Les inégalités « ethnoraciales » dans l’accès à l’emploi à Montréal : le poids de la discrimination1
Bibliographic record
Abstract
Dans cette étude reposant sur la méthode du testing, 581 paires de CV fictifs ont été envoyées en réponse à de véritables offres d’emplois dans des secteurs d’emploi qualifiés et peu qualifiés. Les CV appariés étaient similaires sous tous les rapports, hormis que l’un indiquait un nom « franco-québécois », et l’autre un nom tantôt arabe, tantôt latino-américain et africain. À profil égal, le candidat majoritaire a au moins 60 % plus de chances d’être invité à un entretien que les candidats des minorités racisées, et un peu plus d’une fois sur trois, ces derniers risquent d’être ignorés par l’employeur sur une base discriminatoire.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".