A Behavioral-Genetic Study of Alexithymia and its Relationships with Trait Emotional Intelligence
Bibliographic record
Abstract
The present study is the first to examine relationships between alexithymia and trait emotional intelligence (trait El or trait emotional self-efficacy) at the phenotypic, genetic, and environmental levels. The study was also conducted to resolve inconsistencies in previous twin studies that have provided estimates of the extent to which genetic and environmental factors contribute to individual differences in alexithymia. Participants were 216 monozygotic and 45 dizygotic same-sex twin pairs who completed the Toronto Alexithymia Scale-20. In a pilot study, a sub-sample of 118 MZ and 27 DZ pairs also completed the Trait Emotional Intelligence Questionnaire. Results demonstrated that a combination of genetic and non-shared environmental influences contribute to individual differences in alexithymia. As expected, alexithymia and trait El were negatively correlated at the phenotypic level. Bivariate behavioral genetic analyses showed that that all but one of these correlations was primarily attributable to correlated genetic factors and secondarily to correlated non-shared environmental factors.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".