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Record W2034057577 · doi:10.1037/a0016949

Etiology and measurement of relational aggression: A multi-informant behavior genetic investigation.

2009· article· en· W2034057577 on OpenAlexafffund
Jennifer L. Tackett, Irwin D. Waldman, Benjamin B. Lahey

Bibliographic record

VenueJournal of Abnormal Psychology · 2009
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Toronto
FundersNational Institute of Mental HealthSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyAggressionDevelopmental psychologyContext (archaeology)Behavioural geneticsHuman factors and ergonomicsPoison controlVariance (accounting)Clinical psychology

Abstract

fetched live from OpenAlex

Although the study of relational aggression is gaining attention in the literature, little is known about the underlying causes of this behavior and the relative validity of various informants. These issues were addressed in a sample of 1,981 6- to 18-year-old twin pairs (36% female, 34% male, 30% opposite-sex). Relational aggression was assessed via maternal and self-report using a structured interview. Univariate models estimated genetic and environmental influences by informant and examined evidence for gender differences. A psychometric model combined data from both informants to estimate etiologic influences that were both common to the informants and informant specific. In both sexes, the latent variable reflecting the mother's and child's shared perception of the child's relational aggression was substantially influenced by both additive genetic (63%) and shared environmental (37%) influences, although this latent variable accounted for much greater variance in the maternal report (66%) than it did in the youth report (9%). In addition, informant-specific additive genetic and shared environmental influences were found only for the youth report, with all remaining variance in the mother's report attributed to nonshared environmental influences. Results are discussed in the context of measuring relational aggression and the importance of multiple informants.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.359
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.062
GPT teacher head0.326
Teacher spread0.264 · 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 teacher head, 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

Citations56
Published2009
Admission routes2
Has abstractyes

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