Bibliographic record
Abstract
Au Canada et au Québec, traiter des questions liées à la diversité culturelle et au racisme a été un défi pour les gouvernements depuis les années soixante. Auparavant et jusqu'à présent, une grande partie des responsabilités en termes de développement ethnoculturel sensible des services publics (services sociaux, des programmes de formation en travail social, etc.) ont été laissés aux mains d’organismes de charité non-lucratifs. Cependant, peu à peu, depuis les années soixante, le gouvernement fédéral et le gouvernement provincial, ont dû développer des politiques et des programmes d'action. Au Québec, le travail social a fait partie du débat face à deux grands courants politiques, l’un canadien basé sur le multiculturalisme, et l’autre québécois basé sur l'interculturalisme. L'article vise à donner une perspective historique sur la façon dont le travail social a dû faire face à des contradictions différentes. In Canada and Quebec, dealing with issues related to cultural diversity and racism has been a challenge for the governments since the sixties. Before and up to our days, a large part of responsabilities in terms of developping ethnocultural sensitive public services (social services, training programs in social work, etc.) have been left in the hands of non profit and charity organizations. But, little by little, since the sixites then, both governements, federal and provincial had to develop politics and programs of action. In Quebec, social work has been part of the debate facing two mainstream politics, the canadian one based on multiculturalism and, in Quebec, on interculturalism. The article intends to give a historical perspective on how social work had to deal with different contradictions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.020 | 0.013 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".