Assessment and Implications of Social Avoidance in Chinese Early Adolescents
Bibliographic record
Abstract
The goals of the present study were to (a) develop and validate a new self-report measure of social avoidance for use among early adolescents in mainland China and (b) explore the links between subtypes of social withdrawal (i.e., shyness, unsociability, and social avoidance) and indices of socio-emotional difficulties in this cultural context. Participants were 663 early adolescents (350 boys, 313 girls) attending elementary schools ([Formula: see text] = 10.25 years) and middle schools ([Formula: see text] = 12.53 years) in Shanghai, People’s Republic of China. Measures of social withdrawal subtypes and adjustment were collected using multi-source assessments, including self-reports, peer nominations, and teacher ratings. The results provided evidence in support of the reliability and validity of the new scale of self-reported social avoidance. Shyness, unsociability, and social avoidance were also all uniquely associated with emotion dysregulation and self-reported internalizing problems. However, only social avoidance was uniquely associated with teacher-rated emotion symptoms and peer problems (as rated by both peers and teachers). Results are discussed in terms of the reasons why social avoidance may have particularly negative implications for early adolescents in China.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".