A Cross-Cultural Comparative Study on Gender and Age-Cohort Differences in Multidimensional Social-Emotional Competence
Bibliographic record
Abstract
Background and Purpose: Gender is one of the most commonly studied predictors of social-emotional competence (SEC). Children and adolescents develop their SEC over time under the influence of gender-based cultural practices. While previous literature observed an overall gender difference in SEC, typically favoring girls, there are limitations to note. First, most studies have been conducted within a single cultural context, predominantly in Western societies, lacking a cross-cultural perspective. Second, previous research has largely focused on early childhood, with limited evidence available on gender differences in SEC varying throughout later developmental stages. Third, most studies have measured SEC as a composite variable, resulting in less nuanced findings on specific SEC domains. Also, little work has been done to confirm measurement invariance of SEC assessments before cross-group comparisons. To fill these gaps, this study examines how gender differences in SEC vary between North American (NA) and East Asian (EA) contexts, across middle childhood and adolescence, using a comparable measure of multidimensional SEC. Methods: Using the first wave of the OECD Survey of Social and Emotional Skills, this study analyzed student self-report data (N=25,206, 49.9% girls) collected from two age-cohort samples (52.5% age 10 and 47.5% age 15) from two EA countries–China (28.7%) and South Korea (25.1%)–and two NA countries–Canada (20.1%) and the USA (25.3%). This study used indicators of six SEC dimensions, previously studied to be equally relevant to both cultural samples: Emotional Control (6-item), Optimism (6-item), Open-mindedness (9-item), Task Performance (14-item), Prosociality (10-item), and Leadership (6-item). We first applied multidimensional polytomous item response theory modeling to detect any differential item functioning (DIF), then conducted linear regression analysis to examine the effects of gender and its interactions with culture and age-cohort on all six SEC dimensions. Results: Multigroup DIF analysis suggested that most items showed a good fit and no systematic differences across gender, cultural, and age-cohort subgroups, except for three items that were excluded from further analysis. Regarding the main effects of gender, boys had higher levels of Emotional Control, Optimism, and Open-mindedness, while girls had higher scores on Prosociality and Task Performance (all differences p<.001). Across cultural and age-cohort subgroups, gender differences in SEC were most pronounced among the 15-year-old EA sample: EA adolescent girls had significantly lower levels of Emotional Control, Open-mindedness, and Optimism than EA adolescent boys. These gender gaps were larger than those observed within younger EA children, NA children, and NA adolescents. Moreover, EA adolescent girls tended to have lower levels of Prosociality and Task Performance than EA adolescent boys (both differences p<.05), unlike other subgroups that favored girls. Conclusions and Implications: To our knowledge, this study is one of the first studies that examined how gender differences in multidimensional SEC manifested across different age-cohorts and cultural contexts, using the measurement tool found to be invariant across compared subgroups. This study calls for more research to further explain the observed phenomenon, while providing implications for practice to support healthy development of East Asian girls.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".