DISCRIMINATION À L’EMBAUCHE DES CANDIDATES D’ORIGINE MAGHRÉBINE DANS LA RÉGION DE LA CAPITALE-NATIONALE
Bibliographic record
Abstract
Pour des CV semblables en tout point, Samira Benounis recevra-t-elle moins d’invitations à un entretien d’embauche que Valérie Tremblay dans la région de la Capitale-Nationale (Québec, Canada) ? Cet article tente de répondre à cette question à partir d’une expérience utilisant la méthode de testing par envoi de CV fictifs. Nos résultats suggèrent que, toutes choses égales par ailleurs, la probabilité d’être invitée à un entretien d’embauche diminue d’environ 10 unités de pourcentage lorsque la candidate a un nom d’origine maghrébine plutôt que québécoise. Ce constat suggère la présence d’une discrimination à l’embauche des candidates d’origine maghrébine dans la région de la Capitale-Nationale.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".