The Empathy Quotient: A cross-cultural comparison of the Italian version
Bibliographic record
Abstract
INTRODUCTION: The Empathy Quotient (EQ) is a self-report questionnaire that was developed to measure the cognitive, affective, and behavioural aspects of empathy. We evaluated its cross-cultural validity in an Italian sample. METHODS: A sample of 18- to 30-year-old undergraduate students of both sexes (N=256, males=118) were invited to fill in the Italian version of the EQ, as well as other measures of emotional competence and psychological distress. Results. The EQ had an excellent reliability (Cronbach's alpha=.79; test-retest at 1 month: Pearson's r=.85), and was normally distributed. Females scored higher than males, and more males (n=14, 11.9%) than females (n=4, 2.9%) scored lower than 30, the cutoff score that best differentiates autism spectrum conditions from controls. EQ was negatively related to the Toronto Alexithymia Scale (TAS) and positively related to the Marlowe-Crowne Social Desirability Scale (SDS). Principal component analysis retrieved the three-factor structure of the EQ. Lower emotional reactivity correlated with higher scores in measures of risk in both the schizophrenia-like (Peters et al. Delusions Inventory) and the bipolar (Hypomanic Personality Scale) spectra. CONCLUSIONS: The Italian version of the EQ has good validity, with an acceptable replication of the original three-factor solution, yielding three subscales with high internal and test-retest reliability.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".