'Prevent' policies and laws: a comparative survey of the United Kingdom, Malaysia and Pakistan
Bibliographic record
Abstract
In the years since 9/11 counter-terrorism law and policy has proliferated across the world. This book sets out a comprehensive survey of how the law has been deployed in all aspects of counter-terrorism. The handbook provides an authoritative and critical analysis of how laws are, and ought to be, invoked in domestic jurisdictions against terrorism. With a comparative approach the focus is on those jurisdictions which have produced legal innovations with a sizeable impact, primarily the USA, the UK, Australia, Canada, France, Germany and the European Union. \n \nThe never before published contributions to the book are written by experts in the field of terrorism law and policy, allowing for discussion of a wide range of regulatory responses and strategies of governance. The book is divided into four parts: the boundaries and strategies of national counter-terrorism laws; the pursuit of terrorists through national criminal process and executive measures; protective security; and preventive measures. The chapters engage with areas of traditional interest to lawyers such as policing and special powers, criminal offences and the courts, and prison regimes but also tackle emerging subjects including preventing radicalisation and protective/preparative security. In this way the handbook reflects the elements of counter-terrorism laws which are more transformative of mass movements and transactions alongside prosecutions or orders aimed at particular individuals.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".