La co-construction de la gestion axée sur les résultats : les logiques de médiation des commissions scolaires
Bibliographic record
Abstract
Cet article porte sur le rôle des commissions scolaires (CS) québécoises dans le processus de mise en oeuvre de la politique de gestion axée sur les résultats (GAR) au sein du réseau de l’éducation obligatoire. Lors de ce processus, les CS contribuent à coconstruire cette politique et à la transformer partiellement. Cette médiation de la GAR par les CS conduit à la mise en place d’une gestion plus formalisée de l’efficacité des pratiques des enseignants. À partir d’une étude de cas multiples de quatre CS (61 entretiens semi-dirigés), nous montrons comment leurs logiques de médiation de la politique affectent la portée et l’intensité de la gestion de l’activité pédagogique : certaines CS adaptent la GAR à leur réalité organisationnelle, alors que d’autres l’intensifient.
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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 | 0.030 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".