Bibliographic record
Abstract
Abstract After centuries of near dormancy, the concept of ‘universal jurisdiction’ has suddenly become an important legal tool in the international campaign against impunity, most prominently in high-profile criminal trials. Among the legal questions raised by the exercise of universal jurisdiction, this book considers two. Under what conditions is a country investigating or prosecuting a foreigner for an extraterritorial offence internationally competent? What is the basis in municipal law for the exercise of universal jurisdiction? The book first identifies the international legal issues that arise when a State exercises extraterritorial jurisdiction generally, discerns the different doctrinal concepts of universal jurisdiction, and traces universal jurisdiction in current international texts such as multilateral conventions, resolutions of intergovernmental bodies, and official drafts and studies. The book then brings together, and makes accessible in English, detailed accounts of universal jurisdiction in fourteen countries: Australia, Austria, Belgium, Canada, Denmark, France, Germany, Israel, the Netherlands, Senegal, Spain, Switzerland, the United Kingdom, and the United States. The municipal laws are placed in the larger context of a country’s views on criminal jurisdiction generally and the case discussions pay detailed attention to the factual and legal context of each case. This approach provides the reasons why the individual was brought to justice in a third country.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".