Favoriser l’éducation inclusive à travers les relations école-famille immigrante et réfugiée : analyse de récits de pratique de directions d’établissement
Bibliographic record
Abstract
Les lves issu-es de l'immigration reprsentent plus du tiers des lves qubcois-es (Ministre de l'ducation du Qubec [MEQ], 2022a).Elles/ils prsentent une diversit d'expriences pr-pri et post-migratoires qui se transforment en dfis multiples pour les milieux scolaires.La Politique d'intgration scolaire et d'ducation interculturelle (MEQ, 1998) insiste sur la responsabilit collective l'gard du soutien l'intgration des lves et de leurs familles et, plus rcemment, on presse les tablissements scolaires vers l'adoption d'une perspective dite inclusive (Conseil suprieur de l'ducation [CSE], 2017 ; Ministre de l'ducation, du Loisir et du Sport [MELS], 2017).Partant d'une analyse thmatique par codage mixte (Mucchielli, 2009) de rcits de pratique de directions d'tablissements propos des relations cole-famille immigrante et rfugie (n=11) recueillis dans le cadre d'un projet de recherche men en milieu pluriethnique qubcois, cet article examine dans quelle mesure les pratiques des directions d'tablissement tmoignent et contribuent la mise en oeuvre de l'ducation inclusive (Magnan, et al., 2021 ;Potvin, 2014), travers quatre dimensions oprationnalises dans le Diagramme de l'ducation inclusive (Charette & Audet, 2023).Cette mise en dialogue mnera l'identification de pistes pour soutenir les directions vers une transformation des pratiques de leur cole.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".