Agriculture urbaine : un outil multidimensionnel pour le développement des quartiers
Bibliographic record
Abstract
Depuis plus de 30 ans différentes expériences en agriculture urbaine (AU) ont eu lieu à Montréal (Québec, Canada). Le programme des jardins communautaires, géré par la Ville, et 6 jardins collectifs, gérés par des organisations communautaires, sont examinés dans le cadre de cet article. Ces expériences visent différents objectifs dont la sécurité alimentaire, la sociabilisation et l’éducation. Ceux-ci évoluent au niveau temporel mais se différencient aussi géographiquement (quartiers). Il en ressort que les initiatives en AU à Montréal s’avère un lieu de production de légumes non négligeable, un lieu de sociabilisation et d’éducation favorisant un développement social individuel et collectifs des quartiers ayant une forte présence de population économique défavorisée.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".