Prendre en compte les réalités d’élèves réfugié·e·s afin de soutenir leur résilience: analyse de récits de pratique d’enseignant·e·s en contexte québécois
Bibliographic record
Abstract
Dans le cadre d’un projet de recherche-action mené auprès d’élèves réfugié·e·s au Québec, nous avons documenté l’expérience d’enseignant·e·s qui les accueillent en classe. Dans cet article, nous présentons une analyse de récits de pratique qui relatent des situations vécues mettant en scène un·e élève réfugié·e et qui, du point de vue des personnes qui les racontent, pourraient être formatrices pour de futur·e·s enseignant·e·s. Dans une perspective compréhensive du savoir-agir professionnel, l’analyse qualitative progressive des données menée nous permettra de mettre en lumière six manières dont les participant·e·s soutiennent la résilience des élèves, ce qui nous apparaît également contribuer à leur développement professionnel.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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".