Discrimination et linguicisme au Québec : Enquête sur la diversité ethnique au Canada
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
After defining discrimination and linguicism, the first part of the paper provides a brief overview of employment problems experienced by minority groups in Quebec. Part two offers results from a special analysis of the Ethnic Diversity Survey (2003) dealing with experiencing discrimination in Quebec and in the rest of Canada. Results show that in Quebec, anglophones are more likely to report being victims of discrimination than francophones and language/accent is seen as the main cause of discrimination for both francophones and anglophones. In the rest of Canada skin colour is seen as the main cause of discrimination for anglophones, while francophones see language/accent as the main cause of discrimination. Clearly linguicism is seen as the main cause of discrimination in Quebec for both francophones and anglophones, while this is the case only for francophones in the rest of Canada
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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