Identifying subtypes among offenders with antisocial personality disorder: A cluster-analytic study.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The question of whether antisocial personality disorder (ASPD) and psychopathy are largely similar or fundamentally different constructs remains unresolved. In the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994), many of the personality features of psychopathy are cast as associated features of ASPD, although the DSM-IV offers no guidance as to how, or the extent to which, these features relate to ASPD. In a sample of 691 offenders who met DSM-IV criteria for ASPD, we used model-based clustering to identify subgroups of individuals with relatively homogeneous profiles on measures of associated features (psychopathic personality traits) and other constructs with potential etiological significance for subtypes of ASPD. Two emergent groups displayed profiles that conformed broadly to theoretical descriptions of primary psychopathy and Karpman's (1941) variant of secondary psychopathy. As expected, a third group (nonpsychopathic ASPD) lacked substantial associated features. A fourth group exhibited elevated psychopathic features as well as a highly fearful temperament, a profile not clearly predicted by extant models. Planned comparisons revealed theoretically informative differences between primary and secondary groups in multiple domains, including self-report measures, passive avoidance learning, clinical ratings, and official records. Our results inform ongoing debates about the overlap between psychopathy and ASPD and raise questions about the wisdom of placing most individuals who habitually violate social norms and laws into a single diagnostic category.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it