 6 per cent earned $6,000 to $8,999, and 14 per cent earned $9,000 and over. On the other hand, of the 192 respondents who reported high of such contact, 37 per cent earned $2,999 or l e s s , 19 per cent earned $3,000 to $5,999, 8 per cent earned $6,000 to $8,999, and 36 per cent earned $9,000 and over from sales of farm produce. The preceding analysis indicates that the four socio-economic c h a r a c t e r i s t i c s examined, including years of school completed, adult education p a r t i c i p a t i o n , number of improved acres and approximate gross farm income, proved to be important determinants of the number of contacts which the respondents had with the D i s t r i c t A g r i c u l t u r i s t . But when the contact methods were regrouped into personal and impersonal contacts, years of school completed was not s i g n i f i c a n t . One important r e s u l t i n t h i s analysis i s worthy of note: that p a r t i c i p a t i o n i n adult education was s i g n i f i c a n t where years of school completed was not. This fin d i n g i s consistent with the observation made by Verner and M i l l e r d * i n t h e i r Okanagan V a l l e y study, "that the amount of education i s not as s i g n i f i c a n t a fa c t o r as the recency of the educational experience and i t s s p e c i f i c relevancy with respect to the content". 1 Verner and M i l l e r d , op_. c i t . pp. 18-19. - 86 -I I . THE DISTRICT AGRICULTURIST'S CLIENTELE The o r i g i n a l data on the farmers who used the contact methods and those who d i d not were regrouped, and the chi-square test was conducted on each of the tables. The r e s u l t s are summarized i n Table XV, and the b i v a r i a t e tables f o r which s i g n i f i c a n t chi-square values were obtained are included i n Appendix I I . Comments on the socio-economic c h a r a c t e r i s t i c s which d i f f e r e n t i a t e d the farmers who had one type of contact and those who did not are given below. Knowledge of D i s t r i c t A g r i c u l t u r i s t The factors which d i f f e r e n t i a t e d the farmers who knew the name of the D i s t r i c t A g r i c u l t u r i s t from those who did not included p a r t i c i p a t i o n i n adult education, number of improved acres and the approximate gross farm income. Of the 136 respondents who knew the mame of the D i s t r i c t A g r i c u l t u r i s t , 18 per cent p a r t i c i p a t e d i n adult education and the remaining 82 per cent reported no p a r t i c i p a t i o n . On the other hand, 5 per cent of the 120 respondents who did not know him p a r t i c i p a t e d i n such educational a c t i v i t i e s , and 95 per cent did not. Some 26 per cent of the farmers who knew the name of the D i s t r i c t A g r i c u l t u r i s t owned 99 acres or l e s s , 16 per cent owned 100 to 159 acres, 22 per cent owned 160 to 639 acres, and 36 per cent operated 640 acres and over. On the other hand, 49 per cent of those who did not know him operated 99 acres or l e s s , 21 per cent owned 100 to 159 acres, 17 per cent owned 160 to 639 acres and 13' per cent reported ownership of 640 acres and over. The data on the gross farm income revealed that 35 per cent of these farmers who knew the D i s t r i c t A g r i c u l t u r i s t earned $2,999 or less from a g r i c u l t u r e , 19 per cent earned $3,000 to $5,999, 4 per cent earned $6,00 to $8,999, TABLE XV CHI-SQUARE VALUES FOR DISTRIBUTION BY SOCIO-ECONOMIC CHARACTERISTICS AMONG USERS AND NON-USERS OF EXTENSION CONTACT METHODS Extension Contact Methods Socio-economic Knowledge of D.A. V i s i t s to D.A.'s O f f i c e Telephone c a l l s to D.A. Farm v i s i t s by D.A. c h a r a c t e r i s t i c s x£ p C X2 p C Xj _p C Xj; p C_ Years of school 7.03 <.01 .16 10.97 <.01 .20 1.91 N.S. - 1.96 N.S. completed (d.f = 1) (d.f = 2) (d.f = 2) (d.f = 2) Adult Education 9.85 <.01 .19 13.93 <.001 .22 8.06 ^.01 .17 4.23 <.05 .13 p a r t i c i p a t i o n (d.f = 1) (d.f = 1) (d.f = 1) (d.f = 1) Number of acres 24.16 <.001 .29 25.10 <.001 .30 18.11 <.001 .26 7.51 <.05 .17 improved (d.f = 3) (d.f - 3) (d.f = 3) (d.f = 2) Approximate Gross 20.78 <.001 .27 17.44 <.001 .25 24.77 <.001 .29 28.12 <.001 .31 Farm income (d.f =3) (d.f = 3) (d.f = 2) (d.f = 2) TABLE XV (continued' Extension Contact Methods Socio-economic Meetings and F i e l d days Malls from D.A. Radio and T.V. Programs Newspaper A r t i c l e s c h a r a c t e r i s t i c s X 2 p C X 2 p C X^ p C X^ p C Years of school 9.25 <.01- .19 3.10 N.S. - 0.96 N.S. - 1.68 N.S. completed (d.f = 1) (d.f =2) (d.f = 2) (d.f = 2) Adult education 7.48 <.01 .17 3.41. N.S. - 1.19 N.S. - 2.26 N.S. p a r t i c i p a t i o n (d.f = 1) (d.f = 1) (d.f = 1) (d.f = 1) Number of improved 18.25 ^.001 .26 12.95 <-Ql .22 13.70 <.01 .22 16.33 <.00l .24 acres (d.f = 3) (d.f = 3) (d.f = 3) (d.f = 1) Approximate gross 25.08 <.001 .30 9.71 <.01 .19 3.79 N.S. - 11.53 </.001 .21 farm income (d.f = 3) * (d.f =2) (d.f =3) (d.f = 1) Note: X 2 .= chi-square values, p = p r o b a b i l i t y C = contigency c o e f f i c i e n t s ^ N.S. = Not s i g n i f i c ant - 89 -and 42 per cent earned $9,000 and over. The corresponding percentages of those who did not know him were 53, 19, 11 and 18 r e s p e c t i v e l y . These data indicate that the d i s t r i b u t i o n of respondents by knowledge of the D i s t r i c t A g r i c u l t u r i s t v a r i e d i n the d i f f e r e n t socio-economic l e v e l s , with more of the respondents i n the high socio-economic l e v e l s knowing the name of the D i s t r i c t A g r i c u l t u r i s t while more of those i n the low socio-economic l e v e l s did not. It may be that the high socio-economic status of some of the respondents i s the e f f e c t rather than the cause of t h e i r knowledge of D i s t r i c t A g r i c u l t u r i s t . Further analysis was c a r r i e d out using the c o r r e l a t i o n s t a t i s t i c to determine the socio-economic factors that were correlated with knowledge of D i s t r i c t A g r i c u l t u r i s t . S t a t i s t i c a l l y s i g n i f i c a n t c o r r e l a t i o n c o e f f i c i e n t s were obtained between knowledge of D i s t r i c t A g r i c u l t u r i s t and such factors as years of school completed (r = .18), distance t r a v e l l e d f o r goods and services (r = -.18), l e v e l of l i v i n g (r = .17) and gross farm income (r = .18). These associations suggest that the farmers who knew the name of the D i s t r i c t A g r i c u l t u r i s t had more education, l i v e d c l o s e r to the service centres where the D i s t r i c t A g r i c u l t u r i s t s are l i k e l y to be located, earned more from farming, and had a higher l e v e l of l i v i n g than those who d i d not know him. These data support the r e s u l t s obtained from the chi-square analysis, since the only f a c t o r added ( l e v e l of l i v i n g ) i s related to the other three f a c t o r s . V i s i t s to D i s t r i c t A g r i c u l t u r i s t ' s O f f i c e The socio-economic c h a r a c t e r i s t i c s which d i f f e r e n t i a t e d the respondents who v i s i t e d the D i s t r i c t A g r i c u l t u r i s t i n h i s o f f i c e from those who did not includedyears of school completed, p a r t i c i p a t i o n i n adult education, number of improved acres and the approximate gross farm income. Ninety respondents reported making such v i s i t s , and 56 per cent - 90 -of t h i s number had eight or less years of school, 39 per cent had completed high school, and 7 per cent had at least one year of u n i v e r s i t y education. On the other hand, 74 per cent of the 166 who reported no such v i s i t s completed eight or less years of school, 24 per cent completed high school, and only f i v e respondents (2 per cent) had at le a s t one year of u n i v e r s i t y education. Some 22 per cent of the farmers who made such v i s i t s p a r t i c i p a t e d i n adult education; 78 per cent d i d not. Only 6 per cent of those who did not v i s i t the D i s t r i c t A g r i c u l t u r i s t i n h i s o f f i c e p a r t i c i p a t e d i n such educational programs, while 94 per cent took no part. With respect to the number of improved acres farmed, 19 per cent of the farmers who v i s i t e d the D i s t r i c t A g r i c u l t u r i s t i n hi s o f f i c e owned 99 acres or le s s , another 19 per cent owned 100 to 159 acres, 24 per cent owned 160 to 639 acres, and 40 per cent reported ownership of 640 acres and over. Almost one h a l f (46 per cent) of those who did not make such v i s i t s owned 99 acres or l e s s , 18 per cent owned 100 to 159 acres, 17 per cent operated 160 to 639 acres, and 18 pa_r cent had 640 acres and over. The data on the gross farm income also revealed varying d i s t r i b u t i o n i n the d i f f e r e n t income lev e l s between the respondents who v i s i t e d the D i s t r i c t A g r i c u l t u r i s t i n hi s o f f i c e and those who did not. Thirty-two per cent of the former earned $2,999 or l e s s , 14 per cent earned $3,000 to $5,999, 9 per cent earned $6,000 to $8,999 and almost one h a l f (47 per cent) reported $9,000 and over. On the other hand, most (49 per cent) of the l a t t e r earned $2,999 or l e s s , 22 per cent earned $3,000 to $5,999, 7 per cent earned $6,000 to $8,999, while another 22 per cent reported $9,000 and over. The above data suggest that more of the farm operators who consulted the D i s t r i c t A g r i c u l t u r i s t In hi s o f f i c e about a g r i c u l t u r a l problems were i n the higher socio-economic status group, meaning (that the - 91 -a c c e s s i b i l i t y of the extension agents i s dependent upon the s o c i a l and economic p o s i t i o n of the c l i e n t e l e . The disadvantaged c l i e n t e l e did not p a r t i c i p a t e i n any face-to-face contacts, probably because he was not motivated to do so, and probably because he f e l t he was not wanted. Even i f the low socio-economic farmers have the desire to make such contacts, they may not have the means. The data from the c o r r e l a t i o n analysis showed that v i s i t s to the D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e were s i g n i f i c a n t l y associated with such factors as years of school completed (r = .28), p a r t i c i p a t i o n i n adult education (r = .28), s o c i a l p a r t i c i p a t i o n (r = .24), net farm income (r = .17), t o t a l s i z e of farm (r = .24), s i z e of improved acreage (r = .29), gross farm income (r = .17) and farm value ( r = .28). These data indi c a t e that the farmers who v i s i t e d the D i s t r i c t A g r i c u l t u r i s t i n his o f f i c e to seek advice on a g r i c u l t u r a l problems were those who had higher l e v e l s of education, p a r t i c i p a t e d more i n adult education programs, were more active i n community a c t i v i t i e s , operated larger farms, earned more from a g r i c u l t u r e , and valued t h e i r farms higher than those who did not. The rank c o r r e l a t i o n analysis did not show any ass o c i a t i o n between v i s i t s to D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e and net farm income, but d i d co r r e l a t e with other factors discussed above. Telephone C a l l s to D i s t r i c t A g r i c u l t u r i s t Three f a c t o r s , including p a r t i c i p a t i o n i n adult education, number of improved acres and the approximate gross farm income d i f f e r e n t i a t e d the respondents who made telephone c a l l s to the D i s t r i c t A g r i c u l t u r i s t from those who di d not since these three factors showed s i g n i f i c a n t chi-square values. Of the for t y - f o u r respondents who reported making such c a l l s , 21 per cent p a r t i c i p a t e d i n adult education programs, while 79 - 92 -per cent did not. On the other hand, the majority (90 per cent) of the 212 farmers who did not make such c a l l s did not p a r t i c i p a t e i n adult education, and only 10 per cent showed active i n t e r e s t i n such programs. Twenty-three per cent of those who reported such c a l l s owned 99 acres or l e s s , 14 per cent owned 100 to 159 acres, 11 per cent owned 160 to 639 acres, and 52 per cent operated 640 acres and over. Some 40 per cent of those who did not use the telephone farmed 99 acres or l e s s , 19 per cent owned 100 to 159 acres, 21 per cent farmed 160 to 639 acres, and only 20 per cent owned 640 acres and over. The data on the gross farm income revealed a s i m i l a r d i s t r i b u t i o n , with 16 per cent of the respondents who made telephone c a l l s to the D i s t r i c t A g r i c u l t u r i s t reporting $2,999 or less , 14 per cent reporting $3,000 to $5,999, 2 per cent reporting $6,000 to $8,999 and almost seven-tenths (68 per cent) reporting $9,000 and over. Forty-nine per cent of those who did not make such c a l l s earned $2,999 or l e s s , 20 per cent earned $3,000 to $5,999, 9 per cent earned $6,000 to $8,999, and 23 per cent reported an income of $9,000 and over. These data support an e a r l i e r conclusion that the s o c i a l and economic statuses of the farmer exert influence on the use of personal extension contact, such as telephone c a l l s to the D i s t r i c t A g r i c u l t u r i s t . The low status farmers d i d not make telephone c a l l s to the D i s t r i c t A g r i c u l t u r i s t , probably because they could not af f o r d to own a telephone or because they f e l t rejected by the higher status segment of the society to which the D i s t r i c t A g r i c u l t u r i s t i s l i k e l y to belong; the farmers i n turn, rejected the society. S t a t i s t i c a l l y s i g n i f i c a n t c o r r e l a t i o n c o e f f i c i e n t s were also obtained between telephone c a l l s to the D i s t r i c t A g r i c u l t u r i s t and such factors as years of school completed (r = .20), p a r t i c i p a t i o n i n adult education (r = .18), father's education (r = .29), l e v e l of l i v i n g - 93 -(r = .28), net farm income (r =» .23), number of t o t a l acres ( r - .26), number of improved acres (r = .27), gross farm income ( r = .37) and farm value (r = .33). These associations indicate that the respondents who had telephone discussion with the D i s t r i c t A g r i c u l t u r i s t on a g r i c u l t u r a l matters were more educated, p a r t i c i p a t e d more i n adult education, provided higher l e v e l s of l i v i n g f o r t h e i r f a m i l i e s , owned larger farms, earned more from t h e i r farms, and valued t h e i r faring higher than those who did not. The father's education also influenced the use of t h i s communication medium, with the respondents whose fathers achieved higher l e v e l of education using the medium more. Further analysis with Spearman rank c o r r e l a t i o n showed consistent r e s u l t s with the foregoing a n a l y s i s , except years of school completed, net farm income and number of t o t a l acres; but telephone c a l l s to the D i s t r i c t A g r i c u l t u r i s t also showed asso c i a t i o n with distance t r a v e l l e d f o r goods and services (R = -.185). This f i n d i n g suggests that the farmers who discussed farm problems with D i s t r i c t A g r i c u l t u r i s t on the telephone depended on l o c a l services f o r t h e i r needs. Because these farmers l i v e d f a r from the service centres where the D i s t r i c t A g r i c u l t u r i s t s are l i k e l y to be located, they r e l i e d to a greater extent on telephone conversation instead of v i s i t i n g the agent i n h i s o f f i c e . Farm V i s i t s by D i s t r i c t A g r i c u l t u r i s t The respondents who were v i s i t e d by the D i s t r i c t A g r i c u l t u r i s t at t h e i r farms d i f f e r e d s i g n i f i c a n t l y from those who were not v i s i t e d i n such f a c t o r s as p a r t i c i p a t i o n i n adult education, number of improved acres, and i n the gross farm income they obtained from the sale of farm produce. Of the forty-two respondents who reported such v i s i t s , 19 per cent p a r t i c i p a t e d i n adult education programs and 81 per cent did not. On the other hand, 90 per cent of the 214 farmers who were not v i s i t e d by the - 94 -D i s t r i c t A g r i c u l t u r i s t reported no p a r t i c i p a t i o n , while only 10 per cent p a r t i c i p a t e d i n such educational a c t i v i t i e s . Some 19 per cent of the farmers who were v i s i t e d owned 99 acres or l e s s , a l i k e number (19 per cent) owned 100 to 159 acres, 10 per cent owned 160 to 639 acres, and more than h a l f (52 per cent) owned 640 acres and over. The majority of those who were not v i s i t e d were small-scale farmers as 58 per cent of these farmers owned less than 160 acres, while only 42 per cent reported ownership of 160 acres and over. About 26 per cent of the .household heads who reported such v i s i t s earned $5,999 or l e s s , while 74 per cent earned $6,000 and over. The d i s t r i b u t i o n was reversed with the farmers who had no such v i s i t s as 69 per cent earned $5,999 or less,while 31 per cent were i n the $6,000 and over c l a s s . These data suggest that the D i s t r i c t A g r i c u l t u r i s t made contact with selected group of farmers, making such contact with more of the farmers i n the higher socio-economic status. One way of explaining t h i s i s that the D i s t r i c t A g r i c u l t u r i s t measured h i s success on the basis of the number of farm operators who accepted h i s advice without much resistance, and who consequently increased t h e i r p r o d u c t i v i t y within a set period; therefore, he selected =the higher-status i n d i v i d u a l s who were already i n the process of making progress f o r h i s farm v i s i t s . In other words, he selected the ' l i n e of least resistance'. Another way of explaining h i s s e l e c t i v e contact i s that most of these farm v i s i t s are us u a l l y requested by the farmer themselves, and, since the low-status / farmers d i d not share the same values with the D i s t r i c t A g r i c u l t u r i s t \ who belonged to., a d i f f e r e n t s o c i a l c l a s s , they rejected him and h i s / s e r v i c e s . / The c o r r e l a t i o n analysis showed that the farmers who were v i s i t e d on t h e i r farms by the D i s t r i c t A g r i c u l t u r i s t tended to be more active i n - 95 -adult education a c t i v i t i e s (r =;.20) and i n community programs (r = ;19). They also earned more from t h e i r farms (net farm income, r = .17, gross farm income r = .28) and valued t h e i r farms higher (r = .19). These data further support the r e s u l t s of the chi-square a n a l y s i s . Further analysis showed that i n addition to the factors discussed above, attitudes to change (R = .229) were also s i g n i f i c a n t l y c o r r e l a t e d with v i s i t s to D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e , i n d i c a t i n g that the farmers who made such v i s i t s were more l i k e l y to accept change. Attendance at Meetings and F i e l d Days Four socio-economic fa c t o r s , including l e v e l of education achieved, p a r t i c i p a t i o n i n adult education, number of improved acres and the gross farm income earned from farming accounted f o r the differences between the respondents who attended a g r i c u l t u r a l meetings and f i e l d days and those who did not. These four factors showed s i g n i f i c a n t chi-square values. Of the eighty-seven respondents who attended such meetings and f i e l d days, 55 per cent had eight or less years of school, 39 per cent completed high school, and 6 per cent had at least one year of u n i v e r s i t y education. The d i s t r i b u t i o n of the 169 respondents who reported no attendance at such meetings and f i e l d days included 74 per cent with eight or l e s s years of school, 24 per cent with high school completed and 2 per cent with at le a s t one year of u n i v e r s i t y education. This d i s t r i b u t i o n indicates that more of the farmers who attended a g r i c u l t u r a l meetings and f i e l d days had higher education than those who did not. A greater proportion of those who attended such meetings also p a r t i c i p a t e d i n adult education v i t h 18 per cent reporting p a r t i c i p a t i o n , compared with 8 per cent of those who did not attend the meetings. With regard to the size of farm operated, 39 per cent of the household heads who reported attendance at a g r i c u l t u r a l meetings and f i e l d - 96 -days owned 159 acres or l e s s , whereas 63 per cent of those who did not attend such events reported t h i s s i z e of farm. The d i s t r i b u t i o n s of the farmers i n the 160 acres and over category were 61 and 37 per cent of those who attended a g r i c u l t u r a l meetings and those who did not r e s p e c t i v e l y . More of the respondents who attended a g r i c u l t u r a l meetings and f i e l d days belonged to the higher income group as 58 per cent of such farmers earned $6,000 and over, while only 28 per cent of those who di d not attend earned as much from t h e i r farms. These data support the conclusions drawn e a r l i e r i n t h i s study that the face^-to-face communica-t i o n i s more influenced by the status of the p a r t i c i p a n t s than i s the impersonal contact. Low-status farmers might f e e l shy and i n f e r i o r about communicating with those in the higher status group on the basis that the discussion might be above t h e i r knowledge, or that t h e i r opinions might not be heeded. Attendance at meetings and f i e l d days was correlated with a number of socio-economic f a c t o r s , including years of school completed (r * .19), distance t r a v e l l e d f o r goods and services (r = -.26), l e v e l of l i v i n g (r = .20), s o c i a l p a r t i c i p a t i o n (r - .36), degree of involvement i n farming (r = .21), net farm income (r - .24), t o t a l s i z e of farm (r = .19), gross farm income (r = .32), farm value (r = .23) and time spent at off-farm jobs i n 1966 (r = -.17). The above associations indicate that the farm operators who attended such meetings and f i e l d days had higher educational achievement, l i v e d c l o s e r to the service centres where such meetings were l i k e l y to be held, p a r t i c i p a t e d more i n community a c t i v i t i e s , operated larger farms, earned more from farming, and, consequently, were able to provide most of the items l i s t e d on the l e v e l of l i v i n g s c a le. They also valued t h e i r farms higher and spent less time at off-farm jobs than thbie who did not attend. - 97 -The Spearman rank c o r r e l a t i o n analysis showed that i n addition to the factors discussed above, attitudes to change (R = .179), number of months spent on farming i n 1966 (R = .172) and number of improved acres (R = .266) were also s i g n i f i c a n t l y correlated with attendance at a g r i c u l t u r a l meetings and f i e l d days. These l a s t three associations suggest that the farmers who showed more active i n t e r e s t i n a g r i c u l t u r a l meetings and f i e l d days tended to accept change more r e a d i l y , spent more time on farming, and owned larger farms than those who did not show in t e r e s t . Mail from D i s t r i c t A g r i c u l t u r i s t The respondents who read the mails from the D i s t r i c t A g r i c u l t u r i s t d i f f e r e d s i g n i f i c a n t l y from those who did not read the mails i n the number of improved acres operated and i n the t o t a l income earned from the sale of farm produce i Of the 206 respondents who reported reading such mails, one h a l f (50 per cent) owned 159 acres or le s s , while the remaining 50 per cent reported ownership of 160 acres and over. The d i s t r i b u t i o n of the farmers v a r i e d more among those who did not read such mails than i t did among those who read the mails, with 78 per cent of the former reporting ownership of 159 acres or l e s s , while only 22 per cent operated 160 acres and more. The d i s t r i b u t i o n of farmers among the income groups followed the same pattern as i t did i n the s i z e of farm operated. F i f t y - e i g h t per cent of those who read the mails from the D i s t r i c t A g r i c u l t u r i s t reported a gross farm income of $5,999 or le s s , and 42 per cent of such farmers reported $6,000 and over. On the other hand, 78 per cent of those who did not read such mails earned $5,999 or l e s s , and 22 per cent were i n the $6,000 and over group. - 98 -One possible explanation of the above data i s that although the mail from the D i s t r i c t A g r i c u l t u r i s t i s an impersonal channel of communication, i t s use requires some personal commitment on the part of the r e c i p i e n t . The D i s t r i c t A g r i c u l t u r i s t w i l l not continue to send such mails unless he i s sure that the receiver w i l l read and make use of the information communicated. The data from the c o r r e l a t i o n analyses provided further ins i g h t into the differences between the respondents who read the mails from the D i s t r i c t A g r i c u l t u r i s t and those who did not. Some ad d i t i o n a l f a c t o r s , including years of school completed (r = .21), length of residence i n the area (r = .20), s o c i a l p a r t i c i p a t i o n (r = .25) and attitudes to change (r = .18) correlated with the reading of such mails. These a d d i t i o n a l associations indicate that the farmers who read such mails had higher l e v e l s of education, were old-timers i n the area, were more active i n s o c i a l a c t i v i t i e s , and had more favourable attitudes to change. These r e s u l t s are not unexpected. The higher educational l e v e l s of the farmers would enable them to communicate with the D i s t r i c t A g r i c u l t u r i s t , t h e i r longer stay i n the area enables them to e s t a b l i s h firmer r e l a t i o n s h i p s with the agent, and t h e i r s o c i a l a c t i v i t i e s i n the community and personal attitudes to change s i n g l e them out as the progressive elements with whom the agent would l i k e to work. When the data were subjected to Spearman rank c o r r e l a t i o n a n a l y s i s , a l l the factors discussed i n the preceding paragraph, except attitudes to change, were correlated with reading of mails from D i s t r i c t A g r i c u l t u r i s t . Six other factors including number of c h i l d r e n (R = .174), l e v e l of l i v i n g (R = .175), number of t o t a l acres - 99 -(R = .239), number of improved acres (R = .330), gross farm income (R = .297) and farm value (R = .285) were s i g n i f i c a n t l y correlated with reading of mails from D i s t r i c t A g r i c u l t u r i s t . The l a s t s i x associations indicate that the farmers who received a g r i c u l t u r a l information through the mails from D i s t r i c t A g r i c u l t u r i s t had more ch i l d r e n , higher standards of l i v i n g , larger farms, earned more income from farming, and valued t h e i r farms higher than those who did not. The association between reading of mails from the D i s t r i c t A g r i c u l t u r i s t and number of c h i l d r e n suggests that the c h i l d r e n of such farmers had in t e r e s t i n farm b u l l e t i n s , newsletters, etc. an attitude which, i n turn, suggests that they were l i k e l y to be members of some farm clubs. Radio and T.V. Programs None of the socio-economic c h a r a c t e r i s t i c s tested d i f f e r e n t i a t e d the users of radio and t e l e v i s i o n media from the non-users. This fi n d i n g may be due to the fact that the use of these mass communication media requires no commitment nor s p e c i a l o b l i g a t i o n from the farmer since the farmers could use t h e i r radio and t e l e v i s i o n sets at w i l l . Furthermore, the use of these media does not involve fact-to-face contact, and, therefore eliminates the socio-economic b a r r i e r s that may hinder the disadvantaged farmers from using such media. The c o r r e l a t i o n analyses did not add much to the r e s u l t s discussed above since only the simple c o r r e l a t i o n showed that one fa c t o r , the education of the spouse, revealed s i g n i f i c a n t a s s o c i a t i o n (r = .19) with l i s t e n i n g to farm radio and viewing the t e l e v i s i o n programs. However, t h i s r e s u l t points to the fac t that since the women are more l i k e l y to stay at home, the spouses with higher education know more about radio and t e l e v i s i o n a g r i c u l t u r a l programs and may i n -fluence t h e i r husbands to l i s t e n and watch such programs. - 100 -Farm Newspaper a r t i c l e s The respondents who read farm newspaper a r t i c l e s d i f f e r e d s i g n i f i c a n t l y from those who did not, i n the number of improved acres owned, and i n the gross farm income earned. Of the 239 respondents who reported reading such a r t i c l e s , 52 per cent operated 159 acres or l e s s , while 48 per cent owned 160 acres and over. As one would expect, the majority of the seventeen farmers who did not reod such a r t i c l e s were in the smaller operators' group as 94 per cent of such farmers owned 159 acres or l e s s , while only 6 per cent owned 160 acres and over. Three-f i f t h s (60 per cent) 0 f the farmers who read newspaper a r t i c l e s earned $5,999 or l e s s , while 40 per cent earned $6,000 and over. Of those farmers who did not read such a r t i c l e s , 94 per cent earned $5,999 or l e s s , while only 6 per cent earned $6,000 and over. Although the reading of farm newspaper a r t i c l e s may not require as much personal commitment on the part of the reader as does the use of other media, i t does require some amount of s a c r i f i c e , both of time and money, which the disadvantaged farmers may not be able to make; hence, they read fewer a r t i c l e s compared with the higher-status farmers who have both the time and the money. The data from the c o r r e l a t i o n analysis indicate that the respondents who read farm newspaper a r t i c l e s were more educated (r = .18) and had higher l e v e l s of l i v i n g (r = .25) since these two factors were associated with the decision to read such a r t i c l e s . Again, these associations are functions of the a b i l i t y to read ( l i t e r a c y l e v e l ) and the a b i l i t y to make the f i n a n c i a l and time s a c r i f i c e . Further analysis with rank c o r r e l a t i o n showed that three other f a c t o r s , including number of improved acres (R = .179), gross farm income (R = .173) and farm value (R = .206) - 101 -were s i g n i f i c a n t l y correlated with reading farm newspaper a r t i c l e s . These l a t t e r associations support the observation made above with respect to f i n a n c i a l . s a c r i f i c e involved. I I I . PREDICTION OF CONTACT BY MULTIPLE REGRESSION METHODS It i s not enough to show that c e r t a i n socio-economic factors are associated with the use of c e r t a i n sources of a g r i c u l t u r a l information; i t i s also necessary to show to what extent such socio-economic factors account for the d i f f e r e n t i a l contacts which farmers at d i f f e r i n g socio-economic le v e l s have with the sources of information. This problem was examined by using the multiple regression approach to explain the v a r i a t i o n i n the use of extension contacts. The r e s u l t s of t h i s analysis are summarized in Table XVI. The v a r i a t i o n i n the use of a l l extension contacts was explained by four socio-economic c h a r a c t e r i s t i c s , including years of school completed, distance t r a v e l l e d f o r goods and services, s o c i a l p a r t i c i p a t i o n and gross farm income. These factors accounted for 34 per cent of the v a r i a t i o n i n the use of these sources of a g r i c u l t u r a l information,leaving 66 per cent unexplained. This fi n d i n g means that there are other fac t o r s , not included i n t h i s study, which influenced the decision of a farmer to make contact with the D i s t r i c t A g r i c u l t u r i s t through any of the channels studied. Four socio-economic c h a r a c t e r i s t i c s , including years of school completed, p a r t i c i p a t i o n i n adult education, attitudes to change and s i z e of improved farm were rel a t e d to v i s i t s which farmers at d i f f e r e n t l e v e l s of socio-economic status had with the D i s t r i c t A g r i c u l t u r i s t during the year preceding t h i s study. However, about one quarter (25 per cent) - 102 -TABLE XVI PERCENTAGE OF VARIATION IN CONTACT EXPLAINED AND THE SOCIO-ECONOMIC FACTORS ACCOUNTING FOR THE VARIATION Contact methods Socio-economic factors accounting f o r v a r i a t i o n Per cent of v a r i a t i o n i n contact explained V i s i t s to D.A.'s o f f i c e Telephone c a l l s to D.A. Years of school completed 25.37 Adult education p a r t i c i p a t i o n Attitudes to change Size of improved farm Father's education 26.89 Level of l i v i n g Gross farm income Farm value Farm v i s i t s by D.A. Adult education p a r t i c i p a t i o n Attitudes to change Gross farm income 13.01 Attendance at meetings and f i e l d days Distance t r a v e l l e d for services S o c i a l p a r t i c i p a t i o n Gross farm income 24.86 Read c i r c u l a r l e t t e r s and b u l l e t i n s Farm radio and/or T.V. programs Farm newspaper a r t i c l e s A l l extension contacts Age 22.98 Years of school completed Length of residence i n the area S o c i a l p a r t i c i p a t i o n Attitudes to change N i l N i l Age 13.15 Level of l i v i n g Attitudes to change Years of school completed 33.92 Distance t r a v e l l e d f o r goods and services S o c i a l p a r t i c i p a t i o n Gross farm income - 103 -of the v a r i a t i o n was explained by the combined e f f e c t of these four v a r i a b l e s , l e a v i n g about three quarters (75 per cent) of the v a r i a t i o n unexplained. This f i n d i n g implies that there are other f a c t o r s , not included i n t h i s study, which are re l a t e d to farmers' v i s i t s to the D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e . D i f f e r e n t socio-economic factors accounted f o r the v a r i a t i o n i n the use of the telephone by farmers to discuss a g r i c u l t u r a l problems with the D i s t r i c t A g r i c u l t u r i s t . The four factors accounting f o r such v a r i a t i o n included father's education, l e v e l of l i v i n g , gross farm income and farm value. About one quarter (27 per cent) of such v a r i a t i o n was explained by these four v a r i a b l e s . This f i n d i n g implies that some other f a c t o r s , not included i n t h i s study, are responsible for the bulk (73 per cent) of the v a r i a t i o n i n the use of that medium by farmers to communicate with the D i s t r i c t A g r i c u l t u r i s t . With respect to farm v i s i t s by D i s t r i c t A g r i c u l t u r i s t , the regression analysis showed that only 13 per cent of the v a r i a t i o n was explained by the combined e f f e c t of three f a c t o r s . These included p a r t i c i p a t i o n i n adult education, attitudes to change and gross farm income, a l l of which t h i s analysis showed to be re l a t e d to contacting farmers through farm v i s i t s by the D i s t r i c t A g r i c u l t u r i s t . This r e s u l t suggests the need for further studies of factors influencing farm v i s i t s which may account f o r the remaining 87 per cent of the v a r i a t i o n i n the use of such contact. About one quarter (25 per cent) of the variance in the respondents' attendance at a g r i c u l t u r a l meetings and f i e l d days was accounted f o r by distance t r a v e l l e d f o r goods and services, s o c i a l p a r t i c i p a t i o n and gross farm income,leaving 75 per cent of the v a r i a t i o n - 104 -unexplained. This f i n d i n g intimates the need for further research in this area. Age, years of school completed, length of residence i n the area, s o c i a l p a r t i c i p a t i o n and attitudes to change explained 23 per cent of the v a r i a t i o n i n obtaining a g r i c u l t u r a l information through the mails from the D i s t r i c t A g r i c u l t u r i s t . None of the socio-economic factors u t i l i z e d i n this study explained the v a r i a t i o n i n the use of farm radio and t e l e v i s i o n to obtain information on a g r i c u l t u r a l problems. It may be necessary to look outside the c h a r a c t e r i s t i c s of farm operators• to explain v a r i a t i o n s in the use of such media by farmers. S i m i l a r l y , age,level of l i v i n g and attitudes to change explained 13 per cent of the v a r i a t i o n i n obtaining a g r i c u l t u r a l information through farm newspaper a r t i c l e s . About 87 per cent of such v a r i a t i o n were l e f t unexplained by the remaining nineteen independent v a r i a b l e s included i n t h i s study. This f i n d i n g further confirms the need for a d d i t i o n a l studies of factors which influence farmers' contact with D i s t r i c t A g r i c u l t u r i s t . IV. SUMMARY The r e s u l t s of the chi-square analysis revealed two important f a c t s . F i r s t , the data showed that the users and the non-users of personal contacts d i f f e r e d more s i g n i f i c a n t l y than those who did and those who d i d not use the impersonal sources of information. This f i n d i n g implies that the d i f f u s i o n of a g r i c u l t u r a l information through personal contacts i s subject to the l i m i t a t i o n s of s o c i a l and economic status. Impersonal sources of information, on the other hand, were l i t t l e influenced by such f a c t o r s . The implication of t h i s i n t e r p r e t a t i o n - 105 -is that i f the farm operators in B r i t i s h Columbia are to have the formalized, d i r e c t and face-to-face contacts with the D i s t r i c t A g r i c u l t u r i s t s , they should be helped to improve t h e i r s o c i a l and economic standards. Second, the data showed that the respondents who had contacts with the D i s t r i c t A g r i c u l t u r i s t s d i f f e r e d s i g n i f i c a n t l y from those who did not, with the farmers who had the contacts belonging to the higher socio-economic c l a s s , while those who did not have contacts were the socio-economically disadvantaged farmers. The use of c o r r e l a t i o n analyses added much to the findings already revealed by the chi-square analysis by revealing the factors that were associated with the use of each of the sources of a g r i c u l t u r a l information studied. However, any reader of t h i s thesis i s faced with the problem of choice between the r e s u l t s of the two c o r r e l a t i o n analyses discussed in the preceding paragraphs. There i s , of course, no doubt about the v a l i d i t y of the findings on which the two analyses concurred, but one has to be circumspect i n the areas where they disagreed. However, since the test of normality showed that the sample was not normally d i s t r i b u t e d (Appendix V), one could say that the Spearman rank c o r r e l a t i o n analysis was more v a l i d , and hence, i t s r e s u l t s were more r e l i a b l e . This statement does not mean that the r e s u l t s of the simple c o r r e l a t i o n analysis are incorrect; i t i s only a matter of degree The r e s u l t s of the regression analysis indicate that very l i t t l e i s known yet about the factors which are re l a t e d to farmer's contact with the D i s t r i c t A g r i c u l t u r i s t , since none of the factors included in t h i s study, either s i n g l y or combined, explained more than one quarter of the v a r i a t i o n i n obtaining information from the extension - 106 -agent through any of the media studied. Therefore, t h i s f i n d i n g makes imperative some ad d i t i o n a l studies to examine c h a r a c t e r i s t i c s besides those of the farm operators, i f extension agents are to make e f f e c t i v e use of these media to communicate with the farmers. CHAPTER VI SUMMARY AND CONCLUSIONS SUMMARY The A g r i c u l t u r a l Extension Service, through the extension workers, i s one of the p r i n c i p a l sources of new a g r i c u l t u r a l technology. There are a number of sources of information that a farmer can use, and hi s use of them i s influenced by a number of socio-economic c h a r a c t e r i s t i c s . A thorough knowledge of the c h a r a c t e r i s t i c s of farm residents, as well as of the r e l a t i o n s h i p of such c h a r a c t e r i s t i c s to the sources through which farmers obtain a g r i c u l t u r a l information, i s indispensable for program planning. This study examined the types and frequency of contacts which farmers had with the D i s t r i c t A g r i c u l t u r i s t i n selected areas i n r u r a l B r i t i s h Columbia, and then re l a t e d these data to the socio-economic c h a r a c t e r i s t i c s of the farmers. Socio-economic C h a r a c t e r i s t i c s Six hundred and f o r t y residents of c e r t a i n sections of r u r a l B r i t i s h Columbia were interviewed from May to August, 1967. Two hundred and s i x t y - f i v e (41.4 per cent) of t h i s number were c l a s s i f i e d as farmers and 375 (58.6 per cent) as non-farmers. Completed interview schedules were a v a i l a b l e f or 256 (96.6 per cent) of the farmers, and a l l of those schedules were used f o r t h i s study. In general, the c h a r a c t e r i s t i c s of the respondents were not unlike those of farm residents i n other r u r a l areas of the province. The median age of the household heads was i n the 45 to 54 year category, and the younger farmers tended to belong to the higher socio-economic status group. F o u r - f i f t h s of the respondents were married and had an average of three c h i l d r e n . Sixty-eight per cent of the farmers - 108 -were born i n Canada, but only 24 per cent were born in B r i t i s h Columbia. A su b s t a n t i a l number of farmers had l i v e d i n the areas f o r more than twenty years, and the median number of years l i v e d i n the area was i n the 17 to 20 year category. Nine per cent of the respondents were c l a s s i f i e d as f u n c t i o n a l i l l i t e r a t e s , and the median educational l e v e l was eight years. The educational achievement of the spouses was higher, while that of the fathers of the respondents was lower than that of the respondents. The general adult education programs a v a i l a b l e in r u r a l B r i t i s h Columbia had attracted only a small f r a c t i o n of the farm population since only 12 per cent reported p a r t i c i p a t i o n i n such programs. Adult courses in a g r i c u l t u r e attracted a lower number since only 10 per cent reported p a r t i c i p a t i o n i n such programs. T h i r t y - f o u r per cent attended meetings and f i e l d days organized by the D i s t r i c t A g r i c u l t u r i s t to discuss a g r i c u l t u r a l problems. Approximately one-half of the farmers (46 per cent) indicated a desire to receive further education or t r a i n i n g , with the most frequently required t r a i n i n g being farm mechanization, followed by animal and crop husbandry, welding, recreation, carpentry, academic education and courses i n business management. The l i v i n g conditions of majority of the respondents appeared to be s a t i s f a c t o r y , but the median s o c i a l p a r t i c i p a t i o n score was i n the one to f i v e point c l a s s . The farmers l i v e d within easy access to goods and services, with the median distance t r a v e l l e d for a l l of the items studied i n the eleven to f i f t e e n mile category. The median t o t a l farm s i z e claimed was i n the 320 to 639 c l a s s , but the median number of improved acres was between 100 and 159 acres. The farmers who raised l i v e s t o c k reported a median of 20 to 29 - 109 -animal u n i t s . Beef c a t t l e was the p r i n c i p a l a g r i c u l t u r a l product sold by the respondents. The median net farm income reported was i n the $2,000 to $2,999 category, whereas the median gross farm income was $3,000 to $3,999. The median farm value was i n the $40,000 to $49,999 range. The majority of the respondents considered the net farm income reported t y p i c a l of what they u s u a l l y obtain. Seventy-nine per cent o f the farmers owned a l l of t h e i r farmland. The majority of the respondents used unpaid family labour since 62 per cent reported using no h i r e d labour. Some 49 per cent of the respondents had no off-farm job, while the remainder were employed o f f t h e i r farms on a part-time basis f o r varying lenths of time. Over two-fifths (41 per cent) had been farming for more than twenty years, and 19 per cent had been i n a g r i c u l t u r e f or less than s i x years. The respondents appeared to be s a t i s f i e d with a g r i c u l t u r e as an occupation, but the older farmers tended to be more s a t i s f i e d with farming than the younger. The majority of the farmers were o p t i m i s t i c about the future of a g r i c u l t u r e since most of them planned to expand t h e i r farm operations. The most frequently reported change was land c l e a r i n g and drainage, followed by increase i n farm s i z e , increase i n l i v e s t o c k , change of enterprise, change of farm b u i l d i n g , retirement and decrease i n time spent at off-farm jobs. Contact with D i s t r i c t A g r i c u l t u r i s t The farmers generally reported few personal contacts with the D i s t r i c t A g r i c u l t u r i s t , but they used impersonal contacts to a greater extent. The two types of contact reached d i f f e r e n t people. F i f t y - t h r e e - 110 -per cent of the respondents knew the name of the D i s t r i c t A g r i c u l t u r i s t and the average number of contacts, 3.71, during the year preceding t h i s study, included 2.66 impersonal and 1.05 personal contacts. Only 5.9 per cent of the farmers had seven types of contact, while 1.5 per cent had no contact of any kind with the D i s t r i c t A g r i c u l t u r i s t . S i x t y - f i v e per cent of the respondents did not v i s i t the D i s t r i c t A g r i c u l t u r i s t i n h i s o f f i c e , and 65 per cent reported no attendance at a g r i c u l t u r a l meetings and f i e l d days. Some 84 per cent of the household heads were never v i s i t e d by the D i s t r i c t A g r i c u l t u r i s t , and 83 per cent never c a l l e d the D i s t r i c t A g r i c u l t u r i s t on the telephone. Most of the farmers read farm newspaper a r t i c l e s as 93 per cent said they did so. The l e a s t frequently used of the impersonal sources of information, mail from the D i s t r i c t A g r i c u l t u r i s t , was read by 81 per cent of the respondents. The n u l l hypothesis of no s t a t i s t i c a l l y s i g n i f i c a n t d i f f e r e n c e i n the l e v e l of contact which farmers of d i f f e r i n g socio-economic status had with the D i s t r i c t A g r i c u l t u r i s t was rejected for the c h a r a c t e r i s t i c s years of school completed, p a r t i c i p a t i o n i n adult education, number of improved acres and gross farm income. In general, the respondents who had more frequent contacts were characterized by higher education, p a r t i c i p a t i o n i n adult education, larger farms and higher income from a g r i c u l t u r e . The n u l l hypothesis of no s t a t i s t i c a l l y s i g n i f i c a n t d i f f e r e n c e i n the kind of contacts with D i s t r i c t A g r i c u l t u r i s t among farmers of d i f f e r i n g socio-economic status was also rejected for s i x of the seven contact methods. These included v i s i t s to D i s t r i c t A g r i c u l t u r i s t ' s o f f i c e , telephone c a l l s , farm v i s i t s , a g r i c u l t u r a l meetings and f i e l d days, - I l l -mails from D i s t r i c t A g r i c u l t u r i s t and farm newspaper a r t i c l e s . The farm operators who contacted the D i s t r i c t A g r i c u l t u r i s t through the four personal contact methods p a r t i c i p a t e d more in adult education, owned larger farms and earned more from a g r i c u l t u r e than did those who did not. Furthermore, the respondents who v i s i t e d the D i s t r i c t A g r i c u l t u r i s t i n his o f f i c e , and those who attended a g r i c u l t u r a l meet-ings and f i e l d days, had more years of schooling. The farmers who read mail from the D i s t r i c t A g r i c u l t u r i s t and farm newspaper a r t i c l e s owned larger farms and earned more from a g r i c u l t u r e . The respondents who had personal contacts had higher l e v e l s of education and p a r t i c i p a t e d more i n adult education than those who obtained a g r i c u l t u r a l information from the impersonal sources. The education of the spouse was associated with the use of radio and t e l e v i s i o n as a source of a g r i c u l t u r a l information. In general, the more educated farmers and those who p a r t i c i p a t e d more i n adult education programs were1 more l i k e l y to have a l l extension contacts. The use of a l l extension contacts was also s i g n i f i c a n t l y r e l a t e d to such factors as wife's education, distance t r a v e l l e d f o r goods and services, s o c i a l p a r t i c i p a t i o n , l e v e l of l i v i n g , degree of involvement i n farming, net farm income, t o t a l number of acres, number of acres improved, gross farm income, farm value and time spent at off-farm jobs. The socio-economic c h a r a c t e r i s t i c s which were related to the use of contact methods explained from 13 to 27 per cent of the v a r i a t i o n i n the use of these contact methods. P a r t i c i p a t i o n i n adult education, attitudes to change and gross farm income together accounted f o r 13 per cent of the v a r i a t i o n i n farm v i s i t s by the D i s t r i c t A g r i c u l t u r i s t , - 112 -while father's education, l e v e l of l i v i n g , gross farm income and farm value together explained 27 per cent of the v a r i a t i o n in the use of telephone c a l l s to discuss a g r i c u l t u r a l problems. Years of school completed, distance t r a v e l l e d f o r goods and services, s o c i a l p a r t i c i p a t i o n and gross farm income together accounted for 34 per cent of the v a r i a t i o n i n the use of a l l the extension contacts combined. Discussion The r e s u l t s of t h i s study indicate that the impersonal types of contacts with the D i s t r i c t A g r i c u l t u r i s t reached more farmers than did personal contacts. Verner, Dickinson and Alleyne* reported s i m i l a r findings i n another part of the province. The four personal contacts were corr e l a t e d with each other but not with the three impersonal contacts, except i n the case of mail from the D i s t r i c t A g r i c u l t u r i s t . This f i n d i n g suggests that the farmers who had one personal contact were more l i k e l y to have others and to read mails from the D i s t r i c t A g r i c u l t u r i s t ; but these farmers did not use the other two impersonal contacts. This f i n d i n g i s inconsistent with the findings of a study i n 2 another part of the province in which Verner, M i l l e r d and Dickinson reported that there were high c o r r e l a t i o n s among the respondents' use of the four personal and three impersonal information sources. The f i n d i n g of t h i s other study implies that the same farmers were being served by the d i f f e r e n t sources of information. Level of formal education completed and p a r t i c i p a t i o n i n adult education were highly correlated with personal contacts, but not with 1 Verner, Dickinson, and Alleyne, op_. c i t . p. 59 2 Verner, M i l l e r d , and Dickinson, op_. c i t . p. 62 - 113 -impersonal ones. This c o r r e l a t i o n suggests that the farmers with more years of schooling and more active p a r t i c i p a t i o n i n adult education had more personal contacts with the D i s t r i c t A g r i c u l t u r i s t . Rogers and Capener"" reported s i m i l a r findings i n t h e i r Ohio study with respect to l e v e l of education. The association between l e v e l of contact and educational achievement reported i n t h i s study i s also consistent with 4 the findings of the Washington study by Slocum, Brough and Straus. Of the t h i r t e e n socio-economic factors which showed c o r r e l a t i o n with the use of extension contacts i n t h i s study, two c h a r a c t e r i s t i c s , i . e . years of schooling and farm income, had been i d e n t i f i e d by Rogers and Capener"* to have s i m i l a r association, but they d i d not d i f f e r e n t i a t e 'net farm income' from 'gross farm income' as i t was done in t h i s study. The review of l i t e r a t u r e f a i l e d to f i n d any mention of the extent to which the farmers' c h a r a c t e r i s t i c s , which were associated with extension contacts, accounted f o r v a r i a t i o n i n such contacts. The lack o f knowledge with respect to t h i s problem may account f o r the low proportion of v a r i a t i o n i n contact explained by the factors included i n t h i s study. CONCLUSIONS In general, the findings i n t h i s study are consistent with those of previous research on the socio-economic c h a r a c t e r i s t i c s of farm 3 Rogers and Capener, op_. c i t . p. 37 4 Slocum, Brough and Straus, op_. c i t . p. 27 5 Rogers and Capener, op_. c i t . p. 41 - 114 -respondents, and the types of contact they had with the D i s t r i c t A g r i c u l t u r i s t . Contacts between farmers and the D i s t r i c t A g r i c u l t u r i s t i n r u r a l B r i t i s h Columbia were widely d i s t r i b u t e d throughout the farm population, but c e r t a i n categories of people were more l i k e l y than others to be contacted. This fi n d i n g suggests the need for continuous study of the contact of farm population with the extension workers, in order to evaluate the effectiveness of the Service programs. Studies following a systematic procedure, such as the one reported here, are useful i n t h i s respect. The study of the r e l a t i o n s h i p between the socio-economic c h a r a c t e r i s t i c s of farmers, and t h e i r contacts with the extension workers, can also be a us e f u l t o o l i n improving the type of contact through which farmers receive a g r i c u l t u r a l information. In r u r a l B r i t i s h Columbia, the farmers who had higher l e v e l of education had more personal contacts than those with less education. This f i n d i n g suggests the need for a d d i t i o n a l educational programs for the less educated farmers, i f they are to take advantage of the services provided through personal contacts by the extension change agents. The present study revealed that none of the socio-economic c h a r a c t e r i s t i c s studied, s i n g l y or combined, accounted for more than 27 per cent of such v a r i a t i o n . This f i n d i n g indicates a need f o r furthe r studies i n t h i s area to examine the c h a r a c t e r i s t i c s , including those of the extension workers, which may influence a farmer's decision to seek assistance. When such c h a r a c t e r i s t i c s which explain a high proportion of the v a r i a t i o n i n extension contacts are known, more e f f e c t i v e extension work would be made po s s i b l e . - 115 -BIBLIOGRAPHY - 116 -Ai GOVERNMENT PUBLICATIONS Dominion Bureau of S t a t i s t i c s , Canada Year Book, Ottawa, Queen's P r i n t e r , 1965. Dominion Bureau of S t a t i s t i c s , Census of Canada, 1966, Advance B u l l e t i n A-4, Ottawa, Queen's P r i n t e r and C o n t r o l l e r of Stationery, 1967, Dominion Bureau of S t a t i s t i c s , Eighth Census of Canada, 1941, Ottawa, Queen's P r i n t e r , Province of B r i t i s h Columbia, Department of A g r i c u l t u r e , V i c t o r i a , A g r i c u l t u r a l Outlook Conference, Report of Proceedings, 1966. Province of B r i t i s h Columbia, Department of Lands, Forests, and Water Resources, B u l l e t i n Area Nos. 6, 7, 8 and 10, V i c t o r i a , Queen's P r i n t e r , 1966. B. GENERAL WORKS Brunner, Edmund deS., e_t a_l_. An Overview of Adult Education Research Chicago, Adult Education Association of U.S.A., I l l i n o i s , 1959. Brunner, Edmund deS., The Growth of A Science, New York, Harper and Brothers Publishers, 1957. Kelsey, L i n c o l n D. and Cannon C. Hearne, Co-operative Extension Work, Ithaca, New York, Comstock Publishing Associates, 1963. Kendall, M.G., and S.B. Babington, Tables of Random Sampling Numbers, London, Cambridge University Press, 1951. Lionberger, Herbert F., Adoption of New Ideas and Prac t i c e s, AmeSj The Iowa State University Press, Iowa 1960. Mellor, John W., The Economics of A g r i c u l t u r a l Development, Ithaca, New York, Cornell U n i v e r s i t y Press, 1966. - 117 -C, SPECIFIC WORKS Brayfield, A.H. and H.F. Rothe,"An Index of Job Satisfaction", Journal of Applied Psychology, 35: 307-311, October, 1951. Bryant, Ellen S., Socio-economic Status Indexes for Mississippi Counties, Mississippi State University Agricultural Experiment Station Bulletin 724, April, 1966. Cannon, K.L., "The Relationships of Social Acceptance to Socio-economic Status and Residence among High School Students", Rural  Sociology 22: 142-148, June, 1957. Chapin, F. Stuart, "A Quantitative Scale for Rating the Home and Socic.i Environment of Middle Class Families in an Urban Community: A F i r s t Approximation of the Measurement of Socio-Economic Status", The Journal of Educational Psychology, 19: 99-111, 1928. Chapin, F. Stuart, "Social Participation Scale", Minneapolis, Minnesota, University of Minnesota Press, 1937, reprinted in F. Stuart Chap in, Experimental Designs in Sociological Resaarch, (revised edition), New York: Harper and Brothers, 1955, pp. 276-278. Coleman, Lee, "Differential Contact with Extension Work in a New York Rural Community", Rural Sociology, 16: 207-216. 1951. Dempster, J.H.R., A.E. Gagne, and R. Hogan, Trip: Triangular Regression Package, Vancouver, Computing Centre, University of British Columbia, April, 1965. Freedman, Ronald, Pascal K Whelpton, and John W. Smit, "Socio-economic Factors in Religious Differentials in F e r t i l i t y " , American Sociological Review. 26: 608-614, 1961. - 118 -Fenley, John M. and S.K. Taiwo Williams, Background for Extension Workers i n Western N i g e r i a . Ibadan, M i n i s t r y of Ag r i c u l t u r e and Natural Resources Training B u l l e t i n No. 3, Ni g e r i a , February, 1964. Har r i s , Mary..Jordan and Josephine Staab, "The Relationship of Current Net Income to the Socio-economic Status of Southern Farm Fa m i l i e s " , Rural Sociology. 16: 353-358, 1951. Hurd,Lome, "What Farmers Expect of Extension", Proceedings of the  Canadian Society of Rural Extension. Sixth Annual Meeting and Convention, November, 1965. I n g e r s o l l , Hazel and L.H. Scott, "A Group Scale for the Measurement of S o c i a l , C u l t u r a l and Economic Status of Farm Families of the Middle West", Rural Sociology. 9: 349-363, 1944. Job, Claude H.,"Roles of A g r i c u l t u r a l Extension Agents i n B r i t i s h Columbia", (unpublished, M.S.A. Thesis, Department of A g r i c u l t u r a l Economics, U n i v e r s i t y of B r i t i s h Columbia, 1965^) Keesing, Paul B., "A Study of P r o v i n c i a l A g r i c u l t u r a l Extension Services i n Canada", (unpublished M.S.A. Thesis, Department of A g r i c u l t u r a l Economics, U n i v e r s i t y of B r i t i s h Columbia, 1965} Klapper, Joseph T., The S o c i a l E f f e c t s of Mass Communication, i n Wilbur Schramm (ed.), The Science of Human Communication. New York, Basic Books, Inc., Publishers, 1963. Lionberger, H.F. Low-income Farmers In MiagourA, Their Contacts with P o t e n t i a l Sources of Farm and Home Information, Columbia, Missouri A g r i c u l t u r a l Experiment Sta t i o n Research B u l l e t i n 441, 1949. - 119 -Nam, Charles B. and Mary G. Power, "Variations i n Socio-economic Structure by Race, Residence and the L i f e Cycle", American S o c i o l o g i c a l Review, 30: 97-103, 1965. Parish, Ross, "Extension Services and the Grazier on the South-West Slope", Review of Marketing and A g r i c u l t u r a l Economics, New South Wales, D i v i s i o n of Marketing and A g r i c u l t u r a l Economics, Department of A g r i c u l t u r e , 24: 222-235, March, 1956. Rogers, Everett M. and Harold R. (Capener, The County Extension Agent  and His Constituents, Wooster, Ohio A g r i c u l t u r a l Experiment Station Research B u l l e t i n 858, June, 1960. Rogers, Everett M. and A. Eugene Havens, Extension Contact of Ohio  Farm Housewives, Wooster, Ohio A g r i c u l t u r a l Experiment Station, Research B u l l e t i n 890, Ohio, November, 1961. Scantland L o i s , C.A. Svinth, and M.J. Taves, A Square Look at Extension  Work i n Spokane County. Pullman, Extension B u l l e t i n No. 463, Washington, June 1952. Schuler, Edgar A., " S o c i a l and Economic Status i n a Louisiana H i l l s Community", Rural Sociology, 5: 69-87, 1940. Sewell, W.H. The Construction and Standardization of a Scale f o r the  Measurement of the Socio-economic status of Oklahoma Farm  Fami l i e s , S t i l l w a t e r , Oklahoma A g r i c u l t u r a l and Mechanical College Technical B u l l e t i n No. 9, Oklahoma, 1940. Sewell, W.H., "A Short Form of the Farm Family Socio-economic Status Scale", Rural Sociology, 8: 161-170, June 1943. Slocum, Walter L, Owen L. Brough J r . , and Murray A. Straus, Extension  Contacts, Selected C h a r a c t e r i s t i c s , Practices and Attitudes  of Washington Farm Families. Washington, I n s t i t u t e of A g r i c u l t u r a l Sciences State College of Washington, A g r i c u l t u r a l Experimental Station B u l l e t i n 584, A p r i l , 1958. - 120 -Siemens, L.B, and J.R. Weir, "The R e s p o n s i b i l i t i e s of the U n i v e r s i t i e s " , Proceedings of the Canadian Society of Rural Extension, June 1961 , pp. 70-79, January, 1962. Verner, Coolie, "Adult I l l i t e r a c y , 1921-1961", Journal of Education of the Faculty of Education of the Un i v e r s i t y of B r i t i s h Columbia, Vancouver, 10: 99-109, A p r i l , 1964. Verner, Coolie arid Frank W. M i l l e r d , Adult Education and the Adoption of Innovations, Rural S o c i o l o g i c a l Monograph # 1, Vancouver, Department of A g r i c u l t u r a l Economics, University of B r i t i s h Columbia, 1966. Verner, Coolie, Frank W. M i l l e r d , and Gary Dickinson, A Socio-economic  Survey of the Prince George Special Sales Area, Vancouver, Faculty of Education, U n i v e r s i t y of B r i t i s h Columbia, August, 1967. Verner, Coolie, Planning and Conducting a Survey: A Case Study, Rural Development Branch, Ottawa, Department of Forestry and Rural Development, October, 1967. Verner, Coolie and Peter M. Gubbels, The Adoption or Rejection of Innovations by Dairy Farm Operators i n the Lower Fraser Valley, Ottawa, A g r i c u l t u r a l Economics Council of Canada, P u b l i c a t i o n No. 11, 1967. Verner, Coolie, Gary Dickinson and E. Patrick Alleyne, A Socio-economic  Survey of the East Kootenay Area i n B r i t i s h Columbia, Vancouver:, Faculty of Education, University of B r i t i s h Columbia, January, 1968. - 121 -Verner, Coolie and Gary Dickinson, A Socio-economic Survey of the Pemberton Valley, Vancouver, Faculty of Education, University of B r i t i s h Columbia^ A p r i l , 1968. Wilkening, E.A. "Sources of Information f o r Improved Farm Pra c t i c e s " , Rural Sociology, 15: 19-30, 1950. Wilkening, E.A. and Ralph K. Huitt, " P o l i t i c a l P a r t i c i p a t i o n Among Farmers as Related to Socio-economic Status and Perception of the P o l i t i c a l Process", Rural Sociology, 26: 395-408, 1961. Wilkening, E.A., J o r i T u l l y , and Hartley Presser, "Communication and Acceptance of Recommended Farm Practices Among Dairy Farmers of Northern V i c t o r i a " , Rural Sociology, 27: 116-197, 1962. Wilson, Meredith, C , How and to What Extent i s the Extension Service Reaching Low-income Farm Families, Washington, Extension Service. C i r c u l a r 375, United States Department of Ag r i c u l t u r e , Decembe" 1941. - 122 -APPENDIX I The interview schedule with univariate frequency d i s t r i b u t i o n s added for basic socio-economic c h a r a c t e r i s t i c s and frequency of extension contacts. - 123 -Respondent's Number C.L.I. Region A.R.D.A./U.B.C./67 SOCIO-ECONOMIC INTERVIEW SCHEDULE Respondent's Name Address Record of V i s i t s : Date Time Comments F i r s t Second Third . •  Enumerated by: F i e l d Check by: Coded by: Checked by: D i s t r i c t Lot Number, Respondent's Location on Lot, and Land Use (Sketch). - 124 -Column Code Frequency No. Respondent's Number N.T.S. Map Number C.L.I. Region Socio-economic sub-region Regional D i s t r i c t Sex of Respondent 1,3. 4. 5,9. 10,11. 12. 13. 1. Male 14. 1 0 •0 2. Female 2 256 100 START INTERVIEW HERE 1. How many people are l i v i n g i n your home at the present time? 15. None 0 0 1 27 10 2 40 16 3 38 15 4 46 18 5 32 12 6 30 12 7 17 7 8 12 5 9 9 3 A 2 ) B 2 ) 2 C 1 ) 2. What i s your marital status: 1. Single 16. 1 37 14 2. Married 2 214 84 3. Widowed, divorced, or separated 3 5 2 3. What i s your age? 1. 15 - 24 17. 1 5 2 2. 2 5 - 3 4 2 26 10 3. 35 - 44 3 78 30 4. 45 - 54 4 73 29 5. 55 - 64 5 50 20 6. 65 and over 6 24 9 4. How many years of schooling did you complete? 1. 5 or les s 18. 1 24 9 2. 6 - 7 2 46 18 3. 8 3 103 40 4. 9 - 1 1 4 50 19 5. 12 5 24 9 6. 13 - 15 (1-3 years u n i v e r s i t y ) 6 5 3 "7 7 L 2 - 125 -Column Code Frequency No. % (a) Did you have any t r a i n i n g a f t e r you l e f t school? 1. yes 19. 1 76 30 2. no 2 178 69 0. no response 0 2 1 (b) I f yes, what were you trained in? 20,22 How many years of schooling did your wife complete? 1. 5 or less 23. 1 11 4 2. 6 - 7 2 26 10 3. 8 3 51 20 4. 9 - 1 1 4 72 28 5. 12 5 39 15 6. 1 3 - 1 5 (1-3 years u n i v e r s i t y ) 6 18 7 7. 16 or more (degree or above) 7 0 0 0. no response 0 39 15 Did your wife have any other t r a i n i n g a f t e r she l e f t school? 1. yes 24 1 47 18 2. no 2 167 65 0. no response 0 42 17 (b) I f yes, what was she trained in? 25,27. (a) Have you taken any adult education courses i n the l a s t three years? (Interviewer explain). (b) 1. yes 28. 1 30 12 2. no 2 226 88 Was t h i s course r e l a t e d to your job? 1. didn't take any course 29. 1 213 83 2. yes 2 24 9 3. no 3 7 3 0. no response 0 12 5 many ch i l d r e n do you have? 30. 0 43 17 1 24 9 2 42 17 3 42 17 4 45 18 5 19 7 6 16 6 7 11 4 8 3 1 9 11 4 - 126 -Column Code Frequency No. Of those c h i l d r e n who have l e f t school, a. How many completed grade 12? 31 b. How many did not complete grade 12? 32 How many of your c h i l d r e n have moved to another area? 33 9. What was your father's occupation?_ 34,36 10. How many years of school did your father complete? 1. don't know 2. 5 or less 3. 6 - 7 4. 8 5. 9 - 1 1 6. 12 7. 1 3 - 1 5 (1-3 years u n i v e r s i t y ) 8. 16 or more (degree or above) 37 1 2 3 4 5 6 7 8 112 46 27 46 10 9 3 3 44 18 11 18 4 3 1 1 Did your father have any other t r a i n i n g a f t e r he l e f t school? 1. don't know 2. yes 3. no 38 1 2 3 87 45 124 34 18 48 b. I f yes, what was he trained in? 39,41 11. Where were you born? 1. This area 2. B r i t i s h Columbia 3. Canada 4. United States 5. United Kingdom 6. Other (specify) 42 1 2 3 4 5 6 40 22 112 26 15 41 16 8 44 10 6 16 12. How long have you l i v e d i n th i s area? 1. two years or less 2. 3 - 5 years 3. 6 - 1 0 years 4. 11 - 16 years 5. 1 7 - 2 0 years 6. more than 20 years 7. e n t i r e l i f e t i m e 43 1 2 3 4 5 6 7 12 28 19 32 26 99 40 5 11 7 13 10 39 16 - 127 -Column Code Frequency No. X 13. Where did you l i v e before coming to t h i s area? 1. Not applicable ( l i v e d i n area f o r l i f e t i m e ) 44 2. B r i t i s h Columbia 3. Canada 4. United States 5. United Kingdom 6. Other (specify) 1 41 16 2 57 22 3 116 45 4 17 7 5 2 1 6 23 9 14. Now, I would l i k e to your family t r a v e l , following s e r v i c e s : ask you how f a r you and in miles, to receive the 1. food purchases 45,47 2. cl o t h i n g purchases 48,50 3. medical care 51,53 4. church 54,56 5. elementary school 57,59 6. secondary school 60,62 7. post o f f i c e 63,65 8. work 66,68 Tot a l Distance + = Divided by = 69,71 Distance t r a v e l l e d score 1. 0 -• 5 miles 72 1 42 16 2. 6 -• 10 2 71 28 3. 11 - 15 3 64 25 4. 16 - 20 4 31 12 5. 21 - 25 5 20 8 6. 26 - 30 6 11 4 7. 31 - 35 7 5 2 8. 36 - 40 8 3 1 9. 41 or more 9 9 4 15. - 28 (SEWELL SCALE, SHORT FORM) The next few items are concerned with some of the things that your family owns ITEMS 15. Construction of house: a. b r i c k , stucco, or frame i n good condition (5) 73 5 b. unpainted frame or other i n poor condition (3) 3 - 128 -Column Code Frequency No. % 16. Room-person r a t i o : Number of rooms divided by number of persons equals Ratio: a. below 1.00 (3) 74 3 b. 1.00 - 1.99 (5) 5 c. 2.00 and up (7) 7 17. Li g h t i n g f a c i l i t i e s : a. e l e c t r i c t (8) 75 8 b. gas,mantle, or pressure (6) 6 c. o i l lamps, other or none (3) 3 Respondent's Number 18. Water piped into house: a. yes (8) b. no (4) 19. Power washer: a. yes (6) b. no (3) 20. R e f r i g e r a t i o n : a. mechanical (8) b. ice (6) c. other or none (3) 21. Radio: a. yes (6) b. no (3) 22. Telephone: a. yes (6) b. no (3) 23. Automobile (includes pickup truck) a. yes (6) b. no (2) 1,3 4 START DATA CARD 2 2 8 4 10 8 6 3 6 3 6 3 6 2 - 129 -Column Code Frequency No. 7o 24. - Family takes d a i l y or weekly newspaper: a. yes (6) 11 6 b. no (3) 3 25. Wife's education: grades completed (see question # 5): a. 0 to 7 (2) 12 2 b. 8 (4) 4 c. 9 - 11 (6) 6 d. 12 (7) 7 e. 13 and up (8) 8 26. Husband's education: grades completed (see question # 4): a. 0 to 7 (3) 13 3 b. 8 (5) 5 c. 9-11 (6) 6 d. 12 (7) 7 e. 13 and up (8) % 27. Husband attends church or Sunday School at le a s t once a month: a. yes (5) 14 5 b. no (2) 2 28. Wife attends church or Sunday School at l e a s t once a month: a. yes (5) 15 5 b. no (2) 2 Percentage Score T o t a l = 16,18 1. Under 20 19 1 0 0 2. 21 - 30 2 0 0 3. 31 - 40 , 3 0 0 4. 41 - 50 4 0 0 5. 51 - 60 5 6 2 6. 61 - 70 6 27 11 7. 71 - 80 7 72 28 8. 81 - 90 8 115 45 9. Over 90 9 36 14 - 130 -Column Code Frequency No. % 29. (CHAPLIN SCALE) Would you please t r y to r e c a l l the names of a l l the organizations that you have belonged to i n the past year. (Do not include attendance at church) Name of Organiza-t i o n 2.Atten-dance \ 3. Finan- \ 4.Member c i a l con- of Commi-t r i b u t i o n tee 5. Of f i c e s held l . ! 2. 1 i ; i 3. i 1 • ' i 5. ! i i 6. ! I 7. i j 8. ! i T o t a l (XI) I ! i (X2) j (X3) ; (X4) ; (X5) i i Total P a r t i c i p a t i o n Score = 20,21 P a r t i c i p a t i o n 0 Score 22 1 120 47 1 - 5 2 15 6 6 - 1 0 3 49 19 11 - 15 4 19 7 16 - 20 5 19 7 21 - 25 6 12 5 26 - 30 7 12 5 31 - 35 8 4 2 Over 35 9 6 2 - 131 -3 0 . - 4 9 . I would l i k e to ask you a few questions regarding how you f e e l % about r u r a l l i f e and t h i s area. .3 Please give your reaction to each <S statement, using the f i v e responses on the card. 30. Rural l i f e i s too i s o l a t e d and too lonesome. 23. 31. Since c i t y people have educational oppor-t u n i t i e s within easy reach, I think they have an advantage over r u r a l people 24. 32. This area i s a desirable one i n which to l i v e . 25. 33. I would not mind leaving here in order to make a su b s t a n t i a l advance i n my occupation. 26. 34. I do not wont my new job which involves more r e s p o n s i b i l i t y . 27. 35. I would not leave t h i s area under any circumstances. 28. 36. Learning a new routine would be very d i f f i c u l t f o r me. 29. 37. The future of t h i s area looks bright. 30. 38. I would f i n d i t very d i f f i c u l t to go to school to learn new s k i l l s . 31 39. The people here f i n d i t very easy to get together on community projects. 32. 40. There are not enough jobs a v a i l a b l e here. 33. 41. I believe the r u r a l environment i s h e a l t h i e r than that of the c i t y . 34. 42. I w i l l need further education to ensure my-s e l f adequate employment i n the future. 35. 43. No one seems to care how t h i s area looks. 36. 44. I believe that people who want new and e x c i t i n g experiences must leave the r u r a l areas and go to the c i t i e s . 37. 132 45. I would be w i l l i n g to give up my spare-time to further my education. 46. This area w i l l never seem l i k e home to me. 47. The country o f f e r s more enjoyment of l i v i n g than does the c i t y . 48. I have no desire to learn a new trade. 49. I think that, on the average, the standard of l i v i n g of r u r a l people i s below that of others in Canada. o o 38. 39. 40. 41. 42. Tot a l Rural Score (R) 43,44 Tota l Area Score (A) 45,46 Total Change Score (C) 47,48 50. What was your p r i n c i p a l occupation i n 1966? co u <u 60 QJ n U CO 60 • H 01 X " x >> OJ <u >> 1-1 X l r-l 60 • H u 60 c QJ o 60 C o CD CO O u U X . 60 M u 60 c • i - l 4J w < Q C O 5 4 3 2 1 1 2 3 4 5 5 4 3 2 1 1 2 3 4 5 49,51 C A R C Code 51. Were you self-employed? 1. yes 52 1 2. no 2 52. In what industry did you work? 1. agr i c u l t u r e 53 1 2. f o r e s t r y 2 3. mining 3 4. service and transportation 4 5. secondary ag r i c u l t u r e 5 6. secondary f o r e s t r y 6 7. recreation 7 8. construction 8 9. other 9 53. How many years had you been working i n t h i s occupation? 1. 2 or less 54 1 2. 3 - 5 2 3. 6 - 10 3 4. 1 1 - 1 5 4 5. 1 6 - 2 0 5 6. 21 - 25 6 7. 26 and over 7 0. no response 0 Frequency No. % 21 29 31 35 34 18 86 2 8 11 12 14 13 7 34 2 » 188 • Column Code No. Frequency % 54. Is t h i s the same job you are working i n now? 1. yes 2. no 55. 55. I f not: (a) What job are you working i n now? 56,58 55. (b) Are you s e l f employed? 56. 57. 1. yes 59. 1 2. no 2 (c) What industry are you working in? 1. a g r i c u l t u r e 60. 1 2. f o r e s t r y 2 3. mining 3 4. servdce and transportation 4 5. secondary a g r i c u l t u r e 5 6. secondary f o r e s t r y 6 7. recr e a t i o n 7 8. construction 8 9. other 9 Did you have a secondary occupation or source of income i n 1966? (For farmers - P r i n c i p a l off-farm job). 1. yes 61. 1 123 48 2. no 2 128 50 0. no response 0 5 2 If yes, what was your secondary occupation? 62,64 Were you self-employed i n your secondary occupation? 1. yes 65 1 101 39 2. no 2 25 10 0. no response 0 139 51 In what industry was your secondary occupation? 1. f o r e s t r y 66. 1 12 5 2. a g r i c u l t u r e 2 91 36 3. mining 3 0 0 4. service and transportation 4 10 4 5. secondary a g r i c u l t u r e 5 2 1 6. secondary f o r e s t r y 6 2 1 7. recreation 7 0 0 8. cons tr u c t iou 8 3 1 9. other 9 3 1 0. none 0 133 52 - 134 -Column Code Frequency No. % 59. Did you have a t h i r d job i n 1966? (For farmers - secondary off-farm job). 1. yes 67. 1 11 4 2. no 2 245 96 60. How many months did you work i n 1966? 68 1 0 0 2 1 0 3 0 0 4 0 0 5 0 0 6 4 2 7 2 1 8 7 3 9 5 2 A 7 3 B 3 1 C 225 88 0 2 1 (FOR INTERVIEWER USE ONLY) Respondent may be c l a s s i f i e d as: 1. farmer only 69. 1 126 49 2. farmer p r i n c i p a l l y with secondary off-farm job 2 31 12 3. non-farmer p r i n c i p a l l y with farming as secondary job 3 96 38 4. non-farm only 4 - -5. no job or out of work 5 - -6. s t a r t i n g a farm 6 3 1 61. - 69. (BRAYFIELD AND ROTH'S INDEX OF JOB SATISFACTION - REVISED) I would l i k e to f i n d out how you f e e l about your job. Please reply to each statement using the f i v e phrases on t h i s card. (Hand respondent card). 61. My job i s l i k e a hobby to me. 62. I t seems that my friends are more interested i n t h e i r jobs than I am. 63. I enjoy my work more than my l e i s u r e time. 64. I .am often bored with my job. U 60 co >% 0) <u a) T> OJ r - l OJ 60 ••-1 60 h C OJ o 60 C 60 O OJ 0J CO O CO U u •o w i-l M 4J 60 c •ft 4J ---I C O < S Q C O Q 70. 5 4 3 2 1 71. 1 2 3 4 5 72, 5 4 3 2 1 73. 1 2 3 4 5 65. I f e e l f a i r l y well s a t i s f i e d with my job. 74. 5 4 3 2 1 - 135 -Column 66. I f e e l tiv.t my job i s no more i n t e r e s t i n g than others I could get. 67. I d e f i n i t e l y d i s l i k e my work, 68. Each 'Icy of work seems l i k e i t w i l l never end. 69. I f i n d r e a l enjoyment i n my work. Respondent 1s Number Tota l Score 75. 76. 77. 78. 1,3. 4. 5,6. 1 1 1 5 2 2 2 4 3 3 3 3 4 4 START DATA CARD 3 Tot a l Scale Score: 9 - 12 7. 1 0 0 13 - 16 2 0 17 - 20 3 0 J 21 - 24 4 3 ** 25 - 28 5 25 10 29 - 32 6 64 25 33 - 36 7 134 52 27 - 40 8 22 9 41 and over 9 3 1 no response 0 5 2 Have you worked at any job other than the one(s) you are now working at? 1. yes 8. 1 183 71 2. no 2 73 29 71. If yes, what s p e c i f i c jobs have you had for more than s i x months: Previous job Next Previous job Next Previous job Next Previous job Next Previous job 9,11 12,14 15,17 18,20 21,23 136 -Column Code Frequency No. "%' 72. What was your approximate net nincome from your p r i n c i p a l occupation i n 1966? (for farmers - net farm income) Amt. 24,28 Code. 29 73. What was your approximate net income from your other occupations i n 1966? Amt. 30,34 Code. 35 74. Did any other family members l i v i n g at home earn income i n 1966? If yes, how much was t h i s income? a. wife Amt. 36,40 Code. 41 b. sons or daughters Amt. 42,46 •Code. 47 c. others Amt. 48,52 Code. 53 START DATA CARD 4 Respondent's Number 1,3 4 4 76. Did you or members of your family receive income from other sources i n 1966? If yes, how much was t h i s income? Amt. 5,9 Code. 10 Amt. 11,15 Code. 16 77. What would you estimate was the value of produce ra i s e d and consumed by yourself l a s t year? quantity vglue Amt. 17,21 . n i l k Code 22 butter  eggs _ meat \ garden produce a. rent, i n t e r e s t , or dividends b. unemployment insurance or welfare payments To t a l - 137 -Column Code Frequency No. X 78. Have you been unemployed during the past 3 years? (For farmers - Have you sought off-farm work i n the l a s t three years and been unable to obtain any?) 79. 80. A, 1. yes 23. 1 37 14 2. no 2 219 86 B, If yes, for how long? 1. less than a month 24. 1 2 1 2. 1 - 6 2 12 5 3. 6 - 12 3 15 6 4. 13 - 18 4 6 2 5. 18 - 24 5 0 0 6. 24 - 30 6 0 0 7. 30 - 36 7 2 1 0. no response 0 219 85 If you were unemployed, what was the cause or nature of your unemployment? 1. seasonal l a y o f f s 25. 1 17 7 2. health d i s a b i l i t i e s 2 6 2 3. no work a v a i l a b l e 3 8 3 4. work ava i l a b l e but i n s u f f i c i e n t s k i l l to get work 4 1 i 5. family reasons 5 1 JL 6. seeking new p o s i t i o n 6 2 1 7. other 7 3 1 0. no response 0 218 85 Would you l i k e to take some kind of further education or training? 1. yes 26. 1 117 46 2. no 2 117 46 3. undecided 3 18 7 0. no response 0 4 1 I f yes, what kind of t r a i n i n g would you be interested in? 27,29 81. Do you own t h i s land, own part and rent part, or rent i t e n t i r e l y ? 1. own 30. 1 201 79 2. own more than h a l f and rent the remainder 2 21 8 3. rent more than h a l f and own the remainder 3 23 9 4. rent i t e n t i r e l y 4 1 ) ^ 5. manager 5 1 ) 6. other 6 9 3 - 138 -Column Code Frequency No. % 82. How did you acquire t h i s land? 1. do not own land 31 1 5 2 2. from the Crown-purchase 2 37 14 3. from the Crown-pre-empt or homestead 3 27 11 4. bought as i s 4 78 30 5. in h e r i t e d as a going concern 5 20 8 6. through marriage 6 0 0 7. pri v a t e unimproved 7 42 16 8. i n a c t i v e improved 8 28 11 9. other 9 15 6 0. no response 0 4 2 83. How many acres of land do you own here? Amt. 32,35 _ Code. 36 84. How many acres have not been cleared but are grass meadows or natural pastures? Amt. 37,40 Code. 41 . 85. How many acres have been cleared? Amt. 42,45 Code. 46 ~ 86. How many acres are i n bush or timber? Amt. 47,50 Code. 51 (FOR AREAS AFFECTED BY FLOODING ONLY) 87. Do you expect to be relocated because of flooding from dam storage reservoirs? 1. yes 52 1 2. no 2 88. I f so, where do you expect to be moved to? 53,57 - 139 -Co lumn Code Frequency No. % THE FOLLOWING QUESTIONS ARE TO BE ASKED OF FARMERS ONLY 89. What i s your p r i n c i p a l a g r i c u l t u r a l product sold? (that i s , the product from which you obtained the largest gross revenue). 1. dairy produce (milk or cream shipper) 58 1 35 14 2. beef 2 103 40 3. sheep 3 2 1 4. other l i v e s t o c k 4 '7 3 5. f r u i t and vegetables (including potatoes; 5 8 3 6. other f i e l d crops 6 89 35 7. mixed 7 3 1 8. woodlot products 8 2 1 9. eggs or poultry 9 4 2 0. no response 0 3 1 B. What other a g r i c u l t u r a l products do you s e l l ? (If more than one response, check second response i n B (2) 89. B. (2) 1. dairy produce 59. 1 14 5 2. beef 2 37 14 3. sheep 3 2 1 4. other l i v e s t o c k 4 7 -J 5. f r u i t and vegetables 5 6 •7 6. f i e l d crops 6 35 14 7. mixed 7 0 0 8. woodlot products 8 5 2 9. other 9 13 5 0. none 0 137 54 1. dairy products 60 1 0 0 2. beef 2 2 1 3. sheep 3 0 0 4. other l i v e s t o c k 4 2 1 5. f r u i t and vegetables 5 2 1 6. f i e l d crops 6 5 2 7. mixed 7 0 0 8. woodlot products 8 2 1 9. other 9 4 2 0. none 0 239 93 - 140 -Column Code Frequency ' : ; • • No. % 90. What was the average number of animals on your farm l a s t year? dair y animals Total Animal Units 61,63. cows h e i f e r s T o t a l Animal Units calves b u l l s 1. no animals 64. 1 41 16 2. less than 10 2 52 24 beef animals 3. 10 - 19 3 37 17 4. 20 - 29 4 24 11 cows 5. 30 - 39 5 22 10 h e i f e r s 6. 40 - 49 6 15 7 yearlings 7. 50 - 59 7 13 6 calves 8. 60 - 79 8 14 7 b u l l s 9. 80 and over 9 34 16 0. response 0 4 2 horses sheep swine ch ickens. 91. What was your approximate gross farm income i n 1966? Amt. 65,70. Code. 71 92. Would you consider 1966 a t y p i c a l year, or was i t better or poorer than average with respect to net farm income? 1. t y p i c a l 72. 1 118 46 2. better than average 2 40 16 3. poorer than average 3 85 33 4. not farming previous to 1966 4 10 4 0. no response 0 3 1 93. What would you be w i l l i n g to pay to own and operate t h i s farm as a going concern (every thing included)? Amt. 73,78. Code. 79 - 141 -Column Code Frequency No. % 94. Do you use h i r e d labour f o r your farm operation, and, i f so, on what basis do you h i r e labour? •1. 2 . 3 . 4 . 5 . 0 , no hired labour used 80. h i r e d labour used only on a seasonal basis for less than one man-month hire d labour used only on a seasonal basis for more than one man-month hi r e d labour on a year-round basis some year-round labour, some seasonal no response 3 4 5 0 158 49 33 5 6 5 62 19 13 2 2 2 Respondent's Number START DATA CARD 5 1,3 95 . Did you work o f f your farm l a s t year? If yes, how many weeks d i d you spend working o f f farm? 1. no off-farm work 5. 1 126 49 2. less than 4 weeks 2 14 5 3 . 4 - 9 3 11 4 4 . 10 - 13 4 21 8 5 . 13 - 25 5 19 7 6 . 26 - 39 6 23 9 7. 40 - 52 7 42 16 Do you use unpaid family labour i n your farm operation? I f yes, how much? a. 1. yes 6. 1 139 54 2. no 2 115 45 o . no response 0 2 1 b. 1. l e s s than 1 man-day per month 7. 1 5 2 2 . 1 - 5 2 30 12 3 . 6 - 10 3 . 25 10 4 . 11 - 15 4 32 12 5 . more than 15 5 51 20 0 . no response 0 113 44 Who i s your D i s t r i c t A g r i c u l t u r i s t ? 1. r i g h t 8. 1 136 53 2. wrong 2 8 3 3. don 1t know 3 112 44 - 142 -Column Code Frequency No. 7a 98. Have you v i s i t e d your D i s t r i c t A g r i c u l t u r i s t i n h i s o f f i c e during the past year? I f so, how many times? 1. None 9. 1 166 65 2. 1 or 2 2 62 24 3. 3 or 4 3 18 7 4. 5 or more 4 10 4 99. Have you consulted your D i s t r i c t A g r i c u l t u r i s t about a farm matter over the telephone during the past year? I f so, how many times? 1. None 10. 1 212 83 2. 1 or 2 2 29 11 3. 3 or 4 3 7 3 4. 5 or more 4 8 3 100, Did your D i s t r i c t A g r i c u l t u r i s t v i s i t you during the past year about a farm matter? If so, how many times? 1. None 11. 1 214 84 2. 1 or 2 2 36 14 3. 3 or 4 3 5 2 4. 5 or more 4 •1 0 101. Have you attended l o c a l meetings or f i e l d days sponsored by the D i s t r i c t A g r i c u l t u r i s t during the past year? I f so, how many? 1. None 12. 1 169 66 2. 1 or 2 2 59 23 3. 3 or 4 3 20 8 4. 5 or more 4 8 3 102. Did you read c i r c u l a r l e t t e r s , mailed announcements or b u l l e t i n s on an a g r i c u l t u r e subject during the past year? If so, how often? 1. Never 13. 1 50 19 2. r a r e l y 2 25 10 3. sometimes 3 65 26 4i often 4 116 45 103i Have you l i s t e n e d to farm radio or t e l e v i s i o n programs during the past year? I f so, how often? 1. Never 14. 1 23 9 2. r a r e l y 2 15 6 3. sometimes 3 90 35 4. often 4 128 50 - 143 -Column Code Frequency No. % 104. Did you read any farm newspaper a r t i c l e s during the past year? I f so, how often? 1. Never 15. 1 17 7 2. r a r e l y 2 14 5 3i sometimes 3 56 2'r. 4. often 4 169 66 105. Have you ever taken any a g r i c u l t u r a l courses? If so, where? 1. no courses 2. high school 3. vocational or ag r i c u l t u r e school 4. a g r i c u l t u r a l college 5. u n i v e r s i t y 6. adult education 0. no response 16. 1 2 3 4 5 6 0 196 9 12 5 2 30 2 77 .5 12 1 106. During the next f i v e years do you have any d e f i n i t e plans to change your farming a c t i v i t i e s or operations? 1. yes 2. ho 17. 1 2 196 60 77 23 107. What kind of change(s) do you hope to make? 1* increase farm s i z e 18. 2. change enterprise 3. c l e a r and/or drain land 19. 4. change buildings 5. education 20. 6. take an off-farm job 7. increase off-farm work 8. r e t i r e 9. increase stock J. s e l l farm K. decrease stock L. decrease farm s i z e M. rent out farm N. decrease off-farm work P. other 108. What do you think would improve agr i c u l t u r e i n t h i s area? 21. Present land use (9 cols) Land c a p a b i l i t y f o r ag r i c u l t u r e (10 cols) Land c a p a b i l i t y f o r f o r e s t r y ( 6 cols) 22. 23,31. 32,41. 42,47. - 144 -APPENDIX II Bi v a r i a t e tables of the socio-economic c h a r a c t e r i s t i c s versus contact l e v e l s and contact methods for which s i g n i f i c a n t chi-square values were obtained - 145 -TABLE XVII PERCENTAGE DISTRIBUTION OF YEARS OF SCHOOL COMPLETED BY CONTACT LEVELS Years of school completed  8 yrs or less 9 yrs and over Total Extension No. No. No. Contact Levels ___ (%) Low 101 28 129 (39.5) (10.9) (50.3) Medium 36 23 59 (14.1) (9.0) (23.1) High 36 32 68 (14.1) (12.5) (26.6) Tot a l 173 83 256 (67.6) (32.4) (100) TABLE XVIII . PERCENTAGE DISTRIBUTION OF ADULT EDUCATION PARTICIPATION BY CONTACT LEVELS Adult Education P a r t i c i p a t i o n "Yes" "No" Total Extension No. No. No. Contact l e v e l s £%_ _%_ (%) Low 8 121 129 (3.1) (47.3) (50.3) Medium 5 54 59 (1.95) (21.1) (23.1) High 17 51 68 (6.6) (19.9) (26.6) To t a l 30 226 256 (11.7) (88.3) (100) - 146 -TABLE XIX PERCENTAGE DISTRIBUTION OF NUMBER OF IMPROVED ACRES BY CONTACT LEVELS Number of Improved acres Extension Contact Levels 99 or less No. (%) 100-159 No. (%) 160-639 No, (%) 640 or over No. (%) Tota l No. (%) Low 63 25 23 18 129 (24.6) (9.8) (9.0) (7.0) (50.3) Medium 22 14 14 9 59 (8.6) (5.5) (5.5) (3.5) (23.1) High 9 8 13 38 68 (3.5) (3.1) (5.1) (14.8) (26.6) Tot a l 94 (36.7) 47 (18.4) 50 (19.5) 65 (25.4) 256 (100) TABLE XX PERCENTAGE DISTRIBUTION OF GROSS FARM INCOME BY CONTACT LEVELS Gross Farm Income $2,999 or $3,000- $6,000 and ' Extension les s $5,999 over To t a l Contact No. No. No. No. Levels (X) (%) (%) (%) Low 76 23 30 129 (29.7) (9.0) (U.7) (50.3) Medium 24 18 17 59 (9.4) (7.0) (6.6) (23.3) High 10 8 50 68 (3.9) (3.1) (19.6) (26.6) 110 49 97 256 Tot a l (43.0) (19.1) (37.9) (100) - 147 -TABLE XXI PERCENTAGE DISTRIBUTION OF ADULT EDUCATION PARTICIPATION BY PERSONAL CONTACT LEVELS Adult Education P a r t i c i p a t i o n Personal Contact Levels "Yes" No. (%) "No" No. (%) Tota l No. (%> Low 21 (8.2) 203 (79.3) 224 (87.5) High 9 (3.5) 23 (9.0) 32 (12.5) T o t a l 30 (11.7) 226 (88.3) 256 (100) TABLE XXII PERCENTAGE DISTRIBUTION OF NUMBER OF IMPROVED ACRES BY PERSONAL CONTACT LEVELS Number of Improved Acres Personal Contact Levels 99 or less 100 and over No. No. (%) <%) Tota l No. (%) Low 133 (52.0) 91 (35.6) 224 (87.5) High 8 (3.2) 24 (9.4) 32 (12.5) Tot a l 141 (55.1) 115 (44.9) 256 (100) - 148 -TABLE XXIII PERCENTAGE DISTRIBUTION OF GROSS FARM INCOME BY PERSONAL CONTACT LEVELS Gross Farm Income $2,999 or less $3,000 and over Total Personal No. No. No. Contact Levels a) (%) (%) Low 105 119 224 (41.0) (46.5) (87.5) High 5 27 32 (1.95) (10.6) (12.5) 110 146 256 Tot a l (43.0) (57.0) (100) TABLE XXIV PERCENTAGE DISTRIBUTION OF ADULT EDUCATION PARTICIPATION BY IMPERSONAL CONTACT LEVELS Adult Education P a r t i c i p a t i o n "Yes" "No" Total Impersonal No. No. No. Contact Levels (%) (%) a) Low 3 61 64 (1.2) (23.8) (25) High 27 165 192 (10.5) (64.5) (75) 30 226 256 Tot a l (11.7) (88.3) (100) - 149 -TABLE XXV PERCENTAGE DISTRIBUTION OF NUMBER OF IMPROVED ACRES BY IMPERSONAL CONTACT LEVELS Number of improved acres 640 and 99 or less 100-159 160-639 over Total Impersonal No. No. No. No. No. Contact Levels (%) (%) (%) (%) (%) Low 33 16 9 6 64 (12.9) (6.3) (3.5) (2.3) (25.0) High 61 31 41 59 129 (23.8) (12.1) (16.0) (23.1) (75.0) 94 47 50 65 256 To t a l (36.7) (18.4) (19.5) (25.4) (100) TABLE XXVI PERCENTAGE DISTRIBUTION OF GROSS FARM INCOME BY IMPERSONAL CONTACT LEVELS Gross farm income $2,999 $3,000- $6,000 and or l e s s $5,999 over T o t a l Impersonal No. No. No. No. Contact Levels (%) (%) (%) <%) Low 39 12 13 64 (15.2) (4.7) (5.2) (25.0) High 71 37 84 192 (27.7) (14.5) (32.9) (75.0) 110 49 97 256 (43.0) (19.1) (37.9) (100.0) - 150 -TABLE XXVII PERCENTAGE DISTRIBUTION OF YEARS OF SCHOOL COMPLETED BY KNOWLEDGE OF DISTRICT AGRICULTURIST Years of School Completed Knowledge of D i s t r i c t A g r i c u l t u r i s t 8 years or l e s s No. a) 9 years and over No. (%) Tot a l Total No. (%) "Yes" 82 (32.1) 54 (21.1) 136 (53.1) "No" 91 (35.5) 29 (11.3) 120 (46.9) T o t a l 173 (67.6) 83 (32.4) 256 (100.0) TABLE XXVIII PERCENTAGE PARTICIPATION DISTRIBUTION OF ADULT EDUCATION BY KNOWLEDGE OF DISTRICT AGRICULTURIST Adult Education P a r t i c i p a t i o n Knowledge of D i s t r i c t A g r i c u l t u r i s t P a r t i c i p a n t s No. <%> Non-partici-pants No. (%) T o t a l No. (%) "Yes" 24 (9.4) 112 (43.8) 136 (53.1) "No" 6 (2.3) 114 (44.5) 120 (46.9) T o t a l 30 (11.7) 226 (88.3) 256 (100.0) - 151 -TABLE XXIX PERCENTAGE DISTRIBUTION OF NUMBER OF IMPROVED ACRES BY KNOWLEDGE OF DISTRICT AGRICULTURIST Number of Improved Acres 99 or 640 and Knowledge of less 100-159 160-639 over Total D i s t r i c t No. No. No. No. No. A g r i c u l t u r i s t (%) (%) (%) (%) (%) "Yes" 35 22 30 49 136 (13.7) (8.6) (11.7) (19.1) (53.1) "No" 59 25 20 16 120 (23.1) (9.8) (7.8) (6.3) (46.9) 94 47 50 65 256 Tot a l (36.7) (18.4) (19.5) (25.4) (100.0) TABLE XXX PERCENTAGE DISTRIBUTION OF GROSS FARM INCOME BY KNOWLEDGE OF DISTRICT AGRICULTURIST $2,999 $3,000- $6,000- $9,000 and Knowledge of D i s t r i c t A g r i c u l t u r i s t or less No. (%) $5,999 No. (%) $9,000 No. (%) over No. (%) Tota l No. (%) "Yes" 47 26 6 57 136 (18.4) (10.2) (2.3) (22.3) (53.1) "No" 63 23 13 21 120 (24.6) (9.0) (5.1) (8.2) (46.9) T o t a l 110 (43.0) 49 (19.1) 19 (7.4) 78 (30.5) 256 (100.0) - 152 -TABLE XXXI PERCENTAGE DISTRIBUTION OF YEARS OF SCHOOL COMPLETED BY VISIT TO DISTRICT AGRICULTURIST'S OFFICE Years of School Completed 8 years 9-12 13 years V i s i t to or less years and over To t a l D i s t r i c t No. No. No. No. A g r i c u l t u r i s t ' s O f f i c e (%) (%) (%) a) V i s i t 49 35 6 90 (19.1) (13.7) (2.3) (35.2) No v i s i t 122 39 5 166 (47.7) (15.2) (1.95) (64.8) 171 74 11 256 To t a l (66.8) (28.9) (4.3) (100) TABLE XXXII PERCENTAGE DISTRIBUTION OF ADULT EDUCATION PARTICIPATION BY VISIT TO DISTRICT AGRICULTURIST'S OFFICE Adult Education P a r t i c i p a t i o n V i s i t to D i s t r i c t A g r i c u l -t u r i s t ' s O f f i c e P a r t i c i p a n t s No. a) Non-partici-pants No. (%) Tot a l No. a) V i s i t 18 72 90 (7.0) (28.1) (35.2) No v i s i t 10 156 166 (3.9) (60.9) (64.8) T o t a l 28 (10.9) 228 (89.1) 256 (100) - 153 -TABLE XXXIII PERCENTAGE DISTRIBUTION OF NUMBER OF IMPROVED ACRES BY VISIT TO DISTRICT AGRICULTURIST !s* OFFICE Number of Improved Acres V i s i t to D i s t r i c t A g r i c u l t u r i s t ' s O f f i c e 99 or less No. (%) 100-159 No. (%) 160-639 No. (%) 640 and over No. (%) Total No. (%) V i s i t 15 (5.9) 17 (6.6) 22 (8.6) 36 (14.1) 90 (35.2) No v i s i t 77 (30.1) 30 (11.7) 28 (10.9) 31 (12.1) 166 (64.8) Tot a l 92 (35.9) 47 (18.4) 50 (19.5) 67 (26.2) 256 (100) TABLE XXXIV PERCENTAGE DISTRIBUTION OF GROSS FARM INCOME BY VISIT TO DISTRICT AGRICULTURIST Is- OFFICE Gross Farm Income V i s i t to $2,999 $3,000- $6,000- $9,000 and D i s t r i c t or less" $5,999 $8,999 over Total A g r i c u l t u r i s t ' s No. No. No. No. No. O f f i c e (%) (%) <%) (%) (%) V i s i t 27 13 8 42 90 (10.6) (5.1) (3.1) (16.4) (35.2) No v i s i t 81 36 11 38 166 (31.6) (14.1) (4.3) (14.8) (64.8) 108 49 19 80 256 To t a l (42.2) (19.1) (7.4) (31.3) (100) - 154 -TABLE XXXV PERCENTAGE DISTRIBUTION OF ADULT EDUCATION PARTICIPATION BY TELEPHONE CALLS TO DISTRICT AGRCULTURIST Adult Education P a r t i c i p a t i o n Telephone P a r t i c i - Non-partici-c a l l s to pants pants To t a l D i s t r i c t No. No. No. A g r i c u l t u r i s t '•(%) (%) (%) C a l l e r s 9 35 44 (3.5) (13.7) (17.2) Non-callers 21 191 212 (8.2) (74.6) (82.8) 30 226 256 Tot a l (11.7) (88.3) (100) TABLE XXXVI PERCENTAGE DISTRIBUTION OF NUMBER OF IMPROVED ACRES BY TELEPHONE CALLS TO DISTRICT AGRICULTURIST Number of Improved Acres Telephone 99 or 640 and c a l l s to less 100-159 160-639 over Total D i s t r i c t No. No. No. No. No. A g r i c u l t u r i s t <%) a) (%) (%) (%) C a l l e r s 10 6 5 23 44 (3.9) (2.3) (1.95) (9.0) (17.2) Non-callers 84 41 45 42 212 (32.8) (16.0) (17.6) (16.4) (82.8) 94 47 50 65 256 To t a l (36.7) (18.4) (19.5) (25.4) (100) t - 155 -TABLE XXXVII PERCENTAGE DISTRIBUTION OF GROSS FARM INCOME BY TELEPHONE CALLS TO DISTRICT AGRICULTURIST Gross Farm Income Telephone $ 2 , 9 9 9 $3,000- $6,000 and c a l l s to or -.Gas $5,999 over Total D i s t r i c t No. No. No. No. A g r i c u l t u r i s t (%) (%) (%) ar C a l l e r s 7 6 31 44 (2.7) (2.3) (12.1) (17.2) Non-callers 103 43 66 212 (40.2) (16.8) (25.8) (82.8) 110 49 97 256 To t a l (43.0) (19.1) (37.9) (100) TABLE XXXVIII PERCENTAGE DISTRIBUTION OF ADULT EDUCATION PARTICIPATION BY FARM VISITS BY DISTRICT AGRICULTURIST Adult Education P a r t i c i p a t i o n Farm P a r t i c i - Non-partici-v i s i t s by pants pants Total D i s t r i c t No. No. No. A g r i c u l t u r i s t (7c) (%) (70) Farmers v i s i t e d 8 34 42 (3.1) (13.3) (16.4) Farmers not v i s i t e d 22 192 214 (8.6) (75.0) (83.6) 30 226 256 To t a l (U.7) (88.3) (100) - 156 -TABLE XXXIX PERCENTAGE DISTRIBUTION OF NUMBER OF IMPROVED ACRES BY FARM VISITS BY DISTRICT AGRICULTURIST •' • •• ' ' - Number of improved acres Farm 99 or 160 and v i s i t s by less 100-159 over Total D i s t r i c t No. No. No. No., A g r i c u l t u r i s t (%) (%) <%) (%) Farmers v i s i t e d 8 8 26 42 (3.1) (3.1) (9.3) (16.4) Farmers hot v i s i t e d 86 39 89 214 (33.6) (15.2) (34.8) (83.6) 94 ' ' 47 115 256 To t a l (36.7) (18.4) (44.9) (100) TABLE XL PERCENTAGE DISTRIBUTION OF GROSS FARM INCOME BY FARM VISITS BY DISTRICT AGRICULTURIST " " " G r o s s farm income Farm $2,999 $3,000- $6,000 and v i s i t s by or |ess $5,999 over To t a l D i s t r i c t No. No. No. No. A g r i c u l t u r i s t (%) (%) (%) (%) Farmers v i s i t e d 6 5 31 42 (2.3) (2.0) (12.1) (16.4) Farmers not v i s i t e d 104 44 66 214 (40.6) (17.2) (25.8) (83.6) 110 49 97 256 (43.0) (19.1) (37.9) (100) - 157 -TABLE XLI PERCENTAGE DISTRIBUTION OF YEARS OF SCHOOL COMPLETED BY ATTENDANCE AT AGRICULTURAL MEETINGS AND FIELD DAYS Years of school completed 8 years 9 years A g r i c u l t u r a l or less and over Total Meetings No. No. No. and F i e l d Days a) (%) (%) Attendants 48 39 87 (18.8) (15.3) (34.0) Non-attendants 125 44 169 (48.8) (17.2) (66.0) 173 83 256 Tot a l (67.6) (32.4) (100) TABLE XLII PERCENTAGE DISTRIBUTION OF ADULT EDUCATION PARTICIPATION BY ATTENDANCE AT AGRICULTURAL MEETINGS AND FIELD DAYS Adult education p a r t i c i p a t i o n A g r i c u l t u r a l P a r t i c i - N on-partici-Meetings pants pants Total and No. No. No. F i e l d Days (%) (%) (%) Attendants 16 71 87 (6.3) (27.7) (34.0) Non-attendants 14 155 169 (5.5) (60.6) (66.0) 30 226 256 Tot a l (11.7) (88.3) (100) - 158 -TABLE XLIII PERCENTAGE DISTRIBUTION OF NUMBER OF IMPROVED ACRES BY ATTENDANCE AT AGRICULTURAL MEETINGS AND FIELD DAYS Number of improved acres 99 or 640 and A g r i c u l t u r a l less 100-159 160-639 over Total Meetings No. No. No. No. No. and F i e l d Days (%) <%) (%) (%) (%) Attendants 19 15 18 35 87 (7.4) (5.9) (7.0) (13.7) (34.0) Non-attendants 75 32 32 30 169 (29.3) (12.5) (12.5) (11.7) (66.0) 94 47 50 65 256 To t a l (36.7) (18.4) (19.5) (25.4) (100) TABLE XLIV PERCENTAGE DISTRIBUTION OF GROSS FARM INCOME BY ATTENDANCE AT AGRICULTURAL MEETINGS AND FIELD DAYS Gross farm incor.e $2,999 $3,000- $6,000 - $9,000 and A g r i c u l t u r a l or less $5,999 $8,999 over To t a l Meetings No. No. No. No. No. and F i e l d Days (%) (%) (%) a) a) Attendants 21 16 7 43 87 (8.2) (6.3) (2.7) (16.8) (34.0) Non-attendants 89 33 12 35 169 (34.8) (12.9) (4-7) (13.7) (66.0) T o t a l 110 49 19 78 256 (43.0) (19.1) (7.4) (30.5) (100) - 159 -TABLE XLV PERCENTAGE DISTRIBUTION OF NUMBER OF IMPROVED ACRES BY RESPONDENTS'USE OF MAILS FROM THE DISTRICT AGRICULTURIST AS A SOURCE OF AGRICULTURAL INFORMATION Number of improved acres 99 or 640 and Mails from less 100-159 160-639 over T o t a l D i s t r i c t No. No.' No. No. No. A g r i c u l t u r i s t a) (%) <%) <%) (%) Users 66 36 45 59 206 (25.8) (14.1) (17.6) (23.1) (80.5) Non-users 28 11 5 6 50 (10.9) (4.3) (1.95) (2.3) (19.5) 94 47 50 65 256 T o t a l (36.7) (18.4) (19.5) (25.4) (100) TABLE XLVI PERCENTAGE DISTRIBUTION OF GROSS FARM INCOME BY RESPONDENTS' USE OF MAILS FROM THE DISTRICT AGRICULTURIST AS A SOURCE OF AGRICULTURAL INFORMATION Gross farm income $2,999 $3,000- $6,000 and Mails from or less $5,999 over To t a l D i s t r i c t No. No. No. No. A g r i c u l t u r i s t (%) <%) (%) (%) Users 79 41 86 206 (30.9) (16.0) (33.6) (80.5) Non-users 31 8 11 50 (12.1) (3;1) (4.3) (19.5) 110 49 97 256 T o t a l (43.0) (19.1) (37.9) (100) - 160 -TABLE XLVII PERCENTAGE DISTRIBUTION OF NUMBER OF IMPROVED ACRES BY RESPONDENTS* USE OF FARM NEWSPAPER ARTICLES AS A SOURCE OF AGRICULTURAL INFORMATION Number of improved acres 99 or 100 and Farm less over T o t a l newspaper No. No. No. a r t i c l e s (%) (%) (%) Readers 80 159 239 (31.3) (62.1) (93.4) Non-readers 14 3 17 (5.5) (1.2) (6.6) 94 162 256 Tota l (36.7) (63.3) (100) TABLE XLVIII PERCENTAGE DISTRIBUTION OF GROSS FARM INCOME BY RESPONDENTS* USE OF FARM NEWSPAPER ARTICLES AS A SOURCE OF AGRICULTURAL INFORMATION Gross farm income $2,999 $3,000 and Farm or less over Total newspaper No. No. No. a r t i c l e s (%) C_) _L_ Readers 96 143 239 (37.5) (55.9) (93.4) Non-readers 14 3 17 (5.5) (1.2) (6.6) 110 146 256 Tota l (43.0) (57.0) (100) - 161 -APPENDIX I I I Animal Unit 162 -+ ANIMAL UNIT One Animal Unit Equals OR Animal Unit Factor 1 beef cow, b u l l or animal 2 years old or over .75 dai r y cows 1.5 steers or h e i f e r s 1-2 years old 4 calves under 1 year 1 horse 2 horses 1-2 years old 7 ewes or rams 3 sows or boars 5 hogs 200 l b s . 10 feeder or weaner hogs 72 chickens 50 turkeys-breeding stock 80 turkeys - r a i s e d 25 geese 72 ducks 1 beef cow, b u l l or animal 2 years or over <= 1.0 1 dai r y cow => 1.33 1 steer or h e i f e r 1-2 years old = .66 1 c a l f under 1 year = .25 1 horse 2 years or over =1.0 1 horse 1-2 years = .5 1 ewe or ram = .14 1 sow or boar « .33 1 hog 200 l b s . = .2 1 feeder or weaner hog = .1 1 chicken = .014 1 turkey-breeding stock = .02 1 turkey - r a i s e d = .0125 1 goose = .04 1 duck = .014 + Source: Canada Department of A g r i c u l t u r e , Ottawa, Canada. - 163 -APPENDIX IV Comparison of Che r e s u l t s of simple and Spearman Rho c o r r e l a t i o n c o e f f i c i e n t s - 164 -TABLE XLIX COMPARISON OF THE RESULTS OF SIMPLE AND SPEARMAN RHO CORRELATION COEFFICIENTS Variables S i g n i f i c a n t co-e f f i c i e n t s with both S.C. and S.R.C. S i g n i f i c a n t co-e f f i c i e n t s with S.C. S i g n i f i c a n t co-e f f i c i e n t s with S.R.C. Age Father's education Number of years farming Job s a t i s f a c t i o n Weeks worked off-farm 1966 Years of Wife's education school Father's education completed Level of l i v i n g S o c i a l p a r t i c i p a t i o n Number of improved acres Gross farm income Farm value V i s i t s to D.A.'s o f f i c e Meetings and F i e l d Days Mails from D.A. Newspaper a r t i c l e s Wife's Years of school education completed Number of c h i l d r e n Father's education Level of l i v i n g S o c i a l p a r t i c i p a t i o n Net farm income Number of c h i l d r e n Father's education Wife's education Attitudes to change Net farm income Age Years of school completed Wife's education Telephone c a l l s to D.A. Attitudes to change Net farm income Number of t o t a l acres Telephone c a l l s to D.A. Gross farm income Farm Radio/T.V. programs Attitudes to change Farm value Distance t r a v e l l e d for goods and services Mails from D.A. Attitudes to change Length of residence i n the area Mails from D.A. Number of improved acres Note: S.C. = Simple c o r r e l a t i o n S.R.C. = Spearman RHO c o r r e l a t i o n - 165 -TABLE XLIX (continued) Variables S i g n i f i c a n t co-e f f i c i e n t s with both S.C. and S.R.C. S i g n i f i c a n t co-e f f i c i e n t s with S.C. S i g n i f i c a n t co-e f f i c i e n t s with S.R.C. Distance t r a v e l l e d f o r goods and services Level of l i v i n g S o c i a l p a r t i c i p a t i o n Meetings and F i e l d Days Father's education Years of school completed Wife's education Distance t r a v e l l e d f o r goods and services S o c i a l p a r t i c i p a t i o n Net farm income Gross farm income Farm value Telephone c a l l s to D.A. Meetings and F i e l d Days Newspaper a r t i c l e s Years of school completed Wife's education Level of l i v i n g Number of t o t a l acres Number of improved acres Gross farm income Farm value Weeks worked off-farm i n 1966 V i s i t s to D .A , ' a o f f i c e Farm v i s i t s by D.A. Meetings and F i e l d Days Mails from D.A. V i s i t s to D.A.* s o f f i c e Degree of involve-ment i n farming Job s a t i s f a c t i o n Number of t o t a l acres Gross farm income Telephone c a l l s to D.A. Job s a t i s f a c t i o n Number of t o t a l acres Mails from D.A. Degree of involvement i n farming Attitudes to change Number of c h i l d r e n Months worked i n 1966 Mails from D.A. Age Wife's education Father's education Number of years farming Degree of involvement i n farming Weeks worked off-fsrm i n 1966 Farm v i s i t s by D.A. Meetings and F i e l d Days. - 166 -TABLE XLIX (continued) Variables S i g n i f i c a n t co-e f f i c i e n t s with both S.C. and S.R.C. S i g n i f i c a n t co-e f f i c i e n t s with S.C. S i g n i f i c a n t co-e f f i c i e n t s with S.R.C, Number of years farming Age Degree of involvement i n farming Job s a t i s f a c t i o n Gross farm income Farm value Weeks worked o f f -farm i n 1966 Attitudes to change Net farm income Number of acres improved Months worked i n 1966 Degree of involvement i n farming Attitudes to change Job s a t i s r ' f a c t i o n Net farm income Number of years farming Job s a t i s f a c t i o n Gross farm income Weeks worked o f f -farm i n 1966 Meetings and F i e l d Days Age Number of years farming Degree of involve-ment i n farming Weeks worked o f f -farm i n 1966 Wife's education Number of c h i l d r e n Number of improved acres Level of l i v i n g Farm value Weeks worked o f f -farm i n 1966 Meetings and F i e l d Days Years of school completed Number of t o t a l acres Gross farm income V i s i t s to D.A.'s o f f i c e Telephone c a l l s to D.A. Farm v i s i t s by D.A. Meetings and F i e l d Days Distance t r a v e l l e d for goods and services S o c i a l p a r t i c i p a t i o n Attitudes to change Net farm income Number of t o t a l acres Number of improved acres Farm value Distance t r a v e l l e d f o r goods and services Level of l i v i n g Gross farm income Farm value Number of years farming Degree of involvement i n farming - 167 -TABLE XLIX (continued) Variables S i g n i f i c a n t co-e f f i c i e n t s with both S.C. and S.R.C. S i g n i f i c a n t co-e f f i c i e n t s with S.C. S i g n i f i c a n t co-e f f i c i e n t s with S • R. C. Number of t o t a l acres Number of im-proved acres S o c i a l p a r t i c i p a t i o n Number of improved acres Gross farm income Farm value Weeks worked o f f -farm i n 1966 V i s i t s to D.A.'s o f f i c e Meetings and F i e l d days Years of school completed S o c i a l p a r t i c i p a t i o n Number of years farming Degree of involvement i n farming Number of t o t a l acres Number of improved acres Farm value Years of school completed Net farm income Telephone c a l l s to D.A. Wife's education Net farm income Distance t r a v e l l e d for goods and services Level of l i v i n g Degree of involvement i n farming Mails from D.A. Distance t r a v e l l e d f o r goods and services Job s a t i s f a c t i o n Mails from D.A. Newspaper a r t i c l e s Gross farm Weeks worked off-farm income i n 1966 V i s i t s to D.A.'s o f f i c e Telephone c a l l s to D.A. Farm v i s i t s by D.A. Meetings and F i e l d days Farm value Years of school completed Level of l i v i n g S o c i a l p a r t i c i p a t i o n Number of years farming Net farm income Number of t o t a l acres Number of improved acres Gross farm income Weeks worked o f f -farm i n 1966 V i s i t s to D.A.'s o f f i c e Farm v i s i t s by D.A. Meetings and F i e l d days Wife's education Degree of involvement i n farming Job s a t i s f a c t i o n V i s i t s to D.A.'s o f f i c e Newspaper a r t i c l e s - 168 -TABLE XLIX (continued) Variables S i g n i f i c a n t co-e f f i c i e n t s with both S.C. and S.R.C. S i g n i f i c a n t co-e f f i c i e n t s with S.C. S i g n i f i c a n t co-e f f i c i e n t s with S.R.C. Weeks worked off-farm i n 1966 V i s i t s to D.A.*s o f f i c e Age S o c i a l p a r t i c i p a t i o n Number of years farming Degree of involvement i n farming Job s a t i s f a c t i o n Net farm income Number of t o t a l acres Number of improved acres Gross farm income Farm value Meetings and F i e l d days Years of school com-pleted S o c i a l p a r t i c i p a t i o n Number of t o t a l acres Number of improved acres Gross farm income Farm value Telephone c a l l s to D.A. Meetings and F i e l d days Mails from D.A. Attitudes to change Telephone c a l l s Father's education to D.A. Farm v i s i t s by D.A. Level of l i v i n g Number of improved acres Gross farm income Farm value V i s i t s to D.A.'s o f f i c e Farm v i s i t s by D.A. Meetings and F i e l d days S o c i a l p a r t i c i p a t i o n Net farm income Gross farm income Farm value Telephone c a l l s to D.A. Meetings and F i e l d days. Net farm income Farm v i s i t s by D.A. Years of school completed Net farm income Number of t o t a l acres Distance t r a v e l l e d f o r goods and services V i s i t s to D.A.'s o f f i c e Attitudes to change - 169 -TABLE XLIX (continued) Variables S i g n i f i c a n t co-e f f i c i e n t s with both S.C. and S.R.C.  S i g n i f i c a n t co-e f f i c i e n t s with S.C. S i g n i f i c a n t co-e f f i c i e n t s with S.R.C.  Meetings and F i e l d days Mails from D.A. Farm Radio/ T.V. programs Farm News-paper a r t i c l e s Years of school completed Distance t r a v e l l e d f o r goods and services Level of l i v i n g S o c i a l p a r t i c i p a t i o n Degree of involvement i n farming Net farm income Number of t o t a l acres Gross farm income Farm value Weeks worked o f f -farm i n 1966 V i s i t s to D.A.'s o f f i c e Telephone c a l l s to D.A. Farm v i s i t s by D.A. Mails from D.A. Years of school completed Length of residence i n the area S o c i a l p a r t i c i p a t i o n V i s i t s to D.A.'s o f f i c e Meetings and F i e l d days Farm Radio/T.V. programs Newspaper a r t i c l e s Mails from D.A. Newspaper a r t i c l e s Years of school com-pleted Level of l i v i n g Mails from D.A. Farm Radio/T.V. programs Attitudes to change Wife's education Attitudes to change Months worked i n 1966 Number of improved acres Number of c h i l d r e n Level of l i v i n g Number of t o t a l acres Number of improved acres Gross farm income Farm value Number of improved acres Gross farm income Farm value - 170 -APPENDIX V Test of Goodness of F i t f o r Normal D i s t r i b u t i o n - 171 -Test of Goodness of F i t with data on Age Step 1 C a l c u l a t i o n of mean,(x) and standard deviation,(s No. of respondents X Ranks Ob. Frequencies (X) (1 x 3) 1 5 5 5 2 26 52 104 3 78 234 702 4 73 292 1168 5 50 250 1250 6 24 1__4 864 -£X 977 _ X 2 = 4093 X = 977 = 3.82 256 S = 256 (4093) - (977) 2 M 256 (255) = 1.195 - 172 -Step 2. C a l c u l a t i o n of Expected Frequencies 1 2 3 4 5 6 Normal Difference Class + curve between Z Expected Ranks Boundaries Z values areas values Frequency'-' •2.777 .497 1.5 -1.94? .474 2.5 -1.104 .364 3.5 -0.267 .106 4.5 0.568 .216 5.5 1.405 .421 6.5 2.242 .487 ,023 5.88 .110 28.16 .258 66.04 .110 28.16 ,205 52.48 .066 16.89 + Z = Class boundary - X S * Expected Frequency = Difference between Z values x N Step 3 Comparison of expected frequencies with observed frequencies using chi-square s t a t i s t i c (X 2) 2 2 X = ^ (Observed - Expected) Expected 76.97 - 173 -Note: The n u l l hypothesis that the sample frequency d i s t r i b u t i o n approximated the normal curve d i s t r i b u t i o n was tested at the .01 l e v e l of s i g n i f i c a n c e . Degree of freedom = (N-3), where N = number of terms i n the table ( i n t h i s case 6) and 3 re f e r s to the fac t that the expected frequencies had to s a t i s f y 3 conditions, namely: (1) the sum of the observed frequencies had to be equal to the sum of the expected frequencies, and (2) the mean and (3) standard d e v i a t i o n of the normal curve had to equal the mean and standard deviation of the observed d i s t r i b u t i o n 1 Thus, the degree of freedom i n t h i s case i s (6-3) = 3 X 2 = 76.97, d.f = 3, p<.001 Step 4 Conclusion The test showed that the expected frequencies were s i g n i f i c a n t l y d i f f e r e n t from the observed frequencies, i n d i c a t i n g that the d i s t r i b u t i o n s did not follow a normal curve, and hence, the n u l l hypothesis was reject e d . 1 John E. Frewd and Frank J . Williams, Modern Business S t a t i s t i c s , Englewood C l i f f s , N.J. Pr e n t i c e - H a l l , Inc. 1958, pp. 257-260. 174 Test of Goodness of f i t with data on number of years Farming Step 1 C a l c u l a t i o n of mean,(x) and standard deviation,(s). 1 2 Ranks Ob. frequencies 1 23 2 29 3 31 4 35 5 34 6 18 7 86 £.x = No. of Respondents (X)  23 58 93 140 170 108 602 X^ (1 x 3) 23 116 279 560 850 648 4214 1194 £ X Z = 6690 1194 256 S = = 4.664 256 (6690) - (1194)' N 256 (255) 2.096 - 175 -Step 2 C a l c u l a t i o n of Expected Frequencies 1 2 3 4 5 6 Normal Difference Class curve between Z Expected Ranks Boundaries Z values areas values frequency .5 -1.990 .477 1.5 -1.512 .434 2.5 -1.033 .348 3.5 -0.555 .209 4.5 -0.076 .032 5.5 0.402 .155 6.5 0.880 .310 .043 11.01 .086 22.02 .139 35.58 .177 45.31 ,123 31.49 .155 39.68 7 .103 26.37 7.5 1.359 .413 Step 3 Comparison of expected frequencies with observed frequencies using chi-square s t a t i s t i c (X 2) X 2 • 165.09 d.f - (N-3) = (7-3) = 4 X 2 « 165.09, d.f - 4, p< .001 Note: The n u l l hypothesis that the sample frequency d i s t r i b u t i o n approximated the normal curve d i s t r i b u t i o n was tested at the .01 l e v e l of s i g n i f i c a n c e . - 176 -Step 4 Conclusion The test? showed that the expected frequencies were s i g n i f i c a n t l y d i f f e r e n t from the observed frequencies, i n d i c a t i n g that the d i s t r i b u t i o n s did not follow a normal curve, and hence, the n u l l hypothesis was rejected. 

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