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Record W3091332835 · doi:10.1177/0272431620961457

Unsociability, Peer Rejection, and Loneliness in Chinese Early Adolescents: Testing a Cross-Lagged Model

2020· article· en· W3091332835 on OpenAlexaff
Bowen Xiao, Amanda Bullock, Junsheng Liu, Robert J. Coplan

Bibliographic record

VenueThe Journal of Early Adolescence · 2020
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsCarleton University
FundersHumanities and Social Science Fund of Ministry of Education of ChinaChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsLonelinessPsychologyChinaPeer acceptanceDevelopmental psychologyClinical psychologyPeer groupSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

In this study, we explored the longitudinal linkages among Chinese early adolescents’ unsociability, peer rejection, and loneliness. Participants were N = 445 primary school students in Shanghai, P.R. China followed over 3 years from Grades 6 and 7 to Grades 8 and 9. Measures of adolescents’ unsociability, peer rejection, and loneliness were obtained each year from a combination of self-reports and peer nominations. Among the results, (1) compared with the unidirectional and bidirectional models, the cross-lagged model was deemed the best fit for the data; (2) adolescent unsociability contributed to later increases in loneliness via a pathway through peer rejection; and (3) loneliness directly contributed to later increases in unsociability. Results are discussed in terms of the implications of unsociability for Chinese adolescents’ experience of peer rejection and subsequent loneliness.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.324
Teacher spread0.285 · 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

Citations35
Published2020
Admission routes1
Has abstractyes

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