L’évaluation des systèmes alimentaires urbains à Montréal et dans le monde
Bibliographic record
Abstract
À l’heure de la transition sociale et écologique des systèmes alimentaires, attester des processus de transformation en cours exige de développer des outils de mesure, de suivi et d’évaluation. Il existe d’ailleurs quelques cadres et référentiels visant l’évaluation des systèmes alimentaires dans une perspective de « durabilité » à plusieurs échelles, dont Évaluation en commun, une démarche participative que notre équipe a menée avec des acteurs du système alimentaire montréalais. Le but de cet article est de décrire et comparer quatre cadres qui portent sur les milieux urbains, soit la boîte à outils City-Region Food System, URBAL, SHARE IT et Évaluation en commun. De cette analyse comparative ressortent deux tendances, soit la standardisation des cadres d’évaluation et leur adaptation aux contextes locaux.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".