Constitutionalism and the Genetic Non-Discrimination Act Reference
Bibliographic record
Abstract
In the July 10, 2020 decision in Reference re Genetic Non-Discrimination Act (GNDA Reference), the Supreme Court of Canada arrived at a complex three-to-two-to-four outcome, with a slim five-justice majority in two separate judgments upholding challenged portions of the federal Genetic Non-Discrimination Act (GNDA) as a valid exercise of Parliament’s criminal law power. The federal legislation, which some thought related to certain aspirations of preventing genetic discrimination, seemed to have attractive policy objectives, though we will ultimately suggest that the form of the legislation was not entirely in keeping with these aims. While it may have appeared pragmatically attractive to uphold the legislation, we suggest that the majority’s decision to do so comes at great cost to basic federalism principles, to legal predictability, and to prospects for well-informed intergovernmental cooperation. To make our argument, we first set out some basic background concerning the case in Part II of the Article. We turn in Part III to discuss why it is especially problematic that the case saw three different conclusions on the pith and substance of the law and to show how the four-justice dissenting opinion of Kasirer J. best respected established approaches to characterizing pith and substance. In Part IV, we examine the effects of the legislation on the provincial insurance context and how these bear on the analysis. In Part V, we show how the decision has perpetuated ongoing legal unpredictability concerning the scope of the federal criminal law power and why that sort of unpredictability undermines policy development and intergovernmental negotiation. To conclude, in Part VI, we suggest some ways that the courts can achieve a necessary course correction by properly confining the effects of the GNDA Reference decision and by taking specific steps to ensure that future federalism jurisprudence is not seen as being affected by extraneous considerations related to the perceived merits of particular policies.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.030 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".