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Record W2131202375 · doi:10.1080/00221325.2013.799060

Mixed-Grade Rejection and Its Association With Overt Aggression, Relational Aggression, Anxious-Withdrawal, and Psychological Maladjustment

2014· article· en· W2131202375 on OpenAlexfundno aff
Julie C. Bowker, Rebecca G. Etkin

Bibliographic record

VenueThe Journal of Genetic Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
FundersMcGill University
KeywordsAggressionLonelinessPsychologyAssociation (psychology)Developmental psychologyClinical psychologyAnxietyNominationSocial psychologyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

The authors examined the associations between mixed-grade rejection (rejection by peers in a different school grade), anxious-withdrawal, aggression, and psychological adjustment in a middle school setting. Participants were 181 seventh-grade and 180 eighth-grade students (M age = 13.20 years, SD = 0.68 years) who completed peer nomination and self-report measures in their classes. Analyses indicated that in general, same- and mixed-grade rejection were related to overt and relational aggression, but neither type was related to anxious-withdrawal. Mixed-grade rejection was associated uniquely and negatively with self-esteem for seventh-grade boys, while increasing the loneliness associated with anxious-withdrawal. The results suggest that school-wide models of peer relations may be promising for understanding the ways in which different peer contexts contribute to adjustment in middle school settings.

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)0.004
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
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 head0.027
GPT teacher head0.290
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

Citations8
Published2014
Admission routes1
Has abstractyes

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