Evaluation of the Implementation of a Risk-Need-Responsivity Service in Community Supervision in Sweden
Bibliographic record
Abstract
The effective use of the core treatment principles from the Risk-Need-Responsivity (RNR) model has the potential to reduce criminal recidivism significantly. A pilot trial of the RNR-based model Krimstics in the Swedish probation service showed increased RNR adherence but no effects on recidivism. The subsequent implementation of Krimstics involved the training and clinical support of more than 700 probation officers working with community supervision. In parallel, an implementation evaluation examining RNR adherence was undertaken, collecting and coding audio-recorded supervision sessions and case file data. Findings showed that Krimstics-trained probation officers ( N = 96) used cognitive behavioral therapy-based techniques in supervision sessions while demonstrating moderate-to-high levels of relationship building skills. However, adherence to the risk principle was lacking and key cognitive behavioral techniques showed poor quality. Although Krimstics has increased RNR adherence in a Swedish context, challenges with implementing theory into practice may obscure the assessment of the service’s effectiveness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".