Organizations treating sexual offenders in Manitoba : case studies of management, innovations, and barriers
Bibliographic record
Abstract
This introductory multiple case study described the structure, activities and critical issues of four (4) sex offender treatment agencies in the City of Winnipeg. The study applied the correctional policy model of Ekstedt and Griffiths (1988) to each of these agencies, and examined the fit between the policy model and the findings. The four agencies included a psychiatric clinic, residential facility, small government program, and voluntary support program. The study was conducted using the case study method of Yin (2003) and qualitative research method (Berg, 2001). Sixteen (16) interviews were conducted with paid workers and volunteers at the treatment agencies. Interviews focused on the relevant policy issues and the link between policy and direct practice. In addition, document data supplemented and corroborated interview findings. Cross-case analysis identified a number of significant issues in the offender treatment field in Manitoba, including the high support needs of sexual offenders, the existence of oppressive practices, as well as impressive organizational strengths. Based on the findings, the writer put forth a number of conclusions and recommendations regarding offender treatment agencies, in seeking best practice, supporting workers in a difficult field, and promoting accountability. The findings also demonstrated a moderate fit with the correctional policy model, and suggestions for further theory building were made.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.029 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| 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".