International & Transnational Criminal Law
Bibliographic record
Abstract
International criminal law has focused on the prosecution of truly international crimes — genocide, crimes against humanity, war crimes, and aggression. Our post-Cold War, post-9/11 world has also seen the growth of transnational crimes of international concern, such as terrorism, money laundering, organized crime, and human and narcotics trafficking, as well as transnational crimes of domestic concern, which are simply ordinary domestic crimes that involve the jurisdiction of more than one state. This book surveys these two related but increasingly distinct fields with a focus on Canada, bringing together in one accessible text topics that are of increasing importance in a world of globalized crime. The second edition updates caselaw from Canada as well as international courts and tribunals, transnational criminal law treaties, and recent literature, and adds a new chapter on extended liability, defences, and child soldiers. It reviews the new definition of the crime of aggression and some of Canada's new criminal cooperation ventures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".