Retraite du milieu agricole : enjeux individuels, familiaux et sociaux
Bibliographic record
Abstract
Research Framework: Quebec agriculture is still characterized by family farms that are usually transferred from generation to generation. Considering that the Quebec agricultural lifestyle generally interweaves the “individual”, “family” and “entrepreneurial” spheres, that many farmers are expected to sell their business in the next few years and that this transition raises many questions and challenges, factors influencing adaptation to this new reality deserve to be studied.Objectives: The purpose of this study is to better understand farmers’ current experiences with the transfer or sale of their business to their children or a third party from a psychological angle linked to the systemic approach.Methodology: Nine semi-structured interviews were conducted with farmers (6 men and 3 women, mean 59 years-old), who have withdrawn from their company (between 1 month and 10 years).Results: This study sheds light on the issues and challenges inherent to the agricultural community during the working life and after the transfer or sale of the business. Resilience is evident in all participants. They usually remain professionally active, which is inconsistent with traditional retirement models.Conclusions: Considering that the majority of retirees in the sample continue to get involved during and after the transfer of their business, the reasons that motivate them as well as the psychological and family issues that arise from this deserve to be deepened.Contribution: This study draws a psychological portrait of this transition in Quebec (Canada). Considering the importance reported by the participants to remain active and socially engaged, social innovations are suggested in order to promote the adaptation to retirement of farmers who cannot continue to work in the field.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".