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Record W2736995564 · doi:10.1177/0146167217718169

Anger Promotes Economic Conservatism

2017· article· en· W2736995564 on OpenAlex
Keri L. Kettle, Anthony Salerno

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

VenuePersonality and Social Psychology Bulletin · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIdeologyConservatismAngerSocial psychologyPsychologyPoliticsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Research suggests that certain facets of people's political ideals can be motivated by different goals. Although it is widely accepted that emotions motivate goal-directed behavior, less is known about how emotion-specific goals may influence different facets of ideology. In this research, we examine how anger affects political ideology and through what mechanisms such effects occur. Drawing on the dual-process motivational model of ideology and the functionalist perspective of emotion, we propose that anger leads people to support conservative economic ideals, which promote economic independence and discourage societal resource sharing. Four studies support our hypothesis that anger can enhance support for an election candidate espousing conservative economic ideals. We find that anger shifts people toward economic conservatism by orienting them toward competition for resources. Implications and future research on the relationship between emotions and political ideology are discussed.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score1.000

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 studies0.0040.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.380
Teacher spread0.311 · 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