Discrimination systémique et intersectionnalité : la déqualification des immigrantes à Montréal
Bibliographic record
Abstract
Since the early 1990s, Canada and Québec have been selecting immigration candidates primarily on the basis of their professional qualifications, including any diplomas they hold, their professional experience, and their linguistic abilities. Paradoxically, statistics show that the professional status of women immigrants who have arrived since that time has been deteriorating and that they are more susceptible to experiencing a high unemployment rate, low income, and precarious working conditions. One of the particularly worrisome aspects of this situation is the fact that despite their high qualifications, more and more women immigrants are permanently occupying jobs for which they are over-qualified. The author presents the results of research that explores the downgrading of women immigrants who hold a foreign university degree and who live in Montreal. The significance of this research is that, through a systemic approach, it attempts to better understand why some women immigrants experience a higher level of downgrading, while others manage to escape this predicament.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".