Immigration policies of the government of Quebec in the context of Canadian multicultural policies. Contextual Notes for a social work ethnic environment.
Bibliographic record
Abstract
The English-speaking Canada and the rebellious Frenchspeaking «province» of Quebec are going through a broad and deep identity crisis that dates back to the 19th century, but intensified in the new age of globalization. A country created by immigration, it is still a country of immigration and one of the most multiethnic countries in the world. Multiculturalism is the model of political management that belongs to this diversity and the ideology that legitimates it —a Canadian inventio— at the same time that it recognizes, ignores and eludes the internal conflict —the Canada-Quebec conflict— that implicitly determines the differentiated migratory policies of both political communities. On its part, Quebequian multiculturalism («interculturalism») shows two different models (pro-assimilation and pro differentiation). These tensions, ambiguities, and diversity of models shape the current Canadian and Quebequian debate about citizenship, which conditions and functions as a frame of reference for social work (professional social intervention) with immigrants, very developed both in theory and in practice in this American country, and that is aware of the political challenges offered by multiculturalism in Ottawa and Quebec. The study and evaluation of this dynamic reality can be extremely useful in Europe, both North and South, for working out public policies and organizing social work in a multiethnic environment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".