Inclusion scolaire et inégalités : perspectives plurielles et bilan sur les défis
Bibliographic record
Abstract
Dix ans après, où en sommes-nous ? Cet ouvrage collectif offre des points de repères pluriels à toutes les personnes engagées dans la construction d'un système éducatif plus juste et équitable. En donnant la parole à différentes voix, il offre, par le croisement de leurs expertises (anthropologie, sociologique, ethnographie, sciences de l’éducation, enseignement spécialisé, etc.) et la multiplicité des lieux géographiques (Canada, Brésil, France, Suisse), un recueil de points de vue critiques sur ce que nous a appris cette dernière décennie. Pour qui cherche un éclairage sur les défis persistants de l'éducation inclusive, ces perspectives diverses mettent en lumière les liens complexes entre l'inclusion et inégalités scolaires. Elles témoignent de la nécessité d’une quête incessante pour comprendre, analyser et agir.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.049 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".