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Record W2937567314 · doi:10.1177/1948550619843926

Subcomponents of Right-Wing Authoritarianism Differentially Predict Attitudes Toward Obeying Authorities

2019· article· en· W2937567314 on OpenAlexaff
Stephanie R. Mallinas, Jarret T. Crawford, Jeremy A. Frimer

Bibliographic record

VenueSocial Psychological and Personality Science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsObedienceAuthoritarianismSocial psychologyConstruct (python library)PsychologyMilgram experimentUnitary stateIdeologyAdjudicationMoralityPoliticsLawPolitical scienceDemocracy

Abstract

fetched live from OpenAlex

Previous theory and research has suggested that right-wing authoritarianism (RWA) is a unitary construct related to attitudes regarding obedience to authority. Recently, scholars have suggested that RWA is multidimensional. To adjudicate these competing notions, we test whether the associations between RWA components and moral attitudes regarding obedience differ depending on the ideology of the authority. Across three studies and an integrative data analysis, we found that the RWA component capturing obedience to and respect for authorities (i.e., submission) related to judgments that it is moral to obey all authorities, and perhaps also nonauthorities, regardless of the targets’ political ideologies. In contrast, the RWA component capturing socially conservative beliefs (i.e., traditionalism) related to judgments that it is moral to obey conservative authorities and immoral to obey liberal authorities. These results suggest that RWA is not a unitary construct and that its components differentially relate to moral judgments regarding obedience to authorities.

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)0.002
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 categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.080
GPT teacher head0.392
Teacher spread0.312 · 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; both teacher heads agree on what is shown here.

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

Citations27
Published2019
Admission routes1
Has abstractyes

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