Les étudiants en situation de handicap inscrits en éducation spécialisée : ce qu’en disent leurs enseignantes
Bibliographic record
Abstract
Le département d’éducation spécialisée du Cégep de Jonquière assure quotidiennement la formation d’étudiants en situation de handicap (ÉSH), qui représentent le quart des étudiants qui le fréquentent. Nous avons mené une recherche dans une perspective bioécologique afin de brosser un portrait des caractéristiques des ÉSH inscrits en techniques d’éducation spécialisée (TES) et de connaître les attitudes, les rôles et les stratégies pédagogiques privilégiés pour les soutenir. Dans ce contexte, nous avons réalisé une analyse qualitative d’entrevues individuelles semi-dirigées menées auprès de sept enseignantes. Nos résultats révèlent que leur point de vue sur les besoins des ÉSH est, somme toute, positif et empreint d’espoir pour leur réussite scolaire.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".