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Record W2923638604 · doi:10.1111/jssr.12595

Beyond “Heartless Conservative” and “Bleeding Heart Liberal” Caricatures: How Religiosity Shapes the Relationship Between Political Orientation and Empathy

2019· article· en· W2923638604 on OpenAlexaff
Scott Schieman, Alex Bierman, Laura Upenieks

Bibliographic record

VenueJournal for the Scientific Study of Religion · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsUniversity of CalgaryUniversity of Toronto
Fundersnot available
KeywordsEmpathyReligiosityBiology and political orientationPoliticsContext (archaeology)Social psychologyPsychologyOrientation (vector space)Political scienceLawGeography

Abstract

fetched live from OpenAlex

Abstract Is political orientation associated with self‐reported empathy? Popular caricatures frame political orientation in terms of the “heartless conservative” and the “bleeding heart liberal.” Yet, previous research has produced findings that present mixed evidence to support these caricatures. Using data from the 2004 General Social Survey, analyses show that the caricatures of the caring liberal and the cold‐hearted conservative are supported by results for empathy—in which conservatives have lower levels of empathy than liberals—but this pattern holds only when individuals also have low levels of religiosity. In the context of high religiosity, self‐identified conservatives do not have lower empathy than self‐identified liberals, net of a host of sociodemographic characteristics. Our observations demonstrate that patterns in empathy across political orientation are evident only when levels of different forms of religiosity are considered.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0010.000
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 head0.061
GPT teacher head0.372
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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

Citations11
Published2019
Admission routes1
Has abstractyes

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