MétaCan
Menu
Back to cohort
Record W1979363967 · doi:10.1177/0963721411402596

The Behavioral Immune System (and Why It Matters)

2011· article· en· W1979363967 on OpenAlexaff
Mark Schaller, Justin H. Park

Bibliographic record

VenueCurrent Directions in Psychological Science · 2011
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDisgustPsychologySocial psychologySet (abstract data type)Infectious disease (medical specialty)Extraversion and introversionXenophobiaCognitive psychologyPersonalityDiseaseBig Five personality traitsImmigration

Abstract

fetched live from OpenAlex

Like many other animals, human beings engage in behavioral defenses against infectious pathogens. The behavioral immune system consists of a suite of psychological mechanisms that (a) detect cues connoting the presence of infectious pathogens in the immediate environment, (b) trigger disease-relevant emotional and cognitive responses, and thus (c) facilitate behavioral avoidance of pathogen infection. However, the system responds to an overly general set of superficial cues, which can result in aversive responses to things (including people) that pose no actual threat of pathogen infection. In addition, the system is flexible, such that more strongly aversive responses occur under conditions in which perceivers are (or merely perceive themselves to be) more vulnerable to pathogen infection. Recent research reveals many provocative implications—for the experience of disgust, for extraversion and social interaction, for xenophobia and other prejudices, and for the origins of cultural differences.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.006
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.002

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 head0.250
GPT teacher head0.398
Teacher spread0.148 · 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 designTheoretical or conceptual
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

Citations1,127
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Directions in Psychological ScienceSame topicPsychology of Moral and Emotional JudgmentFrench-language works237,207