New Reliability and Validity Evidence of the Emotional Intelligence Scale
Bibliographic record
Abstract
Emotional Intelligence Scale (EIS) is a popular EI measure. Yet, it has been criticized for an unclear factor structure, and its psychometric properties were mainly examined in the Western context. This study was to evaluate its psychometric properties based on 1,724 Hong Kong undergraduate students, including its (a) factor structure, (b) internal consistency, and (c) criterion validity. We compared different factor structures reported in the literature. The confirmatory factor analysis (CFA) results supported a six-factor structure, which is tallied with Salovey and Mayer’s EI conceptualization. A multigroup CFA also rendered the structure as gender invariant. The scale was internally consistent with high McDonald’s omega coefficients. Significant association between EI and grade point average (GPA) was revealed in the faculties with people-oriented studies. Furthermore, EI was correlated with social, cognitive, and self-growth outcomes and satisfaction of university experience. The study contributes to clarify the factor structure and provides new reliability and validity evidence of the EIS in the Eastern context.
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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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".