R. V. Safarzadeh-Markhali: Elements and Implications of the Supreme Court's New Rigorous Approach to Construction of Statutory Purpose
Bibliographic record
Abstract
The Supreme Court of Canada’s decision in Safarzadeh-Markhali holds great significance, beyond Criminal Law, in the area of Statutory Interpretation: in Markhali, the Court decisively endorses a new rigorous approach to construing legislative purpose. Previously, while legislation itself was long-interpreted utilizing rigorous approaches, legislative purpose was typically construed ad hoc while providing only summary justification. Markhali’s new framework is distinct from prior approaches in at least four ways: (1) It expressly acknowledges the critical importance of purpose construction in many cases; (2) It is conscious of how a less-than-rigorous approach risks being self-defeating of larger legal analyses in which the legislative object is compared with legislative means, effects, etc.; (3) It prescribes overarching parameters that clarify what kind of “purpose” the construction seeks; and (4) It delineates the authoritative sources and analytical procedure to be employed in construing the purpose. The result is a “Rigorous Approach” in that it is structured and systematic, clear and capable of consistent application, and solicitous of disciplined adversarial debate and in-depth judicial justification. A salutary impact may be expected on the adjudication of claims emphasizing statutory purpose, including prominent Charter doctrines such as overbreadth, discrimination, and proportionality. This important advance will help strengthen the rule of law and shelter courts from unwelcome accusations of policymaking.
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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 | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.030 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.015 | 0.024 |
| Insufficient payload (model declined to judge) | 0.001 | 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".