Bibliographic record
Abstract
Abstract This chapter uses the critical framework to examine the development of social work as a profession in Canada as well as the sociopolitical and economic contexts of education and practice. Canada runs a parliamentary democracy as a (con)federation of 10 provinces and three territories, with the queen/king of England as the constitutional monarch. This political and power arrangement affects how social work is structured, with implications for the provision of social welfare services for citizens. Indeed, many social welfare programs are still organized around some of the principles of the British Poor Laws, and early social workers were agents of the state, exerting social control over Indigenous and racialized populations, thereby contributing to the historic practice failure of social work in Canada. Conversely, there were also progressive elements within the same history that were connected to the Settlement House Movement upon which many schools of social work were founded. As a profession mandated by law, social work has regulatory and accrediting bodies in different provinces as well as professional organizations that manage its affairs. It also has different areas of practice and job prospects for graduates. It is part of the accreditation standard that all social work students take courses on social justice/social change and social policy. However, there is limited discussion of political social work. This chapter proposes an intentional professional commitment to political education by calling for the training of social work students to understand their own political power in a neoliberal 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.015 | 0.010 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".