La trousse TAMARIN pour prévenir les difficultés comportementales en contexte éducatif : qu’en disent les enseignant·e·s du préscolaire et primaire ?
Bibliographic record
Abstract
La trousse TAMARIN a été développée pour prévenir les difficultés comportementales des élèves, garçons et filles. Elle inclut une formation en ligne et des outils de dépistage et d’action préventive. Cette étude qualitative vise à recueillir la perception des utilisatrices et leurs recommandations. Des 203 enseignantes ayant expérimenté la trousse, 19 ont participé à des entretiens semi-structurés. L’analyse thématique a permis d’identifier plusieurs facilitateurs à l’adoption de la trousse. En effet, la flexibilité, la rapidité et la simplicité d’utilisation, le respect de leur professionnalisme de même que la pertinence et la complétude du contenu facilitent l’adoption de la trousse par les enseignantes.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".