Youth with psychopathy features are not a discrete class: a taxometric analysis
Bibliographic record
Abstract
BACKGROUND: Recently, researchers have sought to measure psychopathy-like features among youth in hopes of identifying children who may be progressing toward a particularly destructive form of adult pathology. However, it remains unclear whether psychopathy-like personality features among youth are best conceptualized as dimensional (distributed along a continuum) or taxonic (such that youth with psychopathic personality characteristics are qualitatively distinct from non-psychopathic youth). METHODS: This study applied taxometric analyses (MAMBAC, MAXEIG, and L-Mode) to scores from two primary measures of youth psychopathy features: the Psychopathy Checklist: Youth Version (N = 757) and the self-report Antisocial Process Screening Device (N = 489) among delinquent boys. RESULTS: All analyses supported a dimensional structure, indicating that psychopathy features among youth are best understood as existing along a continuum. CONCLUSIONS: Although youth clearly vary in the degree to which they manifest psychopathy-like personality traits, there is no natural, discrete class of young 'psychopaths.' This finding has implications for developmental theory, treatment, assessment strategies, research, and clinical/forensic practice.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".