The Hierarchical Structure of the Dimensional Assessment of Personality Pathology (DAPP-BQ)
Bibliographic record
Abstract
Hierarchical personality models have the potential to identify common and specific components of DSM-IV personality disorders (PDs), and may offer a solution for the re-tooling of personality pathology in future versions of the DSM. In this paper, we examined the hierarchical structure of the Dimensional Assessment of Personality Pathology-Basic Questionnaire (DAPP-BQ; Livesley & Jackson, 2009) and the capacity of various trait components at different levels to predict DSM-IV PD symptoms. Participants were 275 psychiatric outpatients and 365 undergraduate students. Goldberg's (2006) bass-ackwards method was used to investigate the hierarchical structure of the DAPP-BQ. The predictive capacity of hierarchy components was assessed. We found that Level 5 of the hierarchy enhanced the capacity of the DAPP-BQ for predicting DSM PD symptoms beyond a four-factor structure, particularly for borderline PD.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".