Une méta-analyse de récits de pratique de formatrices et de formateurs : l’élaboration d’un savoir collectif pour former le personnel enseignant à la déconstruction du genre
Bibliographic record
Abstract
En Europe francophone, des formations à l’égalité filles-garçons sont offertes aux enseignantes et aux enseignants de manière à instaurer une réflexion sur les inégalités entre les sexes et sur les manières dont elles peuvent être reconduites à l’école, y compris dans leurs propres pratiques. Afin d’échanger autour de leurs démarches, des formatrices et des formateurs ont rédigé des récits de pratique, dans lesquels leurs réflexions portent sur les résistances rencontrées et leurs stratégies pédagogiques pour les contourner. L’article propose une méta-analyse de 33 de ces récits en vue d’interroger les dilemmes et les tensions de la formation à l’égalité des sexes qu’ils mettent en avant.
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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 | 0.087 | 0.196 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.020 | 0.027 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".