Relationship Between Measures of Emotional Intelligence and Alexithymia Among Moroccan Students
Bibliographic record
Abstract
The main purpose of the present study was to examine the relationship between emotional intelligence (EI) and alexithymia, using the Bar-on Emotional Quotient Inventory (EQ-I; BarOn, 1997) and the Wong and Law Emotional Intelligence Scale (WLEIS; Wong & Law, 2002) to measure EI and The Toronto Alexithymia Scale (TAS-20;Bagby et al., 1994) to measure alexithymia.A second purpose was to examine the relationship between the two measures of EI.The study sample consisted of fifty-two participants (28 girls and 24 boys), with a mean age of 151.71 months, belonging to the Fez-Meknes region, Morocco.It was found that there was a negative correlation between score on the Bar-on EQ-i and score on the TAS-20 as well as a positive correlation between the total scores on the two measures of EI. Results were discussed in the context of different theoretical bases for the two measures of EI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".