Critical Issues in the Assessment of Adolescent Psychopathy: An Illustration Using Two Case Studies
Bibliographic record
Abstract
To explore critical issues in the conceptualization and assessment of adolescent psychopathy, we report on the use of the Youth Version of the Hare Psychopathy Checklist-Revised (PCL:YV; Forth, Kosson, & Hare, 2003) and the Comprehensive Assessment of Psychopathic Personality-Institutional Rating Scale (CAPP-IRS; Cooke, Hart, Logan, & Michie, 2004)—both derived from procedures for assessing psychopathy in adulthood—to assess two incarcerated youth identified by clinical staff as demonstrating features of adolescent psychopathy. Consistent with the views of clinical staff, the PCL:YV and CAPP-IRS ratings indicated the presence of serious psychopathy-related personality disturbance in both cases. The PCL:YV and CAPP-IRS also revealed between-case differences in the specific nature or features of personality disturbance present, despite similarities in the overall level or severity of personality disturbance. Raters found it was relatively easy to administer the PCL:YV and the CAPP-IRS, although they identified some challenges, particularly with respect to the assessment of disturbance of self functions. Relative to the PCL:YV, which may be considered the gold standard for assessing the PCL:YV, the CAPP-IRS had some strengths and limitations. We discuss these findings in light of the literature on assessment of adolescent psychopathy and consider their implications for future research.
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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 | 0.032 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| 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".