Bibliographic record
Abstract
The chapter presents an analysis of the application of the proportionality doctrine in the case law of the Canadian Supreme Court. Based on both a qualitative and quantitative analysis of a large sample of case law applying proportionality, the chapter uses quantitative indicators to provide an overview of the characteristics of proportionality analysis in action, including the rights and subject matters to which proportionality is applied, the division of labour between the stages of the analysis when striking down measures, and termination rates for each stage following a failure. The findings reinforce the existing perception that minimal impairment is central to Canadian proportionality analysis: it is the stage where the largest number of cases fail and half of the time the Court does not proceed to even consider the final balancing stage. Even when cases fail at the substantial objective or rational connection stage – which happens more often than generally acknowledged – the court almost always continues the analysis to the minimal impairment stage for an additional failure. The chapter further analyses qualitatively the application in practice of each of proportionality's subtests, exposing the range of interpretations given and the content that has been infused into the different stages.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.018 | 0.014 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".