Vers un curriculum global ? Une perspective comparative sur les transformations curriculaires en France et au Québec
Bibliographic record
Abstract
Alors que la diffusion de réformes basées sur une approche par compétences soulève la question de la standardisation des curricula à l’échelle globale, on sait peu de choses sur la façon dont ces tendances communes sont recontextualisées dans les contextes éducatifs nationaux. Cet article propose de retracer les transformations curriculaires en France et au Québec sur la période 2000-2015, à partir d’une analyse des textes qui constituent le curriculum formel. À la lumière de la sociologie du curriculum, la comparaison à la fois diachronique et synchronique permet de complexifier la vision de tendances mondiales uniformisantes, de souligner des recontextualisations nationales contrastées et de poser la question du pourquoi des différences observées.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".