Cross-Cultural Analysis of Social Competence and Behavior Problems in Preschoolers
Bibliographic record
Abstract
A multi-national study using the Social Competence and Behavior Evaluation Inventory (SCBE-30) was conducted to investigate preschool children's social and emotional development across cultures. A total of 4,640 children from eight participating countries, including Austria, Brazil, Canada, China, Italy, Japan, Russia, and the United States were evaluated by their preschool teachers. The main objective of the study was to validate the SCBE-30 in each country and build a cross-cultural data set for the investigation of universals, as well as cultural differences, in the development of preschool children's social competence and the frequency and type of their behavioral problems. Results provide a clear case for the structural equivalence of the SCBE-30 across all samples, for universals in the structure of early social behavior, and possibly some differences that may be attributed to culture. The pattern of gender differences found in North American samples was found to generalize across cultural contexts as preschool boys were universally reported to be significantly more aggressive and viewed as less socially competent than girls. Age differences were also found in all eight samples reflecting increasing competence in older children, however age trends in the prevalence of behavior problems were culture specific.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".