The notwithstanding clause in the Canadian charter of rights and freedoms: a new interpretive approach
Bibliographic record
Abstract
The notwithstanding clause is a constitutional tool that can be invoked by federal, provincial, and territorial legislatures. It provides these legislatures with the ability to pass legislation that either pre-empts or overrides judicial review that concern certain Charter rights. Any notwithstanding clause legislation must contain a renewable five-year sunset clause. The notwithstanding clause has been tabled in legislation twenty-five times. Between 2018 and 2022, there were seven notwithstanding clause bills tabled in four provincial legislatures. These post-2018 notwithstanding clause invocations raise important questions about the role of the judiciary in substantively evaluating section 33. Currently, the only authoritative case law on the notwithstanding clause is Ford v Quebec. In Ford, the Supreme Court of Canada determined that the notwithstanding clause should be evaluated in ‘form-only’, without substantive review of its use. Through my thesis, I seek to critically engage with Ford and ask, ‘can substantive limits be placed on the notwithstanding clause through judicial review?’. After identifying shortcomings within theoretical approaches to the notwithstanding clause and critiquing Ford, I will present my own theory on the need to revisit the judiciary’s approach to interpreting the notwithstanding clause. Through the application of ordinary approaches to Canadian constitutional interpretation, I argue there are at least four limits on notwithstanding clause application: (1) section 33 cannot be invoked in an omnibus manner; (2) the the unwritten constitutional principle of democracy limits its application to political expression; (3) customary international law jus cogens norms limits its application to torture; and (4) section 28 of the Charter safeguards gender equality from its scope. My four proposed limits on the notwithstanding clause do not represent an exhaustive approach on limits to section 33. Instead, I argue that there are judicial review limits on section 33 that can be derived through constitutional interpretation and non-exhaustively explore four.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.015 | 0.064 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".