Understanding non-agricultural entrepreneurial activities developed by farmers in Canada
Bibliographic record
Abstract
The promotion of entrepreneurial activities is considered a mean to boost employment and income opportunities in less favoured areas. Farmers, as experienced owners and managers of productive resources, represent a great entrepreneurial potential for developing non-agricultural businesses. The aim of this study is to provide empirical evidence regarding farmers' entrepreneurial characteristics, factors affecting their decisions to participate in non-agricultural entrepreneurial activities, and a characterization of the process of formation and operation of farm-based value-added activities in Canada. Canadian farmers exhibit internal locus of control (LOC) and moderate high levels of entrepreneurial self-efficacy (ESE) and entrepreneurial alertness (EA). Farmers performing non-agricultural entrepreneurial activities show higher levels of ESE and EA than farmers who are not doing these types of activities. Furthermore, farmers' participation in value-added activities is influenced positively by innovation, university education, participation in organizations and production of fruit and vegetables. Farming experience affects negatively. Participation in non-farm business is positively influenced by managerial abilities, business experience, and participation in off-farm employment. Negative factors are university education and fruit and vegetable production. In respect to characteristics of farm-based value-added activities: the main objectives for starting VAD are to complement household income and to assure survival of family businesses; main problems in starting VAD are lack of marketing skills and managerial abilities and meeting regulations; and the main barriers for not participation in VAD are lack of time, financial constraints and size of operation. VAD are mostly family businesses involved in direct selling through farmers' markets, pick-your-own and farm shops with a local customer base. The main contribution of VAD activities to farm household are achievement of initial objectives and increase in household income. The results suggest that farmers have the entrepreneurial potential for participating in strategies of rural development through business diversification. Better institutional coordination, revision of regulations and appropriate incentives can improve their participation. Policymakers and rural developers can benefit from this information in developing policies involving farmers in creating or expanding entrepreneurial activities in rural areas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".