Bibliographic record
Abstract
Outre la famille, l’école est le principal milieu de vie des jeunes de cinq à 16 ans, et le milieu de travail de bon nombre d’adultes. Comme dans tous les milieux de vie, des événements tragiques y surviennent sous diverses formes, laissant les uns et les autres désemparés, démunis, atterrés. Dans de telles situations, que doit-on faire ? Que doit-on dire ? Toutes les personnes touchées, élèves, enseignants, membres de la direction, personnels de soutien et parents pressentent qu’il faut en parler, qu’on ne peut garder son émotion pour soi. Mais comment aborder le thème de la mort avec les enfants et les adolescents ? Doit-on le faire en classe ou hors des heures de classe ? Comment le faire ? Peut-on organiser un rituel pour faciliter le deuil à l’école ? Va-t-on faire souffrir les enfants plus que nécessaire en discutant de la mort avec eux ? Toutes ces questions et bien d’autres, que se posent enseignants, parents et directions d’école sont légitimes et méritent, par conséquent, qu’on y réfléchisse.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".