Justice environnementale et ressentiment vert : l’exemple d’arrondissements montréalais
Bibliographic record
Abstract
Cet article examine l’opposition des citoyens des classes moyennes et paupérisées aux politiques vertes dans deux arrondissements de Montréal. Via l’étude de conseils d’arrondissement, cette étude souligne la façon dont la justice environnementale nourrit un ressentiment vert chez certains citoyens. Les citoyens observés ne sont pas idéologiquement contre les politiques environnementales. Ils se sentent plutôt emportés par une « révolution verte » dont ils supporteront la majeure partie des coûts sans en retirer de bénéfices à court terme. Leur conception de la justice environnementale croise une critique procédurale de la démocratie concernant la participation et la transparence et une critique substantielle des inégalités dans la répartition des coûts des politiques environnementales. Ces citoyens mettent également en avant un attachement à leur quartier qui lie l’environnement à une conception du bien commun.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.012 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".