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Record W4416812663 · doi:10.1016/j.paid.2025.113587

Cross-cultural comparison of trait emotional intelligence: A study of Kazakh and Canadian children

2025· article· en· W4416812663 on OpenAlexaffabout
Yelnura N. Autalipova, Samantha M. van Rens, James D. A. Parker

Bibliographic record

VenuePersonality and Individual Differences · 2025
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsTrent University
Fundersnot available
KeywordsKazakhGeneralizability theoryTraitContext (archaeology)SocializationSample (material)PersonalityIntrapersonal communicationMalleability

Abstract

fetched live from OpenAlex

The concept of Trait emotional intelligence (TEI) continues to attract interest from researchers across various fields. While the literature emphasizes the importance of TEI throughout the lifespan, the question of whether the TEI construct generalizes across diverse cultural groups remains largely unaddressed in children. The present study examined the generalizability of the youth version of a widely used self-report measure of TEI (EQi:YV-Short) in Canadian and Kazakh children. Families in Kazakhstan offer a useful comparison to those in Canada, as this Asian culture traditionally emphasizes social interdependence- a very different emotion socialization context from the emphasis on independence in Canadian families. A sample of 200 children (92 boys and 108 girls) between the ages of 9 and 11 from Kazakhstan were compared to a sample of Canadian children ( n = 200). The mean age of the boys in both samples was 9.45 years (SD = 0.52) and for girls was 9.41 years (SD = 0.55). The Canadian sample was collected from children in central and eastern Ontario who identified themselves as “white/Caucasian” and were randomly matched with the Kazakh sample based on age and gender. The results show that Kazakh children scored higher on the intrapersonal dimension, while Canadian children scored higher on the interpersonal, stress management and total TEI dimensions. Findings are discussed with reference to cross-cultural generalizability and applications of TEI theory.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.117
GPT teacher head0.412
Teacher spread0.295 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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