Sociologie de l'environnement, globalisation et traditions nationales: Une étude des cas français et québécois
Bibliographic record
Abstract
Résumé: Cet article explore les liens entre les sociologies québécoise et française de l’environnement. Il revient d’abord sur les difficultés de lier entre-elles les approches sociologiques nationales. Il s’attache ensuite à rassembler un nombre important de contributions issues d’ouvrages collectifs et de colloques français, québécois et francophones pour présenter deux résultats. Premièrement, il existe un ensemble de démarches d’analyse transversales aux approches québécoises et françaises. Deuxièmement, ces deux sociologies régionales gardent pourtant des spécificités historiques et géographiques propres. Cela conduit à penser que sociologies locales et sociologie globale coexistent et trouvent un équilibre certes fragile mais heuristique. Abstract: This article explores the relationship between Quebec and French environmental sociologies. It reviews the difficulties in linking national sociological approaches. Then it endeavours to compile numerous contributions selected in Quebec, French and French-speaking collective books, and conferences with two results. First, there is a set of analytical processes transversal to Quebec and French approaches. Second, both of these two regional sociologies keep their own historical and geographical specificities. This suggests that local sociologies and global sociology can coexist and find an equilibrium, heuristic though fragile.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".