Nipping psychopathy in the bud: an examination of the convergent, predictive, and theoretical utility of the PCL‐YV among adolescent girls
Bibliographic record
Abstract
Over the last decade rates of violence among adolescent girls have increased. Within high-risk contexts, urgent calls for assessment options have resulted in the extension of adult and male-based instruments to adolescent females in spite of the absence of strong empirical support. The current study evaluates the downward extension of psychopathy within a population of female juvenile offenders (N=125). The convergent and predictive validity of the Psychopathy Checklist-Youth Version (PCL-YV) were evaluated within a structural equation modeling (SEM) framework. Results indicated that while a specific component of psychopathy, deficient affective experience, was related to aggression, the effect was negated once victimization experiences were entered into the models. In addition, PCL-YV scores were not predictive of future offending, while victimization experiences significantly increased the odds of re-offending. Implications for research, policy, and clinical practice are discussed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".