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Record W2745832691 · doi:10.1111/cdep.12248

Understanding Processes of Peer Clique Influence in Late Childhood and Early Adolescence

2017· article· en· W2745832691 on OpenAlexaff
Wendy E. Ellis, Lynne Zarbatany

Bibliographic record

VenueChild Development Perspectives · 2017
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsWestern University
Fundersnot available
KeywordsCliqueContext (archaeology)PsychologySocializationSocial psychologyDevelopmental psychologyBiology

Abstract

fetched live from OpenAlex

Abstract Cliques, or groups of peers who interact frequently, are a key social context during childhood and adolescence, providing safety and preferential access to resources. Membership in cliques influences behavior and adjustment, but little is known about the processes by which these influences occur. In this article, we identify putative self and clique socialization processes that may account for greater similarity among clique members over time. Greater adherence to clique norms occurs when members are uncertain about their membership or have limited access to valued clique resources, and when cliques control more resources and are more cohesive. We speculate about other clique influence processes, including those that support children's attempts to distinguish themselves from cliquemates. Understanding clique influence processes can inform efforts to help children and youth resist the negative influences of cliques while protecting the benefits of membership.

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 score0.021
Threshold uncertainty score0.042

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 communication0.0020.002
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 head0.035
GPT teacher head0.298
Teacher spread0.263 · 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

Citations85
Published2017
Admission routes1
Has abstractyes

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