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Record W2316239106 · doi:10.1017/s0008423911000151

Explaining Dissent on the Supreme Court of Canada

2011· article· fr· W2316239106 on OpenAlexaboutno aff
Donald R. Songer, John Szmer, Susan W. Johnson

Bibliographic record

VenueCanadian Journal of Political Science · 2011
Typearticle
Languagefr
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDissentSupreme courtPolitical scienceHumanitiesAmbiguityLawPoliticsPhilosophy

Abstract

fetched live from OpenAlex

Abstract. While there is an extensive literature on the causes of dissensus on appellate courts in the US, few empirical studies exist of the causes of dissent in Canadian Supreme Court. The current study seeks to close that gap in the literature, proposing and then testing what we call a Canadian model of dissent. We find that the likelihood of dissent is strongly related to four broad factors that appear to exert independent influence on whether the Court is consensual or divided: political conflict, institutional structure, legal ambiguity in the law and variations in the leadership style of the chief justice. Résumé. Les causes de dissension dans les cours d'appel aux États-Unis font l'objet de nombreux articles et publications, mais il existe très peu d'études empiriques sur les causes de dissidence à la Cour suprême du Canada. La présente étude vise à combler cette lacune en proposant, un modèle canadien de dissension, puis en le mettant à l'épreuve. Nous avons constaté que le risque de dissension est fortement lié à quatre facteurs genéraux qui semblent exercer une influence indépendante, que la Cour soit en accord ou divisée. Ces facteurs sont le conflit politique, la structure institutionnelle, la présence d'une ambiguité juridique dans la loi et le style de direction du juge en chef.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.010
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.274
Teacher spread0.209 · 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.

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

Citations22
Published2011
Admission routes1
Has abstractyes

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