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Record W2799585418 · doi:10.1080/15298868.2018.1468354

Is there a place in politics for compassion? The role of compassion in predicting hierarchy-legitimizing views

2018· article· en· W2799585418 on OpenAlexaff
Vanessa M. Sinclair, Donald H. Saklofske

Bibliographic record

VenueSelf and Identity · 2018
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsWestern University
Fundersnot available
KeywordsSocial dominance orientationPsychologyCompassionSocial psychologyEgalitarianismEmpathyHierarchyPoliticsViewpointsBlameAuthoritarianismPolitical scienceDemocracy

Abstract

fetched live from OpenAlex

Political beliefs underlie behaviors including voting and participation in collective resistance. Hierarchy-legitimizing beliefs can justify and perpetuate extant social hierarchies, such as economic inequality. Individual differences are important predictors of many political beliefs, but the role of compassion in this context has not been explored. This study investigated the relationship between dispositional compassion, which has shown promise in predicting enhanced prosociality, with hierarchy-legitimizing viewpoints, mediated by social dominance orientation (SDO). A sample of 590 undergraduate students completed measures of compassion, empathy, SDO, and sociopolitical policy views. Structural equation modeling showed that SDO mediated the relationship between compassion and hierarchy legitimization. The findings have implications for compassion’s relevance in political psychology, and for expanding understanding of the antecedents of anti-egalitarianism.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.068
GPT teacher head0.388
Teacher spread0.320 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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