Charkaoui and Bill C-3: Some Implications for Anti-Terrorism Policy and Dialogue between Courts and Legislatures
Bibliographic record
Abstract
The first part of the paper examines Charkaoui withparticular attention to the Court’s survey of less rights-invasive alternatives, including British special advocates and the Arar Commission’s use of security-cleared lawyers. The Court’s holding with respect to indeterminate detention and its relation to the possibility of deportation to torture is also examined.The second part of the paper examines the legislative response to Charkaoui with attention to the role of special advocates and the role of Federal Court judges in defining their precise role. The issue of whether Parliament simply obeyed the Court’s decision or expanded the policy debate is examined. In the third part, Bill C-3 is assessed as an example of truncated dialogue with respect to both security certificates and the treatment of secret information. The conclusion assesses the lessons of Charkaoui and Bill C-3 both for the development of fair and effective anti-terrorism policy and for dialogue between courts and legislatures about the treatment of the rights of the unpopular. It suggests that many issues are left to be resolved with respect to both the sustainability of security certificates and the proper approach to secret information in security certificate proceedings and other legal proceedings.
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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 | 0.023 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.021 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.035 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".