Comment naviguer une révision majeure de cursus en mobilisant un leadership collaboratif?
Bibliographic record
Abstract
Cette ressource est un outil synthèse conçu pour soutenir toutes personnes impliquées dans une révision majeure de programme. Elle présente de manière structurée plusieurs stratégies visant à mobiliser un leadership collaboratif, dans une double perspective : 1. Faciliter l’adhésion au changement et encourager l’engagement des membres de l’équipe ;2. Préserver l’équilibre occupationnel de toutes les parties prenantes impliquées dans le processus. En s’appuyant sur des principes de collaboration, de communication ouverte et de reconnaissance des besoins individuels et collectifs, cette ressource vise à outiller et inspirer les personnes qui pilotent ou participent à des projets de transformation curriculaire. Elle met en lumière des leviers d’action concrets pour naviguer les défis humains, organisationnels et pédagogiques que soulèvent ces démarches complexes.
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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 | 0.037 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.007 |
| 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".