Comprendre la mise en œuvre différenciée d'une politique publique : Le cas d'une politique de gouvernance au Québec
Bibliographic record
Abstract
Résumé.En 2001, le gouvernement québécois adopte laPolitique de reconnaissance et de soutien à l'action communautaire. La mise en œuvre de cette politique a mené à des résultats contrastés en fonction des champs d'intervention considérés. Dans cet article, nous soutenons que la mise en œuvre différenciée de la Politique est directement liée à la structuration des acteurs sociaux dans chaque champ d'intervention. Par l'analyse de deux champs, le champ de l'environnement et celui de la défense collective des droits, nous montrons comment, au-delà des explications usuelles des processus de mise en œuvre des politiques publiques qui font intervenir le rôle des acteurs politiques et des réseaux, c'est la prise en compte de l'action autonome des acteurs sociaux qui permet de comprendre la différenciation des trajectoires de mise en œuvre. Abstract.In 2001, the Québec government adopted itsPolitique de reconnaissance et de soutien à l'action communautaire. The implementation of this policy has led to contrasting results depending on the fields of intervention considered. We argue that the different implementation pathways of this policy are directly linked to the structuring of social actors in each field. Using two fields of intervention – the environment and advocacy – as case studies, we show the need to go beyond the usual explanations regarding the implementation of public policies which stress the importance of political actors and policy networks. Without neglecting the role of the latter, the different pathways in the implementation processes of this policy are also largely due to the autonomous action of social actors.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".