Construction identitaire de l’élève en éducation artistique dans un contexte francophone minoritaire canadien
Bibliographic record
Abstract
Dans les cinq dernières années, plusieurs approches d’éducation artistique et politiques linguistiques ont été mises en oeuvre dans le contexte de la francophonie canadienne pour favoriser la construction identitaire de l’élève. Par exemple, des programmes spécialisés en arts ont été mis sur pied afin de favoriser une concertation entre les contextes de formation scolaire, collégiale, universitaire et en cours d’emploi. Le programme Majeure Haute Spécialisation en Arts et Culture conçu par le ministère de l’éducation de l’Ontario répond à cette visée et l’étude de cas, dont il est question dans cet article, témoigne de la manière dont peut se vivre une insertion sur le marché du travail dès 16 ans, dans le cadre d’un stage réalisé en arts médiatiques en milieu 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.019 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".