Forty years of crime prevention in the Dutch Polder
Bibliographic record
Abstract
For the past two decades the growth of public policies and strategies aimed at crime prevention and community safety has constituted one of the major innovations in crime control, with significant implications for the manner in which crime and safety are governed. But how has 'the preventive turn' in crime control policies been implemented in various different countries and what have its implications been? What lessons have been learnt over the ensuing years and what are the major trends influencing the direction of development? What does the future hold for crime prevention and community safety? These are some of the questions explored by in this book through a comparative analysis of developments in crime prevention policies across a number of European countries. Contributors explore and assess the different models adopted and the shifting emphasis accorded to differing strategies over time. The book also seeks to compare and contrast different approaches as well as the nature and extent of policy transfer between jurisdictions and the internationalisation of key ideas, strategies and theories of crime prevention and community safety. The book brings together a collection of leading international experts to explore the lessons learnt through implementation and the future directions crime prevention policies. Many of the contributors have been closely involved in crime prevention and community safety policy and research in different countries over a number of years. As such, they are well placed to reflect upon developmental trajectories and the direction of change over the last quarter of a century, as well as to draw out the underlying influences that have shaped such changes.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".