A search for consensus on the dimensional structure of personality disorders
Bibliographic record
Abstract
Previous attempts to elucidate the dimensional structure of personality disorders (PDs) have been based on single samples and measures. Like one-item tests, they are useful but scattered and potentially misleading glimpses at the true structure of PDs. Therefore, reanalyses of 33 previously published data sets were conducted using recommended statistical procedures to arrive at consensus structures. Similar reanalyses of published data were conducted on associations between PDs and the five-factor model of normal personality characteristics. High degrees of congruence were observed between the consensus PD structures and the consensus structures suggested by dimensions of normal personality. The analytic techniques used in the present study helped bypass methodological problems inherent in previous tests and revealed higher levels of support for both theoretically and empirically based representations of the five-factor model approach to PDs.
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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 | 0.023 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".