La fonction d'évaluation dans l'administration publique québécoise : analyse de la cohérence du système d'actions
Bibliographic record
Abstract
Sommaire Cet article analyse la fonction d'évaluation dans l'administration publique du Québec au cours des années 2000 comme un système organisé d'actions (valeurs, environnement, ressources et modalités, pratique, effets) avec ses cohérences et incohérences. Trois constats émergent : les activités de soutien de la pratique évaluative de la part des ministères centraux sont quasiment absentes, la transparence auprès des citoyens dans le processus évaluatif est peu présente, la réalisation et l'utilisation d'évaluations de portée stratégique parait peu fréquente. Cet article met en évidence certaines cohérences et incohérences d'une fonction de gestion, et propose une façon directe et systématique de souligner les points à améliorer. Abstract In this article, we analyze the evaluation function within the Quebec public administration during the 2000s as an organized action system (values, environment, resources and procedures, practice, impacts) with its consistencies and inconsistencies. Three findings emerge: the support that central agencies give to the evaluation practice is almost non‐existent; the transparency of the evaluation process for the citizens is barely noticeable; and the undertaking and use of the strategic use of evaluations seem rare. This article brings the attention to some consistencies/inconsistencies of the management function, and suggests a direct and systematic way to highlight what needs to be improved.
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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 | 0.024 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".