Sex Offender Supervision: Communication, Training, and Mutual Respect Are Necessary for Effective Collaboration Between Probation Officers and Therapists
Bibliographic record
Abstract
Developed with the goal of preventing recidivism, contemporary sex offender supervision models focus on collaboration between probation officers and therapists. This exploratory study used focus groups to examine the working relationships between probation officers and therapists from two large U.S. urban probation departments. Overall, both probation officers and therapists were quite positive about their working relationships; they valued each others' roles and agreed that regular, accurate, and timely communication occurred frequently. Not all relationships, however, were effective. Several probation officers and therapists expressed dissatisfaction with poor communication, conflicts between the goals of therapy and probation, a lack of resources, and deficits in the policies they needed to adequately implement components of their supervision model (the containment model). Our findings suggest ways to structure sexual offender supervision that integrate the distinct orientations of probation officers and therapists into a collaboration that promotes public safety and work well for all.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".