Contextes de perte d’une figure d’attachement chez des élèves du primaire : identification de besoins éducatifs particuliers et implications pour la formation enseignante
Bibliographic record
Abstract
À partir de données issues d’une rencontre de groupe dans le cadre d’une recherche qualitative, cet article met en avant les expériences de cinq enseignantes du primaire dont un élève a été confronté à la perte d’un lien d’attachement familial. Les résultats présentés soulignent les besoins éducatifs spéciaux des élèves concernés par une telle perte, le manque de ressources disponibles pour les enseignants et de préparation de l’équipe-école pour accompagner ces élèves. Des recommandations pour la formation enseignante sont ainsi formulées afin de répondre aux besoins éducatifs spéciaux des élèves endeuillés et ainsi soutenir leur adaptation scolaire et sociale.
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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 | 0.005 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".