'Constitution Chicken': National Security Confidentiality and Terrorism Prosecutions after R. v. Ahmad
Bibliographic record
Abstract
This article examines the Supreme Court’s decision in R. v. Ahmad to reverse a decision made by the trial judge in the Toronto terrorism prosecution and to uphold the constitutionality of Canada’s unique two court system to deciding public interest immunity questions involving state claim’s of national security confidentiality. Parliament’s decision to only allow a few specially designated judges of the Federal Court to decide such questions will be related to Canada’s anxieties about being a net importer of intelligence and excessive concerns about secrecy. It will be suggested that the trial judge who ruled that s.38 was unconstitutional had a better grasp of the practical challenges of the two court system including multiple applications and appeals during a jury trial and the drastic nature of the stay remedy than the Supreme Court. The Supreme Court’s approach to reading down the legislation to avoid holding it unconstitutional is critically assessed . It is suggested that terrorism prosecutions will be more difficult in the future and that the Attorney General of Canada will often be in the driver’s seat in a constitutional game of chicken. Only that official will be able to decide whether to disclose information previously ordered not to be disclosed by the Federal Court in order to avoid the trial judge’s drastic and blunt remedy of a stay of proceedings under s.38.14 of the Canada Evidence Act.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.015 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.015 | 0.018 |
| Insufficient payload (model declined to judge) | 0.003 | 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".