Questionnaire d'évaluation du comportement de l'enfant: Version canadienne française du Toddler Behavior Assessment Questionnaire.
Bibliographic record
Abstract
Cette etude vise a valider le Questionnaire d'evaluation du comportement de l'enfant (QECE), une version canadienne francaise du Toddler Behavior Assessment Questionnaire (TBAQ; Goldsmith, 1996) qui est utilise afin d'evaluer cinq dimensions du temperament des enfants âges de 15 a 36 mois : niveau d'activite, tendance a exprimer du plaisir, crainte sociale, predisposition a la colere et interet/attention. Un echantillon de 122 enfants de 15 mois a ete evalue a l'aide du QECE. Cent six d'entre eux ont ete reevalues avec le QECE une deuxieme fois trois mois plus tard (a 18 mois). Cent deux des enfants avaient ete precedemment evalues a dix mois a l'aide du Infant Characteristics Questionnaire (ICQ, Bates, Freeland & Lounsbury, 1979), un questionnaire mesurant le temperament durant la premiere annee de vie. Les resultats demontrent que les echelles du QECE ont une coherence interne et une stabilite temporelle adequate. De plus, les resultats demontrent que les echelles du QECE possedent des proprietes discriminantes adequates et que le QECE possede une bonne validite convergente avec l'ICQ. Les proprietes psychometriques du QECE, sa facilite et rapi-dite d'administration et de cotation et sa capacite a fournir de l'information concernant plusieurs dimensions du temperament font de celui-ci un questionnaire tres interessant a utiliser dans la recherche sur le developpement des enfants.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".