Extradition and trial delays: recent developments (and lessons?) from Canada
Bibliographic record
Abstract
Extradition – the formal rendition of criminal fugitives between states – is well-known to be a time-consuming process that often has impacts, minor or major, on the ability of states to complete prosecution in a timely manner. Thus, the extradition process can sometimes be at odds with the right to trial within a reasonable time, which is part of the overall package of fair trial rights enshrined in international human rights law. In Canada, this right is implemented by paragraph 11(b) of the Canadian Charter of Rights and Freedoms. In recent years, Canadian courts have developed a series of principles to be applied to cases where extradition is involved in claims of trial delay. These range from the prosecution’s obligation to pursue timely trial in a diligent manner, to the extent to which extradition should simply be treated as procedurally neutral, to the attribution of delays when an accused has deliberately left the country to avoid prosecution. This body of case law is surveyed and analysed in this article, as a means of providing an illustrative example of state practice regarding this right. The authors conclude that, while Canadian law on this question is not entirely coherent internally, it generally complies with international standards.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.015 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".