Shaping Canadian citizens: A historical study of Canadian multiculturalism and social work during the period from 1900 to 1999
Bibliographic record
Abstract
Canadian multiculturalism is a source of national pride and Canada’s national identity. Despite this, the marginalization of migrants, Indigenous, and non‐White Canadians has persisted while (re)constructing Canadian citizens and nationhood. Using a Foucauldian genealogical approach, we explored how the social work profession has addressed this paradox around shifting Canadian national identities and multiculturalism while developing its professionalization across various historical junctures in the 20th century. Our findings reveal that, since its inception, the social work profession has negotiated with dominant discourses. In the collective response as a profession, the omission of attention and subsequent inaction to exclusion and marginalization is apparent. However, through the construction of counter discourses, individual social workers’ resistance to social injustice has been noteworthy. Identifying and documenting these counter discourses across significant historical periods thus contributes to rewriting Canadian social work history that reinvigorates our social work core values of justice and respect for all. Key Practitioner Message: • The study provides a critical analysis of the history of Canadian Social Work practice in relation to multiculturalism; • It can be used for pedagogical purposes (critical discussion and evaluation); • It raises awareness of historical social work blind spots.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.052 | 0.018 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".