Covert forms of resistance: Reimagining feminist social work praxis in an increasingly neoliberal world
Bibliographic record
Abstract
Social work as a profession has long claimed its roots in and orientations towards social justice. The realities of enacting social justice as a social worker, however, have proven to be more complex than what is typically taught in social work education programs. Neoliberal ideology has so pervasively impacted social work praxis that many burgeoning social workers often face disillusionment, discouragement, and discomfort when settling into the profession. While social workers enter the field emboldened to create meaningful social change, they encounter barriers characteristic of neoliberalism such as managerialism, professionalization, and bureaucracy. As doctoral social work students who have learned, practiced, and taught social work, we have experienced this phenomenon firsthand. In this article, we reflect upon and work to make sense of these experiences, which we frame as a “cruel optimism” of social work, or the “condition of possibility whose realization is discovered either to be impossible, sheer fantasy” (Berlant, 2011, p. 24). Through engaging in a critically reflexive conversational methodology, we consider the breakdown between the social justice theory that students are often taught and the realities of practice that social workers face in the field, as illustrated by three vignettes. This is rooted in particular analysis of feminist social work praxis, of which all the authors subscribe. We then reimagine new ways to practice feminist social work in the neoliberal landscape, including specific recommendations for how to engage in covert forms of resistance as we collectively repoliticize social work praxis.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.022 | 0.114 |
| Scholarly communication | 0.021 | 0.024 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 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".