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Record W3156668608

Constitutionalism and the Genetic Non-Discrimination Act Reference

2020· article· en· W3156668608 on OpenAlexvenueaboutno aff
Qc Shannon Hale and Dwight Newman

Bibliographic record

VenueConstitutional Forum / Forum constitutionnel · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDiscrimination and Equality Law
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationSupreme courtPolitical scienceFederalismJurisprudenceLawConstitutionalismLaw and economicsEconomic JusticeSociologyPoliticsDemocracy
DOInot available

Abstract

fetched live from OpenAlex

In the July 10, 2020 decision in Reference re Genetic Non-DiscriminationAct (GNDA Reference),1 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)2 as a valid exercise of Parliament’s criminal law power. The legislation, which some thought fundamentally oriented to the goal 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. We argue that the courts must properly confine the effects of the GNDA Reference in accordance with established principles on the treatment of fragmented judicial opinions. We also argue that the courts must take significant steps to ensure that federalism jurisprudence remains well-grounded in legal principle, without the actual or apparent influence of extra-legal policy considerations[...]

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.024
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.309
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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