Vers une approche institutionnelle : favoriser la réussite éducative par la conception universelle de l’apprentissage et l’accessibilité universelle
Bibliographic record
Abstract
Cet article est une réflexion critique autour de la réussite et de l’inclusion des personnes marginalisées ou en situation de handicap au collégial québécois. S’appuyant sur des recherches récentes en éducation sur la réussite et la diversité, cet article souhaite promouvoir le besoin d’approfondir la recherche sur l’application au niveau institutionnel des modèles issus de la conception universelle des apprentissages et de l’accessibilité universelle. Avec l’augmentation de la population identifiée ESH (étudiante ou étudiant en situation de handicap), les enjeux qui y sont associés (intersectionnalité, culturalisation, médicalisation et approche biomédicale, mesures de soutien, gestion administrative des accommodements, etc.) et le besoin manifesté par les personnes enseignantes et étudiantes de recevoir un soutien et un encadrement adaptés à leurs besoins, un changement de paradigme institutionnel semble s’organiser autour de l’approche inclusive prônée par l’accessibilité universelle.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.043 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".