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Record W2953489771 · doi:10.1111/cdev.13269

A Test of the Bistrategic Control Hypothesis of Adolescent Popularity

2019· article· en· W2953489771 on OpenAlexafffund
Amy C. Hartl, Brett Laursen, Stéphane Cantin, Frank Vitaro

Bibliographic record

VenueChild Development · 2019
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of CanadaNational Science Foundation
KeywordsPopularityProsocial behaviorPsychologyAggressionDevelopmental psychologyPeer groupSocial psychology

Abstract

fetched live from OpenAlex

Abstract Resource Control Theory (Hawley, 1999) posits a group of bistrategic popular youth who attain status through coercive strategies while mitigating fallout via prosociality. This study identifies and distinguishes this bistrategic popular group from other popularity types, tracing the adjustment correlates of each. Adolescent participants (288 girls, 280 boys; Mage = 12.50 years) completed peer nominations in the Fall and Spring of the seventh and eighth grades. Longitudinal latent profile analyses classified adolescents into groups based on physical and relational aggression, prosocial behavior, and popularity. Distinct bistrategic, aggressive, and prosocial popularity types emerged. Bistrategic popular adolescents had the highest popularity and above average aggression and prosocial behavior; they were viewed by peers as disruptive and angry but were otherwise well-adjusted.

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)0.003
metaresearch head score (Gemma)0.015
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 score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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

Citations59
Published2019
Admission routes2
Has abstractyes

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