Psychopathy, Alexithymia and Emotional Intelligence in a Forensic Hospital
Bibliographic record
Abstract
In this study, we compared 20 criminal psychopaths and 19 nonpsychopaths identified with the PCL-R ( Hare, 2003 ). All participants were adult males confined in a Belgian security hospital. The psychopath group and the control group were equivalent for age, IQ, and social desirability score ( Crowne & Marlowe, 1960 ). First, the two groups completed the Toronto Alexithymia Scale (TAS; Bagby et al. 1994a, b). This self report measure includes three factors: the identification of emotion states; the expression of emotion states to others, and operative thinking. Secondly, each participant completed the TEIque (Emotional Intelligence Questionnaire; Petrides & Furnam, 2003). The full version of this self-report includes 15 scales and 4 main factors. For this study, we selected six scales that were a priori supposed to be strongly involved in emotion processing: “emotional regulation” of self, “emotion management” of others, “relational aptitudes,” “emotional expression,” “emotional perception,” and “stress management.” First, psychopaths presented a lower total score on the TAS. Among the facets of psychopathy, the deficient affective component was the most negatively correlated to the TAS total score. These results disconfirmed the classical hypothesis of a perceived emotion deficit among psychopaths. Concerning the TEIque, psychopaths presented a higher score on both the “emotional perception” and “emotional regulation” scales. Again, among the facets of psychopathy, the deficient affective component was the most negatively correlated to the TEIque total score. The TAS and the TEIque total scores were negatively related ( r = .61). The overall results are discussed in light of the recent literature on affects characteristics of psychopaths ( Book, Quinsey, & Langford, 2007 ) and on their potential lifetime strategy ( Harris & Rice, 2006 ).
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".