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Record W2100466353 · doi:10.1111/cdev.12414

Shyness-Sensitivity and Social, School, and Psychological Adjustment in Urban Chinese Children: A Four-Wave Longitudinal Study

2015· article· en· W2100466353 on OpenAlexfundno aff
Fan Yang, Xinyin Chen, Li Wang

Bibliographic record

VenueChild Development · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsShynessPsychologyDevelopmental psychologyLongitudinal studyAnxiety

Abstract

fetched live from OpenAlex

This study examined reciprocal contributions between shyness-sensitivity and social, school, and psychological adjustment in urban Chinese children. Longitudinal data were collected once a year from Grade 3 to Grade 6 (ages 9-12 years) for 1,171 children from multiple sources. Shyness-sensitivity positively contributed to social, school, and psychological difficulties over time, with the most consistent effects on peer preference and loneliness. Social and school adjustment negatively contributed to the development of shyness-sensitivity. The initial levels of shyness-sensitivity and social and school adjustment moderated the growth of each other, mainly as a resource-potentiating factor. The results indicate the significance of shyness-sensitivity for adjustment and the role of adjustment in the development of shyness-sensitivity in today's urban Chinese society.

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 score0.099
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.102
GPT teacher head0.349
Teacher spread0.248 · 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

Citations52
Published2015
Admission routes1
Has abstractyes

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