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Record W2098722771 · doi:10.1098/rsbl.2007.0365

Genetic and environmental contributions to prosocial behaviour in 2- to 9-year-old South Korean twins

2007· article· en· W2098722771 on OpenAlexaff
Yoon‐Mi Hur, J. Philippe Rushton

Bibliographic record

VenueBiology Letters · 2007
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsWestern University
Fundersnot available
KeywordsProsocial behaviorBiologyTwin studyDizygotic twinsDevelopmental psychologyDemographyGene–environment interactionPopulationStructural equation modelingPsychologyHeritabilityGeneticsStatistics

Abstract

fetched live from OpenAlex

Although over 50 twin and adoption studies have been performed on the genetic architecture of antisocial behaviour, far fewer studies have investigated prosocial behaviour, and none have done so on a non-western population. The present study examined mothers' ratings of prosocial behaviour in 514 pairs of 2- to 9-year-old South Korean monozygotic and dizygotic twins. Correlational analyses showed a tendency of increasing genetic effects and decreasing shared environmental effects with age although shared family environment effects and the moderating effects of age did not attain statistical significance in model-fitting analyses. The best-fitting model indicated that 55% (95% CI: 45-64%) of the variance in the 2- to 9-year-olds' prosocial behaviour was due to genetic factors and 45% (95% CI: 36-55%) was due to non-shared environmental factors. It is concluded that genetic and environmental influences on prosocial behaviour in young South Koreans are mostly similar to those in western samples.

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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.289
Teacher spread0.274 · 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

Citations68
Published2007
Admission routes1
Has abstractyes

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