Pratique de gouvernance éducative multijoueur et leadership partagé : la direction, les parents et les membres de la communauté
Bibliographic record
Abstract
Depuis plusieurs années, au Québec comme ailleurs, les États ont approfondi et intensifié la gouvernance multijoueur dans leur pratique de gestion publique (Côté, Lévesque et Morneau, 2007; Hamel et Jouve, 2006; Gaudin, 2002). Le secteur de l’éducation a suivi cette tendance et a notamment accru de façon importante la participation des acteurs concernés (Meyer, 2014; Lacroix, 2012; Paquet, 2010; Brassard, 2007; Lessard et Brassard, 2006; Landry et Haché, 2001). Dans le présent article, nous nous intéressons à la gouvernance multijoueur et plus particulièrement à l’espace qu’elle crée pour l’exercice d’un leadership véritablement partagé (Luc, 2010; Harris et Spillane, 2008). Ainsi, nous avons étudié les pratiques de gouvernance et de leadership partagé — notamment entre les directions, les parents et les membres de la communauté — au sein de deux commissions scolaires québécoises au moyen d’entrevues et d’observations. Les résultats de nos analyses ont fait ressortir les aspects facilitant le partage du leadership et les contraintes inhérentes à cette pratique de gouverne.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".