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Record W3033892577

With a Little Help from Too Many Friends? Lessons from TWU and Comeau on Intervening Before the Supreme Court

2019· article· en· W3033892577 on OpenAlexaboutno aff
Christopher D. Bredt, Ewa Krajewska, Mannu Chowdhury

Bibliographic record

VenueSSRN Electronic Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Systems and Judicial Processes
Canadian institutionsnot available
Fundersnot available
KeywordsViewpointsSupreme courtIntervention (counseling)Framing (construction)LawPolitical scienceSociologyLaw and economicsPsychologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

Under the Supreme Court of Canada’s (“SCC”) current approach to intervention, the Court grants leave to almost all parties seeking to intervene and allots them 10 pages for their written submissions and five minutes for their oral arguments. The authors argue that these constraints make it difficult for “friends of the court” to meaningfully engage with the SCC. At the heart of the problem is a screening policy that hinders interveners from providing, and the Court from receiving, assistance. The SCC’s approach restricts interveners who are advancing meritorious and nuanced positions to the same limits as those proffering the Court with generic or duplicative viewpoints. The result is one of mutual dissatisfaction: The Court does not get the full assistance that it could from interveners, and interveners — who are keen to assist on cases — cannot adequately fulfil their key objective. Instead, by surveying how the high courts in the United States and the United Kingdom treat interveners, the authors re-imagine the rules of intervention. While the proposed rules continue to be inclusive, they also provide interveners with greater opportunities to contribute to the development of the law and the framing of the issues. Specifically, the authors propose that the Court revise its screening policy in two ways: (1) any actor with relevant interests can file a factum (minimum of 20 pages); (2) only those interveners who provide distinct and helpful perspectives would be invited to make oral arguments, and given more than five minutes to make their arguments.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.272
Teacher spread0.260 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2019
Admission routes1
Has abstractyes

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