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Record W2618708008 · doi:10.1177/0143831x17715768

‘How could management let this happen?’ Gender, unpaid work and industrial relations in the nonprofit social services sector

2017· article· en· W2618708008 on OpenAlexfundaboutno aff
Donna Baines, Ian Cunningham

Bibliographic record

VenueEconomic and Industrial Democracy · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRestructuringWorkforceIndustrial relationsManagerialismAgency (philosophy)CorporatismGovernment (linguistics)Trade unionTemporary workPrivate sectorPublic administrationWelfare stateSocial WelfareSocial dialoguePoliticsLabour lawLabour economicsPolitical sciencePolitical economySociologyEconomicsWork (physics)Economic growthLawSocial science

Abstract

fetched live from OpenAlex

In order to compete in increasingly tight quasi-markets generated by government cutbacks and contracting-out, management in nonprofit agencies have argued that wages and benefits must be reduced or jobs and services will be cut. These arguments have motivated some of the female-majority workers to join and/or organize unions and undertake strike action. Focusing on two case studies exploring restructuring in the highly gendered nonprofit social services in two liberal welfare states (Scotland and Canada), this article explores shifts in industrial relations at the agency level, as well as workforce resistance and union activism. Through the analysis of gendered unpaid work and gendered forms of social and union solidarity, this article extends feminist political economy and mobilization theory. It also suggests convergences at several layers of practice and policy, including private and nonprofit industrial relations cultures, managerialism and the underfunding of contracted-out government services.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.081
GPT teacher head0.292
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2017
Admission routes2
Has abstractyes

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