Lier recherche, formation et pratique enseignante : une piste pour développer des pratiques inclusives ?
Bibliographic record
Abstract
Cet article présente et discute une configuration d’actions liant recherche, formation et pratique professionnelle en vue de promouvoir un enseignement différencié à visée inclusive. Quatre actions interreliées ont été conduites. Elles ont permis de constater que travailler à développer une vision inclusive et des compétences dans le domaine de la différenciation semble un défi accessible en formation initiale, mais plus conséquent en formation continue. Dans les deux cas, une visée praxéologique est nécessaire pour susciter l’adhésion des personnes enseignantes. L’entrée par l’activité, supervisée par une même équipe de personnes formatrices-chercheuses, est une piste prometteuse pour développer des pratiques différenciées.
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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 | 0.045 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.042 |
| Scholarly communication | 0.023 | 0.030 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 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".