Using latent variable- and person-centered approaches to examine the role of psychopathic traits in sex offenders.
Why this work is in the frame
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Bibliographic record
Abstract
The current study employed both latent variable- and person-centered approaches to examine psychopathic traits in a large sample of sex offenders (N = 958). The offenders, who had committed a range of sexual crimes, had been assessed with the Psychopathy Checklist-Revised (PCL-R; Hare, 2003). Structural equation modeling results indicated that the four-factor model of psychopathy (Hare, 2003; Neumann, Hare, & Newman, 2007) provided good representation of the dimensional nature of psychopathic traits across the sample of offenders, and that the PCL-R factors significantly predicted sexual crimes. In particular, the Affective and Antisocial psychopathy factors each predicted sexually violent crimes. Latent profile analysis results revealed evidence for a 4-class solution, with the subtypes showing distinct PCL-R facet profiles, consistent with previous research. The four subtypes were validated using sexual crime profiles. The prototypic psychopathy subtype (high on all 4 PCL-R facets) evidenced more violent sexual offenses than did the other subtypes. Taken together, the results demonstrate how variable- and person-centered approaches in combination can add to our understanding of the psychopathy construct and its correlates. (PsycINFO Database Record
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it