Explorer le leadership des directions d’établissement scolaire par l’analyse de l’activité en autoconfrontation croisée
Bibliographic record
Abstract
Dans le cadre de la gestion axée sur les résultats qui introduit une recherche accrue d’efficience et d’efficacité, le leadership, entendu comme la capacité des chefs d’établissement à mobiliser leur personnel, s’avère essentiel pour assurer le relais des orientations stratégiques qui mettent l’accent sur la réussite scolaire. Or, la recherche peine à rendre compte de la complexité du phénomène de leadership, tout comme à accéder à l’expérience du travail réel, à l’intelligence pratique déployée par les « leaders ». Cet article présente une démarche méthodologique qui permet d’accéder à l’expérience vécue des directions d’établissement scolaire. Elle consiste à confronter les professionnels à des traces filmées de leur activité dans une exploration progressive et guidée.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".