L’apprentissage au cœur des projets d’action sociale en agriculture : accroître le pouvoir et la volonté d’agir des individus et des groupes sociaux
Bibliographic record
Abstract
L’émergence de projets d’action sociale en agriculture témoigne d’une prise en charge de la problématique agroalimentaire par les citoyens, lesquels développent ensemble un agir pour résoudre les problèmes qui les affectent. Les personnes impliquées dans de tels projets acquièrent plusieurs types de savoirs propices au développement d’une compréhension plus globale du système agroalimentaire, contribuant à accroître leur pouvoir et leur volonté d’agir.Quelles sont les racines de la problématique socioécologique qui touche le système agroalimentaire au Québec ? Quel est le pouvoir d’action des citoyens et des agriculteurs sur ce système ? Après avoir exploré ces questionnements, cet article se penche plus spécifiquement sur certains résultats d’une étude de cas, celle de la coopérative La Mauve, afin de mettre en lumière les liens qui unissent l’apprentissage et l’action sociale dans une perspective de prise de pouvoir citoyenne.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".