Trois mesures du vocabulaire chez des élèves d’écoles françaises du Nouveau-Brunswick
Bibliographic record
Abstract
La mesure du vocabulaire des jeunes néo-brunswickois se heurte à la rareté des tests disposant de normes adaptées et de données psychométriques actuelles. Trois tests de vocabulaire se prêtant bien à une utilisation individuelle ou de groupe sont analysés dans la présente étude : le test de vocabulaire Binois-Pichot (1959), le sous-test vocabulaire du Test collectif d’intelligence générale (Lavoie et Laurendeau, 1960) et le test de vocabulaire Mill Hill (Deltour, 1993). Trois échantillons d’élèves de la quatrième à la huitième année d’écoles françaises du Nouveau-Brunswick ont été examinés à l’aide de l’un de ces trois tests de vocabulaire. Les qualités métrologiques ainsi que des données normatives préliminaires sont rapportées pour chacun des trois instruments.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".