Associations of Intellectual Ability with Emotional Intelligence, Academic Achievement and Aggression of Adolescents
Bibliographic record
Abstract
Purpose: The current study examined the relationship of intellectual ability with emotional intelligence, academic achievement, and aggression of adolescents.Methods: Correlational design was utilized to study the relationship between these variables. Adolescent students (N=500, 50% boys & 50% girls, with the mean age of 15.01 years & SD of 1.11) were approached from different private schools and colleges of Karachi. To measure their intellectual ability, emotional intelligence, and aggression, Draw-A-Person Intellectual Ability Test for children, adolescents, and adults (DAP: IQ), Wong and Law Emotional Intelligence Scale (WLEIS), and Aggression Questionnaire-Short Form (AQ-12) were administered. Their academic achievement was assessed through their percentage of most recent examination. Pearson product moment correlation coefficient was utilized to analyse the results.Results: Intellectual ability was significantly positively related with emotional intelligence and its domains i.e. Self-Emotional Appraisal, Others’ Emotional Appraisal, Use of Emotions, and Regulation of Emotions (p
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".