Adaptation et validation d’instruments de mesure des stéréotypes de genre en mathématiques et en français
Bibliographic record
Abstract
Le présent article expose les qualités psychométriques de l’adaptation de deux questionnaires destinés à des élèves francophones, qui évaluent les stéréotypes de genre en mathématiques, d’une part, et les stéréotypes de genre en français, d’autre part. Les résultats de deux études comprenant des élèves de sixième année du primaire, de deuxième et de quatrième secondaire [n (Étude 1) = 169 ; n (Étude 2) = 1 138] montrent que les instruments adaptés offrent une consistance interne élevée ainsi qu’une bonne validité concomitante. De plus, des analyses factorielles exploratoires et confirmatoires ont révélé une structure reflétant les sous-échelles adaptées et procurant de bons indices d’ajustement aux données. Les questionnaires proposés présentent donc des qualités psychométriques satisfaisantes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".