Bibliographic record
Abstract
The Supreme Court’s jurisprudence constitutionalizing overbreadth as a principle of fundamental justice under section 7 of the Charter adopted two understandings of the norm. The first conception operates in a “strict” sense wherein any effect of a law that is disconnected from its objective renders the law overbroad. The second conception applies in a “relaxed” manner by prohibiting any application of a law that overshoots its objective more than reasonably necessary. Hamish Stewart’s recent contribution to the literature agrees with and builds upon my prior argument that the strict version of the norm fails to qualify as a principle of fundamental justice. He nevertheless asserts that the relaxed norm ought to maintain its constitutional status. There are, however, two reasons to question this conclusion. First, the relaxed version is highly indeterminate as what is “reasonably necessary” to meet a legislature’s objective provides no concrete restraint on judges declaring laws violative of the Charter. Second, the relaxed norm does not attract adequate consensus as a principle of fundamental justice. Instead, overbreadth in this form operates as a “gross disproportionality light” that effectively crowds out the more intuitive principle of justice that laws must not impose grossly disproportionate effects.
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 | 0.026 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.009 | 0.017 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.035 | 0.038 |
| Insufficient payload (model declined to judge) | 0.007 | 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".