Universal Jurisdiction in a Common Law Context
Bibliographic record
Abstract
Abstract This research examines the limited use of universal jurisdiction in Canada for the prosecution of serious international crimes such as genocide, war crimes, crimes against humanity, and torture. Despite Canada’s early adoption of a robust legal framework permitting universal jurisdiction, actual prosecutions remain rare, especially when compared to continental European states. The analysis identifies three primary factors contributing to this gap: political and institutional constraints, legal challenges inherent to the common law system, and practical obstacles in evidence gathering and prosecution. Employing doctrinal research and insights from an interview with Canadian officials, the article explores how Canada’s ‘no safe haven’ policy, selective prosecution strategies, and reliance on immigration remedies have shaped its approach. The study shows the impact of executive influence, prosecutorial discretion, and evidentiary hurdles, as well as the evolving practice of structural investigations and international cooperation. Ultimately, this article argues that Canada’s approach — grounded more in political calculation and alliance consensus than in proactive international justice — limits the effectiveness of universal jurisdiction as a tool for accountability.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.023 | 0.050 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".