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Record W3006162667

Intervenors at the Supreme Court of Canada

2020· article· en· W3006162667 on OpenAlexaboutno aff
Geoffrey D. Callaghan

Bibliographic record

VenueeYLS (Yale Law School) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsSupreme courtLawPolitical science
DOInot available

Abstract

fetched live from OpenAlex

My aim in this paper is to offer a normatively attractive and explanatorily sound interpretation of the Supreme Court of Canada’s approach to third party intervention. The crux of my interpretation is that the policy the Court has developed on intervenors allows it to strike a reasonable balance among a number of competing democratic considerations, all of which have value in the context of judicial decision making. In this respect, the Court should be commended for identifying a way to liberalize a practice that possesses many democratically-attractive features, but also the inherent capacity to undermine the democratic standing of the Court. I buttress my argument against early literature on the subject, and use more recent works by Ian Brodie and Benjamin Alarie and Andrew Green as argumentative foils.\nMon but dans cet article est d’offrir une interprétation normative attrayante et explicative de l’approche de la Cour suprême du Canada en matière d’intervention des tiers. L’essentiel de mon interprétation est que la politique que la Cour a élaborée à l’égard des intervenants lui permet d’établir un équilibre raisonnable entre un certain nombre de considérations démocratiques concurrentes, qui ont toutes une valeur dans le contexte du processus décisionnel judiciaire. À cet égard, il convient de féliciter la Cour d’avoir trouvé une façon de libéraliser une pratique qui possède de nombreuses caractéristiques attrayantes sur le plan démocratique, mais en même temps la capacité inhérente de miner la position démocratique de la Cour. J’étaye mon argument contre la littérature ancienne sur le sujet, et j’utilise les travaux plus récents de Ian Brodie et de Benjamin Alarie et Andrew Green comme contrepoids argumentatif.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.136
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0240.010
Scholarly communication0.0130.002
Open science0.0020.003
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0060.000

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 head0.019
GPT teacher head0.253
Teacher spread0.234 · 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 designNot applicable
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

Citations3
Published2020
Admission routes1
Has abstractyes

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