MétaCan
Menu
Back to cohort
Record W2136071512 · doi:10.2190/hs.42.3.a

Social Class, Politics, and the Spirit Level: Why Income Inequality Remains Unexplained and Unsolved

2012· article· en· W2136071512 on OpenAlexaff
Nanky Rai, Edwin Ng, Haejoo Chung

Bibliographic record

VenueInternational Journal of Health Services · 2012
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of WindsorUniversity of Toronto
Fundersnot available
KeywordsEconomic inequalityPoliticsInequalitySocial inequalityCapitalismEconomicsArgument (complex analysis)SociologyDevelopment economicsPolitical economyPolitical scienceLawMedicine

Abstract

fetched live from OpenAlex

Richard Wilkinson and Kate Pickett's latest book, The Spirit Level: Why Equality is Best for Everyone, has caught the attention of academics and policymakers and stimulated debate across the left-right political spectrum. Interest in income inequality has remained unabated since the publication of Wilkinson's previous volume, Unhealthy Societies: The Afflictions of Inequality. While both books detail the negative health effects of income inequality, The Spirit Level expands the scope of its argument to also include social issues. The book, however, deals extensively with the explanation of how income inequality affects individual health. Little attention is given to political and economic explanations on how income inequality is generated in the first place. The volume ends with political solutions that carefully avoid state interventions such as limiting the private sector's role in the production of goods and services (e.g., non-profit sector, employee-ownership schemes). Although well-intentioned, these alternatives are insufficient to significantly reduce the health inequalities generated by contemporary capitalism in wealthy countries, let alone around the world.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.094
GPT teacher head0.452
Teacher spread0.358 · 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.

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

Citations9
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Health ServicesSame topicEmployment and Welfare StudiesFrench-language works237,207