Management of professional sexual misconduct: Evaluation and recommendations
Bibliographic record
Abstract
Despite condemnation by ethical codes, published guidelines and policies for all the helping professions, sexual exploitation by health and mental health professionals remains a prevalent but poorly understood problem.It is estimated that half of all mental health clinicians will evaluate and/or treat at least one person who was sexually exploited by a previous psychotherapist, physician, psychiatrist or other health or helping professional.Because these sex offenders are professionals, they are more frequently subject to moral indignation, societal disgust, shame and negativity than other sex offenders.Following their arrest and the interruption, or termination, of their practice, these offenders are particularly at risk for major depressions, emotional breakdowns and suicide.Given the hope to maintain or the expectation to return to their professional practice, the evaluation process may be complicated by the offender's use of deception and denial, and avoidance of self-revelation and self-examination.Considering the nature of the offense, the degree of psychopathology and overall occupational functioning, reintegration in the offender's professional practice may or may not be recommended.For others, modification of their professional roles may be indicated.
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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 | 0.025 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".