Discrimination systémique et intersectionnalité : la déqualification des immigrantes à Montréal
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it