Bibliographic record
Abstract
ContextSocial work has experienced long-standing tensions between care and control since its inception.As shifting moral, social, political, intellectual, and market forces have historically shaped social work agendas and practices, so have feminists through politics, research, teaching, and praxis.While radical and critical social work has frequently pushed back against oppressive systems and movements, social work and feminist social work frequently find itself colluding with and/or being coopted by institutions and systems that oppress, coerce, and control certain people and communities.We need not look far for evidence of these tensions, including but not limited to social work practice and interventions steeped in carceral logics and rescue-based work poignantly evidenced by the now defunct Project Rose (Wahab & Panichelli, 2013).Gramsci (1992), pessimism of the mind, optimism of the will, captures the spirit from which we write this editorial, and we turn to paperson's (2017) A Third University Is Possible for inspiration and critical hope, as we contemplate the tensions above and the emotions they engender.The bits of machinery that make up a decolonizing university are driven by decolonial desires, with decolonizing dreamers who are subversively part of the machinery and part of machine themselves.These subversive beings wreck, scavenge, retool, and reassemble the colonizing university into decolonizing contraptions.They are scyborgs with a decolonizng desire.You might choose to be one of them.(p.xiii) Rather than wonder about dismantling existing institutions in order to build new ones, paperson inspires us to ask, how might social workers and social work scholars repurpose social work institutions and technologies for more emancipatory and decolonizing agendas?How might we embrace and join the scyborg "the decolonizing ghost in the colonizing machine" (p.xxiv) to decolonize social work?
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.022 | 0.053 |
| Scholarly communication | 0.022 | 0.015 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".