La gestion des ressources humaines pour la réussite scolaire
Bibliographic record
Abstract
Malgre les restrictions budgetaires et les exigences croissantes en matiere de performance, les directions d’etablissement scolaire doivent assurer la qualite de l’enseignement et de l’apprentissage. Cette nouvelle edition de La gestion des ressources humaines pour la reussite scolaire etablit le lien entre la gestion des ressources humaines et la reussite scolaire et propose une description du systeme educatif. La planification, l’organisation, la direction et l’evaluation sont analysees et les themes au cœur de la gestion des personnes sont abordes (recrutement, formation, motivation, mobilisation et gestion des conflits).Le present ouvrage, mis a jour en tenant compte du contexte actuel (qui n’est plus celui de l’austerite budgetaire), propose de nouveaux chapitres et de nouveaux elements ayant une incidence sur la reussite scolaire – l’ecole en milieux francophones minoritaires au Canada, le milieu socio-economique de l’eleve et de l’ecole, le genre?: directrice ou directeur?? – en faisant ressortir, entre autres, l’importance du leadership. Il veut fournir aux gestionnaires, aux etudiants et aux professeurs en administration scolaire des ressources documentaires en francais.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".