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Record W2295415823 · doi:10.1177/1035304615627950

Deprivileging the public sector workforce: Austerity, fragmentation and service withdrawal in Britain

2016· article· en· W2295415823 on OpenAlexfundno aff
Stephen Bach

Bibliographic record

VenueThe Economic and Labour Relations Review · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAusterityPublic sectorRestructuringWorkforceEconomic policyCoalition governmentEconomicsGovernment (linguistics)Public serviceLabour economicsPublic administrationPolitical scienceEconomyEconomic growthFinancePolitics

Abstract

fetched live from OpenAlex

Abstract The impact of the financial crisis has reignited debate about the scope and scale of public sector restructuring and its consequences for the workforce in Britain. The economic crisis precipitated austerity measures concentrated on expenditure reductions with the intention of reducing the public deficit. Because the public sector pay bill comprises over half of current public spending, achieving deficit reduction has major consequences for the total pay bill and the workforce. This article assesses the restructuring of the public sector and public sector employment relations in Britain and identifies underlying continuities in public sector restructuring over recent decades. Drawing on and repositioning New Labour’s legacy, the Coalition government used the economic crisis to establish a pro-austerity frame that has legitimated deep cuts in public sector employment and involved measures to refashion public sector employment relations. The article considers the consequences of this agenda and responses by trade unions and indicates some of the limits and uncertain prospects for public sector restructuring under conditions of austerity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0010.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.034
GPT teacher head0.311
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations40
Published2016
Admission routes1
Has abstractyes

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