Le contexte et la raison : agir contre la violence à l’école par « l’évidence » ?
Bibliographic record
Abstract
Le présent article examine l’importance qu’ont prise dans la littérature scientifique les méta-analyses sur la prévention de la violence à l’école. Le nombre, la qualité et l’importance de celles-ci ont produit un savoir à la fois critique (ce qui ne marche pas) et opérant (ce qui marche) qui est présenté dans le présent article. Toutefois, quel que soit ce savoir, il n’est pas aisément ni directement transposable dans l’action publique et cela montre quelques limites inhérentes au développement de politiques basées sur les preuves scientifiques, politiques qui contiennent sans doute une part d’illusion rationnelle. Cela ne remet pas forcément en cause cette approche, mais lui assigne une place plus modeste et réaliste.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".