Community Sanctions and Measures in Europe and North America
Bibliographic record
Abstract
At the beginning of the 21st century, the field of community sanctions is still in a developmental stage, and the possibilities provided by these new sanctions are not being fully utilized. In many countries, legislation restricts the further development of these sanctions, there is a lack of an adequate infrastructure, and/or community sanctions are not receiving the support they deserve from politicians, judicial authorities and society. Community-based sanctions differ from traditional custodial sanctions in both form and objective, and can make a major contribution to the development of more humane and flexible criminal justice systems. An international exchange of both positive and negative experiences, and a comparison of similarities and differences in legislation and enforcement are the preferred means with which to diminish current prejudices against these modern sanctions and to promote their proliferation. This volume contains all the contributions to the festive seminar the Dutch Probation Service held in 1998 to celebrate its 175th anniversary. The authors are law experts from the USA, Canada, Russia and seventeen Western and Central European countries (Austria, Belgium, Czech Republic, Denmark, England & Wales, Finland, France, Germany, Greece, Ireland, Italy, the Netherlands, Norway, Poland, Portugal, Spain and Switzerland). This publication provides exactly what is needed to stimulate the debate over the further, theoretical and practical development of community sanctions: numerous ideas, many experiences and ample information.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".