Fragmented outcomes: International comparisons of gender, managerialism and union strategies in the nonprofit sector
Bibliographic record
Abstract
Since the mid-1980s, the nonprofit social services sector has been promoted as an option for cheaper and more flexible delivery of services. In order to comply with government standards and funding requirements, the sector has been subject to ongoing waves of restructuring and the introduction of new private market-like, outcomes-based management models, such as New Public Management. This article explores ways in which nonprofit social services sector workers experience their work as highly fragmented. Drawing on case studies completed as part of a larger project addressing restructuring in the nonprofit social services sector in Scotland, New Zealand, Australia and Canada, we examine three key aspects shaping work in the nonprofit social services sector: 1) workers’ experience of managerialism; 2) gendered strategies drawn on by workers in the agencies studied; and 3) union strategies in the nonprofit social services sector, as well as within individual workplaces. Conclusions focus on contributions to understanding managerialism as a strong but fragmented project in which even weak union presence and the willingness of the predominantly female workforce to sacrifice to provide care for others ensure that some level of social solidarity endures.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".