The DSM-5 Personality Disorder Proposal and Future Directions in the Diagnostic Classification of Personality Disorder
Bibliographic record
Abstract
BACKGROUND: The compilation of DSM-5 presented a substantial opportunity to develop a coherent, evidence-based classification of personality disorder. The irremediable problems with DSM-IV are widely recognized, the field seemed ready for change, and the data and methods for constructing a scientific classification are readily available. Rather than seize this opportunity, DSM-5 advanced an incoherent proposal lacking in evidential support and too poorly organized for clinical use. METHODS: This article examines the problems with the proposal based on a consideration of the basic requirements of a satisfactory classification. It is suggested that an adequate system should have an explicit and coherent conceptual structure, be based on the best available scientific evidence, possess clinical utility, and be as parsimonious as possible. RESULTS: The DSM-5 proposal fails to meet these criteria. Problems with the product and process suggest the need for a radical reconsideration of how personality disorders are classified and how classifications are compiled. CONCLUSIONS: The article proposes that greater emphasis be placed on developing a classification that provides the diagnostic information clinicians need to treat personality disorder and that future classifications should be constructed through an explicit process that is open to public scrutiny.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.093 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".