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Record W2946925214 · doi:10.1177/1474704919849924

An Examination of the Westermarck Hypothesis and the Role of Disgust in Incest Avoidance Among Fathers

2019· article· en· W2946925214 on OpenAlexafffundabout
Lesleigh E. Pullman, Kelly M. Babchishin, Michael C. Seto

Bibliographic record

VenueEvolutionary Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsRoyal Ottawa Mental Health CentrePublic Safety CanadaUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDisgustPsychologyKinshipDevelopmental psychologyPerspective (graphical)Mechanism (biology)Social psychology

Abstract

fetched live from OpenAlex

From an evolutionary perspective, incestuous behavior is puzzling. The goal of this study was to assess the tenability of the Westermarck hypothesis (1891, 1921)-that people who live in close physical proximity with one another during childhood will develop a sexual indifference or aversion toward one another-and the mediating role of disgust as an incest avoidance mechanism in father-daughter relationships. A sample of fathers with daughters ( N = 632) from Canada and the United States were recruited by Qualtrics-a survey platform and project management company-to complete an online survey. The results from this study did not support the viability of the Westermarck hypothesis as a mechanism that facilitates incest avoidance for fathers. Physical proximity was not associated with incest propensity or disgust toward incest. Less disgust toward incest, however, was found to be associated with more incest propensity. These results indicate that physical proximity may not be a reliable kinship cue used by fathers to inform incest avoidance, but that disgust toward incest may still be a proximate mechanism that facilitates incest avoidance among fathers using kinship cues other than physical proximity.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.015
GPT teacher head0.286
Teacher spread0.272 · 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

Citations7
Published2019
Admission routes3
Has abstractyes

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