The Evolving Politics of Race and Social Work Activism: A Call across Borders
Bibliographic record
Abstract
Social work has engaged with and led the revolutionary social movements of the past century. Yet today, as activism by and for racial others unfolds across the United States and Canada, our discipline remains largely silent. This article considers new ways for social workers to conceptualize social work activism, challenge the existing erasures within the profession, and construct innovative strategies to locate social work within the critical social movements of our time. Recognizing the continuity of histories of colonialism, slavery, and genocide, the author argues that social workers must engage with racialized communities' resistance through their legacy of exclusion and displacement. The author demonstrates the significance of an evolving politics of race and social justice for social work practice.
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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 | 0.023 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.024 | 0.133 |
| Scholarly communication | 0.031 | 0.032 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.012 | 0.015 |
| 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".