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Record W2073626732 · doi:10.1037/0012-1649.44.4.1184

Social functioning and adjustment in Canadian-born children with Chinese and European backgrounds.

2008· article· en· W2073626732 on OpenAlexafffundabout
Xinyin Chen, Hennis Chi‐Hang Tse

Bibliographic record

VenueDevelopmental Psychology · 2008
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of CanadaWilliam T. Grant Foundation
KeywordsShynessPsychologyDevelopmental psychologyFriendshipAggressionSociometryEthnic groupPeer relationsPeer victimizationContext (archaeology)Social environmentSocial acceptancePeer acceptanceSociometric statusPeer groupPoison controlHuman factors and ergonomicsSocial psychologyAnxietyMedicine

Abstract

fetched live from OpenAlex

The purpose of the study was to examine social functioning and adjustment in peer context in Chinese Canadian and European Canadian children. A sample of elementary school children participated in the study. Data on social functioning, peer acceptance and rejection, and victimization were collected from peer assessments and sociometric nominations. The results indicated that Chinese Canadian children were viewed by peers as less aggressive-disruptive than European Canadian children. Chinese Canadian girls, but not boys, were more shy-sensitive than their European Canadian counterparts. Sociability was associated with peer acceptance, whereas aggression was associated with peer rejection and victimization. Shyness was associated with peer relationship difficulties more evidently in European Canadian children than in Chinese Canadian children. These results indicate the relevance of ethnic background to children's peer social experiences.

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)0.001
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 score0.041
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.275
Teacher spread0.254 · 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

Citations60
Published2008
Admission routes3
Has abstractyes

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