Association between Alexithymia, Neuroticism, and Social Desirability Scores among Italian Graduate Students
Bibliographic record
Abstract
An inverse correlation between social desirability and alexithymia has been observed in undergraduate students in Japan and Australia. It is not clear how this association is influenced by the personality dimension of neuroticism. This study examined the association of scores on social desirability with those on alexithymia controlled for neuroticism, in a sample of 111 Italian graduate students, with age range of 24 to 58 years. Students completed the Eysenck Personality Questionnaire (short form) and the Toronto Alexithymia Scale-20 (TAS-20). Social desirability scores inversely correlated with TAS-20 total scores, neuroticism scores, and the TAS-20 subscale, Difficulty identifying feelings. Neuroticism directly correlated with TAS-20 total score, Difficulty identifying feelings, and Difficulty describing feelings. Students with higher alexithymia and neuroticism scores seem to present themselves in less socially desirable ways. The correlation of social desirability with alexithymia was moderated by higher neuroticism scores.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".