The Arbitrariness in “Arbitrariness” (And Overbreadth and Gross Disproportionality): Principle and Democracy in Section 7 of the Charter
Bibliographic record
Abstract
This paper examines the rise to prominence of proportionality analysis in section 7 of the Canadian Charter of Rights and Freedoms. In recent years, the Supreme Court of Canada has affirmed that any law affecting life, liberty and security of the person must not be arbitrary, overbroad or grossly disproportionate. The expansion of section 7’s substantive scope to include means-testing government action re-engages concerns about judicial capriciousness that have troubled section 7 since its early days. This paper examines this concern in light of section 7’s history. It suggests that the prominence of proportionality analysis in section 7 may be understood as, in part, an effort to avoid the difficult task of setting normative boundaries on the scope of the provision. This paper argues that substantive values are inescapable as courts identify and frame these goals and scrutinize proportionality with close attention to real-world impacts of government action. Drawing on comparisons with the role played by proportionality analysis in section 1 of the Charter, the paper suggests that means-testing government policy should be guided by the Court’s institutional role, but with careful attention to the substantive purpose of section 7 of the Charter as a right, a purpose that includes protection against overweening majoritarianism. Such a purposive interpretation may permit proportionality analysis to be informed by democratic deficits and political powerlessness in government law and policy-making processes.
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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 | 0.022 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.078 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.012 |
| 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".