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Record W4412979671 · doi:10.1016/j.sel.2025.100137

Exploring gender differences in multidimensional social-emotional competence from developmental and cross-cultural perspectives

2025· article· en· W4412979671 on OpenAlexaboutno aff
Juyeon Lee, Cheng-ling Wang, Ingrid D. Lui

Bibliographic record

VenueSocial and Emotional Learning Research Practice and Policy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
FundersUniversity of Hong Kong
KeywordsPsychologyDevelopmental psychologyCross-culturalSocial competenceCompetence (human resources)Social emotional learningSocial psychologySociologySocial changeAnthropologyPolitical science

Abstract

fetched live from OpenAlex

Children and adolescents develop social-emotional competence (SEC) over time under the influence of gender-based cultural practices, though evidence is limited on how patterns of gender differences in multiple dimensions of SEC vary across developmental stages and cultural contexts. The current study first examined measurement invariance of an international SEC assessment, the OECD Survey of Social and Emotional Skills, then compared patterns of gender differences in multidimensional SEC across age cohorts and cultural regions. Using self-reported data collected from China, South Korea, Canada, and the United States (N=25,454), our analysis identified 48 items measuring six domains of SEC that were invariant across gender, age cohorts, and cultural regions. Interaction analysis with bias-adjusted estimates suggested that each SEC domain showed different patterns of gender difference depending on age cohorts and cultural regions: (1) boys had higher Emotional Control and Optimism, particularly in age 15 cohort, (2) girls had higher Task Performance and Prosociality, particularly in the North American sample, and (3) boys had higher Open-mindedness and lower Leadership in East Asia, but girls had higher Open-mindedness and lower Leadership in North America. We discuss these findings, calling for more research to further explain gender differences in SEC from developmental and cross-cultural perspectives.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.279
GPT teacher head0.484
Teacher spread0.205 · 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 teacher head, not a consensus.

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

Citations2
Published2025
Admission routes1
Has abstractyes

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