Une compétence interculturelle et inclusive « en acte » : analyse de récits de pratique d’enseignant.e.s à propos de l’intervention en contexte de diversité ethnoculturelle
Bibliographic record
Abstract
Une comptence interculturelle et inclusive en acte : analyse de rcits de pratique d'enseignant.e.s propos de l'intervention en contexte de diversit ethnoculturelle Formation et profession 30(1) 2022 1 sum La Politique d'intgration scolaire et d' ducation interculturelle qubcoise (MEQ, 1998) insiste sur l'importance de former les enseignant.e.s relever les dfis ducatifs lis, d'une part, la diversit ethnoculturelle, linguistique et religieuse des effectifs et, d'autre part, la ncessaire socialisation commune de l' ensemble des lves , ce qui a men la formalisation d'une comptence interculturelle et inclusive (Potvin, Borri-Anadon, Larochelle-Audet, Armand, Beck, Cividini et Chastenay, 2015). Cet article prsente les rsultats d'une analyse de rcits de pratique (Desgagn, 2005) d' enseignant.e.s propos de l'intervention en contexte de diversit ethnoculturelle, documentant une comptence interculturelle et inclusive en acte .
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".