Structure of Pathological Personality Traits Through the Lens of the CAT-PD Model
Bibliographic record
Abstract
Personality pathology is increasingly conceptualized within hierarchical, dimensional trait models. The Comprehensive Assessment of Traits Relevant to Personality Disorders (CAT-PD) is a pathological-trait measure with potential to improve on currently prevailing instruments because it has wider content coverage; however, its domain-level structure, which is of scientific and clinical interest, is not established. In this study, we investigated the structure and construct validity of the CAT-PD’s domain level to facilitate wider use of the measure. We estimated five- and six-factor models with exploratory factor analysis in a pooled sample of eight independent subsamples ( N = 3,987) and found that both models fit the data well; each had interpretable factors that were invariant across gender, sample type, and Black/White racial groups; and the factors had good convergent validity with other measures of maladaptive traits, Big Five personality, and interpersonal problems. Our results support the validity of the CAT-PD for assessing multiple levels of the pathological trait hierarchy.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".