The Relationship Between Brain-Behavior Systems, Dark Personality Traits, Alexithymia, and Theory of Mind Deficits in Sexual Offenders
Bibliographic record
Abstract
The aim of the current research is to examine the relationship between brain-behavior systems, dark personality dimensions, and Alexithymia with theory of mind deficits in sexual offenders. For this purpose, 80 inmates from the central prison of Bojnurd were selected using purposive sampling. The variables were measured using the Gray-Wilson Personality Questionnaire (GWPQ), the Dirty Dozen scale of dark personality traits, the 20-item Toronto Alexithymia Scale (TAS-20), and the Reading the Mind in the Eyes Test (RMET). Data were analyzed using Pearson correlation coefficients and multiple regression analysis. The results showed a significant positive correlation between the fight system and theory of mind deficits; and significant negative correlations between the flight and freeze systems, all aspects of dark personality dimensions, difficulty in identifying and describing feelings, and overall Alexithymia with theory of mind deficits. The regression analysis findings suggest that the fight/flight/freeze systems, dark personality traits, and Alexithymia play predictive roles in mind-reading abilities.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".