<i>Fleming v Ontario</i>
Bibliographic record
Abstract
The willingness of courts to create new common law powers has ebbed and flowed over time. Whether to do so at all was a matter of some debate in R. v. Dedman (1985), 46 C.R. (3d) 193 (S.C.C.), and even after that case set the precedent of doing so, it was another fifteen years before the Court did so again, in R. v. Godoy (1998), 21 C.R. (5th) 205 (S.C.C.). However, Godoy was a bit of a tipping point, leading courts to become quite open to the creation of such powers through the early 2000s. This was so to the extent that in R. v. Kang-Brown (2008), 55 C.R. (6th) 240 (S.C.C.), four of the nine judges - the largest cohort in the case, but the minority on the particular issues of whether to create a power in that instance - expressed discomfort with how frequently this was occurring, observing at para. 6 that "[t]hese precedents do not mean that the Court should always expand common law rules, in order to address perceived gaps in police powers or apprehended inaction by Parliament, especially when rights and interests as fundamental as personal privacy and autonomy are at stake."
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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; both teacher heads agree on what is shown here.
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".