Redressing the Harms of Government (In)Action: A Section 7 Versus Section 15 Charter Showdown
Bibliographic record
Abstract
When considering the recent Charter claims of vulnerable individuals seeking to redress the harms of government action or inaction, there are two related trends in the appellate case law on sections 7 and 15 that merit attention.1 First, the Supreme Court has undertaken new approaches to equality rights under section 15(1) and 15(2) of the Charter, with a marked lack of success of claims in spite of (or perhaps because of) these approaches. The cases of Kapp,2 Withler,3 and Cunningham4 will be discussed in Part II as illustrations of this trend, along with cases where section 15 was given scant attention, such as Hutterian Brethren,5 AC v Manitoba,6 and Fraser.7 Second, there has been relative success of Charter claims under section 7 where there is strong evidence of harm to life, liberty or security of the person in circumstances where the government action was arbitrary, grossly disproportionate, or overbroad. In Part III, the cases of PHS Community Services,8 Adams,9 and Bedford10 will be shown to reflect this trend.11 These cases present an opportunity to discuss whether section 7 holds advantages over section 15 as a tool for disadvantaged persons challenging the harms of government (in)action, which will be addressed in Part IV. I conclude that while framing government harms as violations of life, liberty or security of the person may be a winning strategy for some Charter claimants, not all such harms can be presented in those terms, and the particular harms captured by section 15 must be given their due.
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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 | 0.009 | 0.020 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.019 | 0.017 |
| 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".