Constitutional Legitimacy and Responsibility: Confronting Allegations of Bias After Wewaykum Indian Band v. Canada
Bibliographic record
Abstract
This paper reviews the unusual case of Wewaykum Indian Band v. Canada where a motion to vacate the judgment was brought after the Court had rendered a unanimous decision on the merits of the case. It was alleged that a reasonable apprehension of bias existed because of involvement that Justice Binnie (who authored the decision) had with this file while Associate Deputy Minister of Justice of Canada some 15 years earlier. In the first part of the paper, the author reviews the Supreme Court’s decision in Wewaykum, focusing on several key issues in the disqualification motion. In the second part of the paper, the author contends that Wewaykum is also an important constitutional case. The author contends that judicial impartiality is a core value in the Canadian constitutional system and that challenges to the impartiality of the Supreme Court constitute attacks on the Constitution itself. In response to the age old question of Sed quis custodiet ipsos Custodes? — who guards the guardians — this paper argues that Parliament, the bar and the Court itself each have a duty to protect the integrity of the Court. The paper proposes means for each of these parties to protect the Court and, ultimately, the Constitution as well.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.034 | 0.029 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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".