Entre mesure, science et politique : construction et analyse d’un réseau international de copublications dans le domaine de l’éducation
Bibliographic record
Abstract
Notre étude vise à repérer certains réseaux d’experts et de chercheurs, à l’oeuvre à l’échelle internationale, qui produisent de nouveaux référentiels et de nouveaux instruments de mesure pour améliorer l’efficacité et la qualité de l’éducation. Pour ce faire, nous utilisons la méthodologie de l’analyse des réseaux (dont l’outil Pajek) afin d’objectiver et d’étudier les liens de co-publications. La définition de ces liens repose sur un travail préalable de constitution d’une base de références bibliographiques contenant 5 300 références écrites par environ 3 500 auteurs. On met alors en évidence des communautés épistémiques clairement identifiées et rattachées à un paradigme: des chercheurs de laschool effectiveness, des économistes du capital humain, des psychométriciens spécialistes des comparaisons internationales de résultats.
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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 | 0.043 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.038 | 0.047 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.027 | 0.020 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".