Bibliographic record
Abstract
Section 33 of the Canadian Charter of Rights and Freedoms (Charter) can be used to ensure that legislation operates notwithstanding sections 2 or 7 to 15 of the Charter, but can it be used to ensure that administrative decisions made under legislation survive notwithstanding those provisions, and if so, how? This administrative law—as opposed to purely constitutional law—question has become a live one, given increasing use of section 33 and the evolving framework for assessing whether administrative decisions comply with the Charter. Yet this question is underexplored. In this article, I suggest that section 33 can, in principle, be used to ensure that administrative decisions survive notwithstanding the relevant provisions. I then examine whether section 33 can, in fact, be used in this way—and if so, how. Given the evolving framework for assessing whether administrative decisions comply with the Charter, I distinguish between two general approaches to the framework—one based on Charter rights and the other based on Charter values—and explain the effect of using section 33 in the context of administrative decisions on each approach. On the Charter rights approach, using section 33 has effects that are analogous to the effects of using section 33 in the context of legislation; at the least, it prevents a court from quashing the decision. On the Charter values approach, however, using section 33 has no effect, since using section 33 has no effect on Charter values or their enforcement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".