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Record W4313179885 · doi:10.51952/9781529208689.fm001

Frontmatter

2020· book-chapter· en· W4313179885 on OpenAlexfundno aff

Bibliographic record

VenueBristol University Press eBooks · 2020
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
FundersSimon Fraser UniversityUniversiteit van AmsterdamEdinburgh Napier UniversityMcMaster UniversityMiddlesex UniversityCardiff UniversityUniversity of St AndrewsUniversity of LimerickYork University
KeywordsAusterityNeoliberalism (international relations)Political sciencePrivate sectorPolitical economyEconomicsLawPolitics

Abstract

fetched live from OpenAlex

Austerity was presented as the antidote to sluggish economies, but it has had far-reaching effects on jobs and employment conditions. This book goes beyond a sole focus on public sector work and uniquely covers the impact of austerity on work across the private, public and voluntary spheres. The book begins with an introduction to some of the major debates concerning austerity, neoliberalism, and work. Austerity is viewed as a set of interwoven policies aimed at reducing public debt and expenditure, increasing consumer taxes and purportedly stimulating economic wellbeing through corporate tax cuts and support for private business. Since the 1970s, austerity policies have been closely associated with neoliberalism, a set of policies and processes that valorize the private-market as the solution to all social and economic problems and seek to reduce or eliminate social entitlements and public provision. Drawing on a range of perspectives, the book engages with the major debates surrounding austerity and neoliberalism, providing grounded analysis of the everyday experience of work and employment.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.123
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.8770.795

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 head0.037
GPT teacher head0.175
Teacher spread0.138 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

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