Problematic Physicians: A Comparison of Personality Profiles by Offence Type
Bibliographic record
Abstract
OBJECTIVE: This exploratory study compares objective personality test findings among physicians exhibiting different forms of misconduct. The importance of delineating distinctive personality characteristics by type of offence is that such characterizations can direct therapy and prognosis for remediation. METHOD: Eighty-eight physicians referred to the Vanderbilt Comprehensive Assessment Program for Professionals (V-CAP) completed the Minnesota Multiphasic Personality Inventory-2, the Personality Assessment Inventory, or both, as part of their evaluation. On the basis of referral information, physicians were partitioned into 3 groups of offenders: "sexual boundary violators," "behaviourally disruptive," and "other misconduct." RESULTS: On both personality measures, the sexual boundary violators generated the greatest percentage of profiles indicative of character pathology. CONCLUSIONS: Although all 3 groups exhibited unacceptable behaviours, the pervasive personality features of the sexual boundary violators are associated with greater therapeutic challenge, and these individuals likely pose the greater risk of reoffending.
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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".