Stratégies à déployer par les étudiants en situation de handicap en stage et accompagnement souhaité
Bibliographic record
Abstract
Stratégies à déployer par les étudiants en situation de handicap en stage et accompagnement souhaité Formation et profession 31(3) 2023 • 1 ésumé Les universités connaissent une hausse d' étudiants en situation de handicap (ESH) qui suscite des questions concernant l'accompagnement à leur offrir en stage.Cette recherche collaborative leur donne une voix afin qu'ils puissent : 1) identifier leurs principaux défis rencontrés en stage, 2) répertorier leurs stratégies d'apprentissage pour composer avec leurs défis et 3) identifier les mesures d'accompagnement souhaitées de la part des formateurs de stage.Un processus itératif de collecte et d'analyse de données, comportant questionnaire et groupes de discussion, suggère que les ESH souhaitent ardemment réussir en déployant différentes stratégies tout en étant accompagnés par des formateurs disposés à les accueillir dans leur altérité.
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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 | 0.019 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".