Bibliographic record
Abstract
The therapeutic process in the clinical and social management of professional sexual misconduct is complex and complicated by legal reports and procedures, the involvement of professional association review boards and the negative impact of the media.Crisis interventions and supportive individual, couple and family counseling are frequently necessary before therapy can more directly focus on the sexual misconduct.Offenders usually hope to maintain, or expect to resume, their professional practice, increasing the use of deception, denial of problems and avoidance of self-revelation and self-examination.Through the course of treatment, reintegration into their professional practice may or may not be recommended.If reintegration is feasible, modification of their professional roles may also be preferable and recommended.However, prognosis is usually considered better than with most other types of sex offenders.A major focus of this anaylsis is to provide a description of current treatment procedures for professional sexual misconduct.A brief review of the immediate and deeper causes of this sexual problem will also be presented.When reintegration in the workplace is feasible, issues concerning posttreatment maintenance planning, identification of the victim pool and the establishment of preventive measures and safeguards will be reviewed.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".