L’analyse intersectionnelle et l’approfondissement de la compréhension des violences sexistes par Femmes et villes international
Bibliographic record
Abstract
Depuis quelques années, l’organisation Femmes et villes international emploie une approche intersectionnelle dans ses projets et ses mandats concernant la prévention et la réduction des violences sexistes en milieu urbain. Cette approche particulièrement utile lui permet de mettre en lumière les intersections entre les oppressions en jeu dans la construction du sentiment de sécurité dans les espaces publics. À partir des principes de l’intervention féministe intersectionnelle, l’auteure analyse les approches et les méthodes de travail de l’organisation afin de mettre en relief des pratiques en vue d’améliorer la collaboration avec les communautés dans des projets locaux et internationaux.
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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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".