Lean social care and worker identity: The role of outcomes, supervision and mission
Bibliographic record
Abstract
Since the 1980s, many social care jobs have shifted from the public to the nonprofit sector, accompanied by funding cuts, government contracts, managerialism and performance management. Qualitative data collected in Australia, New Zealand and Canada show that agency mission and immediate supervisors remain centrally important to workers’ identity and willingness to remain employed in social care. With the exception of one study site (where targets were jointly resisted by managers and staff), outcome measures were seen by workers to detract from the quality of care and erode social justice. This article argues that agency mission and supportive supervision buffer the impact of poor wages and conditions in the sector, while outcome measures undermine workers’ identities as caring people, in effect making the ‘self’ a site of struggle and discontent. Resistance strategies that agencies, workers and unions have used to challenge the hegemony of outcome-oriented funding and management models are explored.
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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 | 0.025 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".