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Record W2024383087 · doi:10.1017/s0047279413000056

Fairness and the Politics of Resentment

2013· article· en· W2024383087 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Social Policy · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicPopulism, Right-Wing Movements
Canadian institutionsBlackberry (Canada)
FundersEconomic and Social Research Council
KeywordsResentmentPopulismAusterityReactionaryPoliticsPolitical economyWelfarePolitical sciencePunitive damagesFraming (construction)FeelingSociologySocial psychologyLawPsychology

Abstract

fetched live from OpenAlex

Abstract The role of the emotions in the framing of welfare policies is still relatively underexplored. This article examines the role of resentment in the construction of a particular form of ‘anti-welfare populism’ advanced by the Coalition Government in the UK after 2010. We argue that UK political parties have appropriated the discourse of fairness to promote fundamentally divisive policies which have been popular with large sections of the electorate including, paradoxically, many poorer voters. In focus group research in white working class communities in the UK undertaken just before the 2010 General Election, resentments related to perceived unfairness and loss emerged as very strong themes among our respondents. We examine such resentments in terms of an underlying ‘structure of feeling’ which fuels the reactionary populism seen in ‘anti-welfare’ discourses. These promote increasingly conditional and punitive forms of welfare in countries experiencing austerity, such as the UK, creating rivalries rather than building solidarities amongst those who ‘have little’ and drawing attention away from greater inequalities.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.989

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.348
Teacher spread0.326 · 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