Are Psychopathic and Borderline Personality Disorder Distinct, or Differently Gendered Expressions of the Same Disorder? An Exploration Using Concept Maps
Bibliographic record
Abstract
Research findings on gender differences in prevalence and clinician gender bias in the diagnosis of Psychopathic Personality Disorder (PPD) and Borderline Personality Disorder (BPD) have led some to suggest that PPD and BPD are not distinct disorders, but rather differently gendered expressions of the same disorder. This paper explores gender differences in conceptualization using prototypicality ratings of PPD and BPD symptoms from the Comprehensive Assessment of Psychopathic Personality (CAPP; Cooke, Hart, Logan, & Michie, 2004 , 2012 ) and the Comprehensive Assessment of Borderline Personality (CABP; Cook et al., 2013 ). Findings indicated that symptoms of PPD and BPD are gendered, but did not appear consistent with the view that PPD and BPD are differently gendered variants of the same disorder. Unfortunately, the implications of our findings for clinical practice are not clear at this time. Future research should explore effective methods to mitigate clinician bias and/or explore the development of gender-fair measures.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".