The role of antisociality in the psychopathy construct: Comment on Skeem and Cooke (2010).
Bibliographic record
Abstract
J. Skeem and D. J. Cooke (2010) asserted that Hare and Neumann consider criminality to be an essential component of the psychopathy construct. The assertion, presented in the guise of a debate on the nature of psychopathy, is neither accurate nor consistent with the clinical and empirical literature on psychopathy to which Hare and Neumann have contributed. Broadly defined antisociality, not criminality per se, is considered to be part of the psychopathy construct. Skeem and Cooke also expressed concerns that the popularity of the Psychopathy Checklist-Revised (R. D. Hare, 2003) inhibits the development and use of other instruments, that it has become the construct it measures, that it deviates from its clinical roots, and that it conflates criminality with personality. These and related issues are addressed, and it is suggested that the arguments proffered by Skeem and Cooke are not convincing, nor do they provide clear directions for theory and 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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.081 | 0.068 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".