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Record W2006954447 · doi:10.1177/0272431614561262

Assessment and Implications of Coping Styles in Response to a Social Stressor Among Early Adolescents in China

2014· article· en· W2006954447 on OpenAlexaff
Mila Kingsbury, Junsheng Liu, Robert J. Coplan, Xinyin Chen, Dan Li

Bibliographic record

VenueThe Journal of Early Adolescence · 2014
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsCarleton UniversityUniversity of Ottawa
FundersCommercializations Promotion Agency for R and D Outcomes
KeywordsPsychologyCoping (psychology)Socioemotional selectivity theoryStressorDistancingDevelopmental psychologyClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

The aims of the present study were to (a) examine the factor structure of the Self-Report Coping Scale in a sample of Chinese early adolescents and (b) explore associations between coping and socioemotional functioning in this sample. Participants were N= 569 elementary school students (307 boys) in Grades 4 to 6. Participants completed a measure of coping in response to an argument with a friend. Students’ functioning across multiple domains was assessed using self, peer, and teacher reports. Results suggested a five-factor model of coping in Chinese early adolescents (problem solving, seeking social support, internalizing, externalizing, distancing). In support of predictions, internalizing and distancing coping were positively related to adjustment indices, whereas seeking social support and problem-solving coping were negatively related to outcomes. Results are discussed in terms of the important role of coping for adolescents’ adjustment across multiple domains and in relation to recent shifts in traditional Chinese cultural values.

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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.315
Teacher spread0.298 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

Explore more

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