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Examining Genetic and Environmental Effects on Social Aggression: A Study of 6-Year-Old Twins

2005· article· en· W2154280054 on OpenAlexaff
Mara Brendgen, Ginette Dionne, Alain Girard, Michel Boivin, Frank Vitaro, Daniel Pérusse

Bibliographic record

VenueChild Development · 2005
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversité de MontréalUniversité LavalUniversité du Québec à Montréal
Fundersnot available
KeywordsAggressionPsychologyDevelopmental psychologyBivariate analysisBehavioural geneticsSocial environmentCorrelationTwin studyHeritabilityGeneticsBiology

Abstract

fetched live from OpenAlex

Using a genetic design of 234 six-year-old twins, this study examined (a) the contribution of genes and environment to social versus physical aggression, and (b) whether the correlation between social and physical aggression can be explained by similar genetic or environmental factors or by a directional link between the phenotypes. For social aggression, substantial (shared and unique) environmental effects but only weak genetic effects were found. For physical aggression, significant effects of genes and unique environment were found. Bivariate modeling suggests that social and physical aggression share most of their underlying genes but only very few overlapping environmental factors. The correlation between the two phenotypes can also be explained by a directional effect from physical to social aggression.

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)0.007
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.019
GPT teacher head0.262
Teacher spread0.244 · 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

Citations120
Published2005
Admission routes1
Has abstractyes

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