Canadian Policy of Multiculturalism: Citizenship, Institutional Adjustments, and Fairness
Bibliographic record
Abstract
Multiculturalism as a policy has been implemented in Canada for nearly thirty years. What kind of influence did it have on the Canadian society? Which criticisms did it raise? Which unexpected effects did it have? And what kind of adjustments has been introduced? In this paper, I will try and evaluate a policy which has been considered quite often in France as pertaining only to the North-American context, and as being therefore irrelevant with regard to the French Republican one. I will attempt to describe the concrete measures related to this policy within three different social areas: the voluntary associations representing ethnic minorities, the school system which plays a central role in terms of “management” of ethnic and religious diversity, and the organization of labor, taking as an example the implementation in Quebec of equity measures meant to insure an equal access to job opportunities.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.029 | 0.017 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".