Occupying Social Work: Unpacking Connections and Contradictions in the Social Work/Activist Divide
Bibliographic record
Abstract
We are interested in how social work and activism fit, connect and contradict each other. As academics, activists and social workers, we consistently grapple with the tensions between these realms and how we configure ourselves and our work into these spaces. This pilot project was initially undertaken by Emma, an undergraduate social work student, under the supervision of May, an assistant professor of social work, as a means of blending our diverse identities and subject positions while allowing us to analyze the relationships between social work and activism. We were able to use our own different roles and ideas as a jumping off point that led to Emma interviewing eight other people (who identified, variously, as social workers and/or activists), allowing for a rich and multifarious conversation to emerge. While neither social work nor activism nor any other form of protest and resistance can single-handedly engender utopia, this research has confirmed what our lived experiences have suggested: that individual connections, communities, social movements, educational models and radical alternatives must continue an engaged dialogue in order to constructively co-exist.
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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 | 0.029 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.025 | 0.123 |
| Scholarly communication | 0.032 | 0.034 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".