Restricted Access to Justice for Canadians Mistreated Abroad: Abdelrazik v Canada (Re: Interim Costs)
Bibliographic record
Abstract
Abousfian Abdelrazik is a Canadian citizen who, after having his name added to various anti-terrorism lists, and after being tortured by Sudanese officials, found himself unable to return home from Sudan largely because of Canadian government actions.Abdelrazik sought to challenge the constitutionality of these restrictions on his ability to return to Canada. However, he had no money and no means of support, as he was unable to leave the Canadian embassy in Sudan where he had sought refuge to avoid further torture by Sudanese officials. He therefore brought a motion for interim costs in Canada’s Federal Court. If granted, this interim costs award would require the Canadian government to pay his legal fees so that his constitutional challenge could proceed.In Abdelrazik v Canada, the Federal Court denied the request for interim costs – a decision that has serious implications not only for interim cost awards jurisprudence, but also for litigation involving citizens who allege that their rights under section 6 of the Charter have been violated. This comment critically analyzes the access to justice implications of the Federal Court decision in light of both the principle that courts may use costs awards to promote access to justice, and the unique challenges faced by Canadians mistreated abroad by the Canadian government.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.006 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".