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Why Are Conservatives Happier Than Liberals?

2008· article· en· W2105073095 on OpenAlexfundno aff
Jaime L. Napier, John T. Jost

Bibliographic record

VenuePsychological Science · 2008
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
FundersInstitute of Population and Public Health
KeywordsHappinessIdeologyPsychologyPoliticsSocial psychologyRationalization (economics)ConservatismInequalityBiology and political orientationSystem justificationEconomic inequalitySubjective well-beingPositive economicsEconomicsLawPolitical science

Abstract

fetched live from OpenAlex

In this research, we drew on system-justification theory and the notion that conservative ideology serves a palliative function to explain why conservatives are happier than liberals. Specifically, in three studies using nationally representative data from the United States and nine additional countries, we found that right-wing (vs. left-wing) orientation is indeed associated with greater subjective well-being and that the relation between political orientation and subjective well-being is mediated by the rationalization of inequality. In our third study, we found that increasing economic inequality (as measured by the Gini index) from 1974 to 2004 has exacerbated the happiness gap between liberals and conservatives, apparently because conservatives (more than liberals) possess an ideological buffer against the negative hedonic effects of economic inequality.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.092
GPT teacher head0.384
Teacher spread0.291 · 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

Citations590
Published2008
Admission routes1
Has abstractyes

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