Variants of psychopathy in adult male offenders: A latent profile analysis.
Bibliographic record
Abstract
As measured with the Psychopathy Checklist-Revised (PCL-R), psychopathy is a dimensional construct underpinned by 4 correlated factors: Interpersonal, Affective, Lifestyle, and Antisocial. Theorists and clinicians (e.g., Karpman and Arieti) have posited 2 variants of "primary" or "true" psychopathy, both distinct from so-called "secondary" or "pseudopsychopathy." We used latent profile analysis to determine if homogeneous classes exist within a sample of 1,451 male offenders with high PCL-R scores (≥ 27). The 4 PCL-R factors were the dependent variables for clustering. A solution with 3 latent classes showed a better fit to the data than did a unitary model without latent classes. Tentative labels for the latent classes are Manipulative (Latent Class 1 [LC1]), Aggressive (Latent Class 2 [LC2]), and Sociopathic (Latent Class 3 [LC3]). The latter class represented an antisocial group that lacked the emotional detachment observed in the other 2 groups. We propose that LC1 and LC2 reflect phenotypic variations on a theme of the traditional construct of psychopathy, and that LC3 is consistent with conceptions of antisocial personality disorder and sociopathy. Replication and external classification with an independent data set of 497 adult male offenders again yielded clearly separable clusters, as well as meaningful differences or trends among latent classes on education, intelligence, symptoms of antisocial personality disorder, and self-reported psychopathic traits and negative affect. The conceptualization of psychopathy in terms of manipulative and aggressive variants is consistent with clinical theory and is empirically grounded.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".