Validation et consistance interne d’une batterie de tests pour l’évaluation multidimensionnelle de la lecture en français
Bibliographic record
Abstract
Nous présentons les considérations théoriques qui guident l’élaboration de la batterie de tests destinée à l’évaluation de la lecture en français. Ensuite, nous étayons les cinq domaines ciblés par la Batterie d’épreuves multidimensionnelles pour l’évaluation de la lecture (BÉMÉL) : a) la sensibilité phonologique, b) les connaissances alphabétiques, c) l’identification des mots réels ou inventés, d) la sensibilité grammaticale, e) la compréhension des phrases et des textes. Nous rapportons les résultats d’une étude sur huit échelles de mesure représentant trois de ces domaines. Ces résultats attestent que la consistance interne des échelles est satisfaisante et que l’augmentation de la performance en fonction du niveau scolaire appuie la validité des concepts représentés par ces échelles. Nous concluons avec quelques observations sur le développement à venir.
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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 | 0.060 | 0.165 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".