A Framework for Integrating Dimensional and Categorical Classifications of Personality Disorder
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although empirical evidence strongly supports a dimensional representation of personality disorder, there is strong resistance to dimensional classification due in part to concerns about clinical utility. Acceptance of an evidence-based dimensional classification would be facilitated by information on how such a system would map onto existing diagnoses. With this objective in mind, an integrated framework is proposed that combines categorical and dimensional diagnoses. A two-component classification is adopted that distinguishes between the diagnosis of general personality disorder and the assessment of individual differences in the form the disorder takes. Then, the DSM definition of personality disorders is extended by defining individual disorders as categories of trait dimensions. This makes it possible to develop an integrated classification organized around a set of empirically derived primary traits. Assessments of these traits may then be combined to generate categorical and dimensional diagnoses. It is argued that this approach would introduce an etiological perspective into the classification of personality disorder and improve categorical classification by providing an explicit definition of each diagnosis. The clinical utility of incorporating a dimensional classification is discussed in terms of convenience and acceptability, value in predicting outcomes and treatment planning, and usefulness in organizing and selecting interventions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it