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Record W2121547787 · doi:10.1177/0956797609359623

An Adaptive Cognitive Dissociation Between Willingness to Help Kin and Nonkin in Samoan <i>Fa’afafine</i>

2010· article· en· W2121547787 on OpenAlexafffund
Paul L. Vasey, Doug P. VanderLaan

Bibliographic record

VenuePsychological Science · 2010
Typearticle
Languageen
FieldPsychology
TopicCategorization, perception, and language
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSamoanPsychologyDissociation (chemistry)CognitionDevelopmental psychologySocial psychologyCognitive psychologyNeuroscienceChemistry

Abstract

fetched live from OpenAlex

Androphilia refers to sexual attraction and arousal to adult males, whereas gynephilia refers to sexual attraction and arousal to adult females. Previous research has demonstrated that Samoan male androphiles (known locally as fa'afafine) exhibit significantly higher altruistic tendencies toward nieces and nephews than do Samoan women and gynephilic men. The present study examined whether adaptive design features characterize the psychological mechanisms underlying fa'afafine's elevated avuncular tendencies. The association between altruistic tendencies toward nieces and nephews and altruistic tendencies toward nonkin children was significantly weaker among fa'afafine than among Samoan women and gynephilic men. We argue that this cognitive dissociation would allow fa'afafine to allocate resources to nieces and nephews in a more economical, efficient, reliable, and precise manner. These findings are consistent with the kin selection hypothesis, which suggests that androphilic males have been selected over evolutionary time to act as "helpers-in-the-nest," caring for nieces and nephews and thereby increasing their own indirect fitness.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.029
GPT teacher head0.399
Teacher spread0.371 · 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

Citations51
Published2010
Admission routes2
Has abstractyes

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