Les microagressions raciales dans les établissements scolaires
Bibliographic record
Abstract
L’article explore les microagressions raciales dans les écoles et leur impact sur l’inclusion scolaire. À travers une étude menée auprès de douze directions d’école à dans la région métropolitaine de Montréal, il met en lumière les défis éthiques et pratiques liés à la gestion de ces microagressions. Développé par Derald Wing Sue, le concept de microagression englobe des comportements subtils et souvent involontaires qui véhiculent des messages discriminatoires. Ces microagressions, qui nuisent au climat scolaire et à l’inclusion, se manifestent sous trois formes : les micro-assauts, les micro-insultes et les micro-invalidations. L’article insiste sur l’importance de mettre en oeuvre des stratégies d’intervention, de la formation continue et des politiques claires pour créer un environnement scolaire inclusif en engageant tous les actrices et les acteurs éducatifs dans la lutte contre les microagressions.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".