Effectiviteit van sanctieprogramma's: bouwstenen voor een toetsingskader
Bibliographic record
Abstract
This study surveys available literature to establish the proven or probable characteristics which penal interventions must meet for particular groups of offenders and/or offences in order to be effective. Can these characteristics be laid down in an assessment framework for effectiveness? Covering the full range of sanctions, for both minor and adult offenders, this report first addresses the study surveys (both meta-analyses and descriptive research surveys) with regard to the effectiveness of sanctions and criminal interventions. It then addresses the effectiveness of interventions with regard to specific offenders and /or offences, followed by a discussion of how this expertise is used in practice abroad. It deals with the cognitions-driven programme Reasoning and Rehabilitation, introduced in Canada and other countries on a large scale, and with the ways in which countries outside the Netherlands try to obtain and maintain a better insight into the effect and execution of interventions. This is followed by the conclusions, while it also looks at how the expertise gained can be used in the Netherlands.
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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 | 0.079 | 0.201 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".