Validity Evidence based on Internal Structure of Scores of the Emotional Quotient-Inventory: Youth Version Short (EQ-i: YV-S) in a Spanish Sample
Bibliographic record
Abstract
The purpose of this study was to analyze the reliability and validity evidence of scores on the Spanish version of EQ-i: YV-S in Spanish adolescents. The total sample was comprised of 508 participants from Grades 7 to 12, 241 males (47.4%) and 267 females (52.6%), each of whom completed the questionnaires on two separate occasions. Three [intrapersonal (α = .83, CR = .86, and McDonald Omega = .86), stress management (α = .83, CR = .86, and McDonald Omega = .85) and adaptability (α = .82, CR = .85, and McDonald Omega = .85)] of the four scales had acceptable internal consistency. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used with FACTOR and EQS version 6.1 software to examine validity evidence based on internal structure drawn from the scores on the EQ-i: YV-S, supporting the multidimensionality of the questionnaire. Three models were tested; the best fit to the data was the hierarchical model (S-Bχ2 / df = 2.11, CFI = .93 and RMSEA = .047), which hypothesized that the four specific factors (interpersonal, intrapersonal, stress management, and adaptability) were explained with a second-order factor, Emotional-Social-Intelligence (ESI). Finally, significant positive correlations were found between general self-concept and EQ-i: YV-S [interpersonal (r = .153, p < .001), intrapersonal (r = .235, p < .001), stress management (r = .145, p < .001), adaptability (r = .311, p < .001) and ESI (r = .360, p < .001)]; ESI showed significant direct power prediction of the general self-concept (.52) as demonstrated through structural equation modeling.
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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 | 0.018 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".