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Children in Peer Groups

2015· other· en· W1670202110 on OpenAlexaff
Kenneth H. Rubin, William M. Bukowski, Julie C. Bowker

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsConcordia University
Fundersnot available
KeywordsFriendshipPsychologyPopularityAggressionDevelopmental psychologySet (abstract data type)Peer groupSocial psychologyPerceptionAnxiety

Abstract

fetched live from OpenAlex

Abstract The features, processes, and effects of children's experiences with their peers exist on multiple levels of social complexity and intersect with many other developmental domains. Peers are implicated in several theoretical accounts of multiple development domains, including the models proposed by Piaget, Sullivan, the social learning theorists, Vygotsky, ethologists, and the symbolic interactionists. The extensive data base on peer relations points to the diverse set of positive and negative experiences that children and adolescents can have with their peers and to the breadth of the processes that account for peer effects on multiple forms of outcome including behavior (e.g., aggression), affect (e.g., depression, anxiety), school performance, self‐perceptions, moral perspectives, and physical and mental health. The chapter reviews the effects of several experiences including acceptance and rejection, exclusion, friendship, victimization, popularity, and experiences within groups. Specific attention is devoted to variation in processes and effects as a function of culture and gender.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.001

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 head0.020
GPT teacher head0.288
Teacher spread0.268 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations335
Published2015
Admission routes1
Has abstractyes

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