The Shifting Labour Process in Professional Care: Recreating Dominance and the Managerialised Mental Health Social Worker
Bibliographic record
Abstract
Abstract Though the rationalisation of health care has been well documented, less is known about its impacts on mental health social workers. Drawing on qualitative data collected from 120 interviews and the qualitative comments on a Canadian four-province survey, the article explores the shifting labour process through profession-linked and organisational care strategies. The article argues that power is shifted from mental health social workers to management through stratagems including managerialism, biomedical hegemony and team-based care. These processes are complex and dynamic, travelling along professional divisions and logics, appearing neutral and scientific rather than as conduits reinforcing neoliberalised approaches to health care provision. Social workers’ resistance to these models of care is similarly complex and professionally based, though with strong elements of gendered altruism and social justice themes. Though this article draws on Canadian data, the analysis is likely highly applicable to other managerialised contexts including the UK. The article contributes to the intersection of Labour Process Theory and moral economy theory by highlighting the operation of a unique form of engagement referred to here as resistance-as-engagement. Overall, mental health social workers revealed strong oppositional narratives and identities pivoting on their marginalised position within team-based care, medical professional hierarchies and narrow, neoliberal approaches.
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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 | 0.020 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.027 | 0.089 |
| Scholarly communication | 0.018 | 0.009 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.004 | 0.006 |
| 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".