Regard transactionnel sur l’effet des stratégies punitives mobilisées par l’enseignant auprès des élèves présentant des problèmes de comportements extériorisés
Bibliographic record
Abstract
Les stratégies punitives sont utilisées par plusieurs enseignants pour réduire les comportements extériorisés chez les élèves. Cet article décrit, à l’aide d’un modèle transactionnel, comment ces stratégies affectent les interactions entre l’enseignant et l’élève qui présente des problèmes de comportements extériorisés. L’utilisation de ces stratégies est susceptible de maintenir, voire d’exacerber les problèmes de comportement, en plus d’entrainer un cycle d’échec scolaire, tout en favorisant une augmentation des situations conflictuelles avec l’élève et l’augmentation des risques pour l’enseignant de développer de l’épuisement professionnel. La dernière section de cet article présentera certaines pistes de solutions, dont la formation continue, afin de prévenir les situations conflictuelles et l’utilisation chez les enseignants de stratégies punitives.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.011 | 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".