Les coopératives alimentaires en circuits courts
Bibliographic record
Abstract
Cet article analyse les motivations conduisant des producteurs agricoles du Québec à créer et à adhérer à des coopératives spécialisées en circuits alimentaires de proximité (CAP). Si ces dernières sont bien implantées en France, elles demeurent limitées au Québec et peinent à pérenniser leurs structures. À partir d’une étude de cas multiples, l’article établit comment l’adhésion à une coopérative en CAP permet de répondre à plusieurs besoins, dont la diversification des exploitations et des revenus, grâce à la mutualisation des moyens. Les auteurs établissent également une typologie de profils de membres selon leur engagement envers la coopérative et leurs aspirations personnelles, montrant qu’il existe une gradation de motivations et d’engagements à mobiliser ou à questionner pour pérenniser ce modèle coopératif de production, de transformation et de distribution en circuit court.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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; both teacher heads agree on what is shown here.
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".