A Question of Style: Refining the Dimensions of Personality Disorder Style
Bibliographic record
Abstract
The frequent finding that meeting criteria for one type of personality disorder (PD) is commonly associated with meeting criteria for several other PDs indicates significant problems in defining and measuring PDs independently of each other, whether measured categorically or dimensionally. This study was designed to enrich recent DSM descriptor sets and, with the enriched set of descriptors, develop refined PD dimensions. A large sample of patients with a PD or significant personality disturbance were studied, with most analyses based on self-report (SR) data, but with corroborative witness (CW) data also collected to validate refinement analyses. The original descriptor set comprised 139 DSM descriptors and 127 items obtained from other sources. Personality disorder dimensions of interest were refined by factor analyses. We specifically identify items that failed to "belong" to their original PD "base." A refined set of 92 items demonstrated greater independence of the underlying dimensions and suggested an underlying five-factor structure at some variance to the current DSM-IV cluster set. The study should assist measurement of individual PDs by identifying items and constructs that build to more homogeneous dimensions that define lower-order and higher-order PD traits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".