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Record W2808225335 · doi:10.3138/utlj.2017-0074

The architectural metaphor and the decline of political conventions in the Supreme Court of Canada’s <i>Senate Reform Reference</i>

2018· article· en· W2808225335 on OpenAlexaffvenueabout
Christa Scholtz

Bibliographic record

VenueUniversity of Toronto Law Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsMcGill University
Fundersnot available
KeywordsSupreme courtLawConstitutionPolitical scienceArgument (complex analysis)PoliticsNominationSeparation of powersConstitutional lawPolitical questionCampaign financeFederalismSociology

Abstract

fetched live from OpenAlex

In 2014, the Supreme Court of Canada rejected the federal government’s Senate reform agenda. This article focuses on the Court’s response to the government’s proposal for consultative (non-binding) elections, which would have had the prime minister consider recommending an electorate’s preferred candidate for nomination by the governor general. The Court rejected the government’s argument that the proposal was consistent with the legally unenforceable parliamentary conventions of responsible government. The Court characterized the proposal as a break in Canada’s ‘constitutional architecture.’ I ask: how is it that Canada’s constitutional architecture has become unconventional? My answer lies in the Court’s theorization of what the Constitution is and how it may be amended. I trace a shift in the Court’s metaphorical reasoning, from the 1981 Patriation Reference’s Constitution as dynamic machine where conventions are its ‘operative force’ to the 1998 Secession and 2014 Senate Reform References, where a static and aesthetically coherent Constitution as architecture emerges. I argue that, in its architectural understanding, the Court understates the role of conventions in constitutional amendment and finally casts conventions as the saboteurs of a unified constitutional design.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.109
Threshold uncertainty score0.793

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0400.051
Scholarly communication0.0150.003
Open science0.0020.003
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.245
Teacher spread0.231 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations4
Published2018
Admission routes3
Has abstractyes

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