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Record W2200669250 · doi:10.1177/1474704915613909

Adolescent Bullying, Dating, and Mating

2015· article· en· W2200669250 on OpenAlexaff
Anthony A. Volk, Andrew V. Dane, Zopito A. Marini, Tracy Vaillancourt

Bibliographic record

VenueEvolutionary Psychology · 2015
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversity of OttawaBrock University
Fundersnot available
KeywordsPsychologyMatingEvolutionary psychologyPhysical attractivenessAttractivenessDevelopmental psychologyDating violenceSocial psychologyPoison controlHuman factors and ergonomicsEcologyDomestic violenceBiology

Abstract

fetched live from OpenAlex

Traditionally believed to be the result of maladaptive development, bullying perpetration is increasingly being viewed as a potentially adaptive behavior. We were interested in determining whether adolescents who bully others enjoy a key evolutionary benefit: increased dating and mating (sexual) opportunities. This hypothesis was tested in two independent samples consisting of 334 adolescents and 144 university students. The data partly supported our prediction that bullying, but not victimization, would predict dating behavior. The data for sexual behavior more clearly supported our hypothesis that bullying behavior predicts an increase in sexual opportunities even when accounting for age, sex, and self-reports of attractiveness, likeability, and peer victimization. These results are generally congruent with the hypothesis that bullying perpetration is, at least in part, an evolutionary adaptive behavior.

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)0.005
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.053
GPT teacher head0.348
Teacher spread0.296 · 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

Citations137
Published2015
Admission routes1
Has abstractyes

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