Reconstruing the “Reconstruction” of Psychopathy: A Comment on Cooke, Michie, Hart, and Clark
Bibliographic record
Abstract
In this comment we highlight critical problems in the estimation of parameters for their hierarchical three-factor model of psychopathy, as assessed with the Hare Psychopathy Checklist, and their interpretation of these factors as causally related to socially deviant behavior. We argue that there is nothing "causal" about a model in which cross-sectional data are used to assert that antisocial tendencies are consequences of other more fundamental psychopathic traits. We present an equally viable model, based on the PCL-R four-factor solution, in which antisocial tendencies play a fundamental role in the construct of psychopathy, consistent with previous research and clinical tradition.
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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 | 0.014 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.059 | 0.074 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".