La recherche francophone en éducation : réseaux, échanges, publications
Bibliographic record
Abstract
À l’occasion des rencontres de juillet 2019 à Toulouse, le comité d’organisation du Réseau international de recherche en éducation et en formation (REF) et le comité de rédaction des Dossiers des Sciences de l’éducation ont décidé de consacrer ce numéro 41 de la revue à une mise en perspective de la recherche francophone dans la discipline des sciences de l’éducation et de la formation. Le REF est né en 1989. Ses diverses rencontres, maintenant organisées tous les deux ans dans l’un des quatre pays fondateurs (France, Belgique, Québec, Suisse), ont vu le nombre de symposiums, qui sont la marque distinctive de son fonctionnement, augmenter de 4 à 37 (Toulouse, 2019) et l’effectif des participantes et participants connaître la même croissance. Précédées et/ou suivies par une journée de colloque(s), ces rencontres contribuent à la réalisation et à la diffusion de la recherche comme en témoignent les dizaines de publications (plus de 140 livres ou dossiers de revue à ce jour).
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 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 | 0.056 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.027 | 0.015 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.053 | 0.016 |
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".