Cinquante ans de la <i>Revue des sciences de l’éducation</i> : réflexions sur un demi-siècle de recherches
Bibliographic record
Abstract
Au terme d’entrevues menées dans le cadre du 50 e anniversaire de la Revue des sciences de l’éducation en 2023-2024, 5 chercheur·se·s commentent un article de la revue de leur choix, lié à leur spécialisation. Ces entrevues montrent que les théories et les résultats des recherches antérieures continuent d’exercer une influence, voire d’expliquer des enjeux et des phénomènes contemporains dans le monde de l’éducation. Les réflexions portent sur les technologies et l’intelligence artificielle en éducation, l’importance de la rigueur scientifique en sciences de l’éducation, la citoyenneté et le rôle de l’école dans l’éducation, les obstacles auxquels font face les personnes immigrantes nouvellement arrivées au Québec et qui sont parents, les enjeux liés aux programmes de formation et l’appropriation des savoirs par les futur·e·s enseignant·e·s.
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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 | 0.022 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".