Judicial Discipline through the Prism of Public Law Values: A Contextual Analysis of Bill C-9, An Act to Reform the Judges Act
Bibliographic record
Abstract
Bill C-9 is the first significant legislative reform to the Judges Act in five decades. The goal of the legislation is to enhance public confidence in the administration of justice by modernizing the complaints and discipline regime for federally appointed judges. This essay is a contextual analysis of Bill C-9. The authors begin by outlining a conceptual framework which identifies eight public law goods that can guide an assessment of a complaints and discipline system. They then locate Bill C-9 in a historical context by identifying a crisis of legitimacy that had overtaken the Canadian Judicial Council by the early 2020’s. Having established this context the authors outline seven key strengths of the reform legislation. In a follow up essay entitled, “A Critical Analysis of Bill C-9,” the authors revisit the eight public goods identified in this essay and argue that the legislative reforms are vitiated by five significant weaknesses. The authors conclude that Bill C-9, despite some improvements, reveals a failure of nerve on the part of its proponents and therefore it is unlikely to generate the improved public confidence that is central to the legitimacy of the Canadian judiciary as a democratic institution.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.037 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| 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".