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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".