A Five-Factor Model Description of Depressive Personality Disorder
Bibliographic record
Abstract
This investigation extends previous work on Five-Factor Model (FFM) personality disorder profiles. Specifically, a FFM expert consensus prototype for Depressive Personality Disorder (DPD) using the 30 facets of the NEO Personality Inventory-Revised (NEO PI-R) was developed. Initial validation of this prototype in a psychiatric population employed several clinical scales. When combined with trait information yielded by criteria translation and empirical approaches, the composite FFM profile emphasized several facets that represent the core components of DPD. In addition to several traits represented by the current DSM conceptualization of DPD, such as depressiveness, anxiousness, self-consciousness, and low tendermindedness, the composite profile was also characterized by several unrepresented traits, such as high modesty and low positive emotionality, warmth, assertiveness, trust, and achievement striving. Future definitions of depressive personality, conceptualized either as a DSM-V personality disorder or as a multifaceted construct, should consider these additional traits.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".