MétaCan
Menu
Back to cohort
Record W2109927533 · doi:10.1177/009385480102800407

A Factor Analysis of Traits Related to Individual Differences in Antisocial Behavior

2001· article· en· W2109927533 on OpenAlexaff
Vernon L. Quinsey, Angela S. Book, Martin L. Lalumière

Bibliographic record

VenueCriminal Justice and Behavior · 2001
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsCentre for Addiction and Mental HealthQueen's University
Fundersnot available
KeywordsPsychologyAggressionDevelopmental psychologyPsychopathyPoison controlExploratory factor analysisMatingHuman factors and ergonomicsInjury preventionSocial psychologyClinical psychologyPsychometricsPersonalityMedical emergencyEcologyMedicine

Abstract

fetched live from OpenAlex

Male undergraduates and men from the local community completed questionnaires dealing with antisocial behavior, aggression, mating effort, and self-esteem. An exploratory maximum likelihood factor analysis revealed three factors, labeled Aggressiveness, Mating Success, and Antisociality. No clear mating effort factor emerged. Number of sexual partners and Preference for Partner Variety loaded on Mating Success, but age at first intercourse loaded on Antisociality. The only significant correlation among the factors was between Aggressiveness and Antisociality. Variables from each of the 3 factors discriminated between individuals scoring at the extreme ends of the Childhood and Adolescence Taxon Scale–Self Report, a measure containing items previously shown to identify a discrete class of antisocial offenders.

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)0.003
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.104
GPT teacher head0.389
Teacher spread0.285 · 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

Citations17
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCriminal Justice and BehaviorSame topicEvolutionary Psychology and Human BehaviorFrench-language works237,207