Antisociality and the Construct of Psychopathy: Data From Across the Globe
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous theory and research on the structural, longitudinal, and genetic nature of psychopathy have provided strong conceptual and empirical evidence that overt antisociality is a component of the psychopathy construct (Hare & Neumann, 2008, 2010; Lynam & Miller, 2012). However, determination of the strength of the association between antisociality and other psychopathic features has not been explored systematically. The current article draws on previously published large North American studies, as well as data from across the globe, to estimate the strength and pattern of the associations between overt antisociality and other psychopathic domains in a diverse set of samples. Structural equation modeling was used to estimate model parameters from samples that had data on either the Psychopathy Checklist-Instruments (PCL-R, PCL: YV, PCL: SV) or self-report assessments that have known latent structures (SRP, B-Scan 360). In addition, two relatively large samples (male offenders and young adult males), assessed with both the PCL-R and the SRP, provided an opportunity to examine the link between antisociality and the other psychopathy domains across different assessment methods. The overall findings indicate that the associations were moderate to strong, depending on the nature of the sample, and clearly indicate that antisociality is a core component of the psychopathy construct.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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