Principes méthodologiques et techniques des enquêtes internationales
Bibliographic record
Abstract
Cet article vise à expliquer les principes méthodologiques sous-jacents à l’élaboration et à la mise en oeuvre des enquêtes internationales dans le domaine de l’éducation. Plus spécifiquement, ce sont les épreuves de rendement disciplinaires qui sont abordées et non pas les questionnaires contextuels. À cette fin, le développement du cadre de référence, le choix des tâches et des items, l’essai de terrain, le plan d’évaluation ainsi que la définition de la population de référence et le plan d’échantillonnage sont décrits. De plus, les aspects psychométriques de base sont abordés : modélisations issues de la théorie de la réponse à l’item utilisées ; méthodes d’estimation des paramètres et particularités propres à ces enquêtes ; qualité des mesures obtenues.
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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 | 0.167 | 0.309 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.017 | 0.022 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.018 | 0.011 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".