MétaCan
Menu
Back to cohort
Record W2114038289 · doi:10.1177/1368430204046142

Evolved Disease-Avoidance Mechanisms and Contemporary Xenophobic Attitudes

2004· article· en· W2114038289 on OpenAlexafffund
Jason Faulkner, Mark Schaller, Justin H. Park, Lesley A. Duncan

Bibliographic record

VenueGroup Processes & Intergroup Relations · 2004
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMortality saliencePsychologySalience (neuroscience)Social psychologyFeelingImmigrationDiseaseCognitionIngroups and outgroupsVulnerability (computing)Terror management theoryDevelopmental psychologyCognitive psychologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

From evolutionary psychological reasoning, we derived the hypothesis that chronic and contextually aroused feelings of vulnerability to disease motivate negative reactions to foreign peoples. The hypothesis was tested and supported across four correlational studies: chronic disease worries predicted implicit cognitions associating foreign outgroups with danger, and also predicted less positive attitudes toward foreign (but not familiar) immigrant groups. The hypothesis also received support in two experiments in which the salience of contagious disease was manipulated: participants under high disease-salience conditions expressed less positive attitudes toward foreign (but not familiar) immigrants and were more likely to endorse policies that would favor the immigration of familiar rather than foreign peoples. These results reveal a previously under-explored influence on xenophobic attitudes, and suggest interesting linkages between evolved disease-avoidance mechanisms and contemporary social cognition.

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)0.002
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.065
GPT teacher head0.269
Teacher spread0.205 · 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

Citations865
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueGroup Processes & Intergroup RelationsSame topicPsychology of Moral and Emotional JudgmentFrench-language works237,207