Contribution des buts d'accomplissement en éducation physique sur la pratique d'activités physiques: comparaison entre classes spécialisées et classes ordinaires
Bibliographic record
Abstract
Résumé : \nCette étude examine la contribution des buts poursuivis en éducation physique sur la pratique d’activités physiques de loisirs (PAP) d’élèves du secondaire (N = 277) en fonction du type de classe (ordinaire ou spécialisée). Les analyses de pistes causales ont révélé que les attitudes et le sentiment de compétence (SC) des élèves prédisaient positivement la PAP et que les attitudes étaient associées positivement au climat de maîtrise, au SC et aux buts de maîtrise, et négativement aux buts de performance-évitement. Les tests d’invariance ont montré que le modèle était statistiquement invariant selon les deux types de classes. Cette recherche met en valeur l’importance du climat motivationnel en éducation physique pour mieux prédisposer les jeunes à maintenir la PAP en dehors des heures de classe. \nAbstract: \nThis study examines the contribution of the goals pursued in physical education to the practice of leisure-time physical activity (LTPA) among high school students (N = 277) according to class type (regular or special education). Path analysis revealed positive relationships between LTPA and the students' attitudes and their perceived competence (PC). Their attitudes were positively associated with mastery climate, PC, and mastery goals, and negatively associated with performance-avoidance goals. Invariance analyses revealed that the model was statistically invariant for both types of classes. This research supports the importance of motivational climate as a determinant of students' predispositions to be active outside of physical education classes. © 2020 Canadian Society for the Study of Education.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".