MétaCan
Menu
Back to cohort
Record W4291237217 · doi:10.1093/publius/pjac033

From the Ivory Tower to the Courtroom: Cooperative Federalism in the Supreme Court of Canada

2022· article· en· W4291237217 on OpenAlexaffabout
M. Harding, Dave Snow

Bibliographic record

VenuePublius The Journal of Federalism · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSupreme courtFederalismLawPolitical scienceNew FederalismSupreme Court DecisionsMajority opinionTerm (time)JurisdictionConstitutionSeparation of powersOriginal jurisdictionGovernment (linguistics)Politics

Abstract

fetched live from OpenAlex

Abstract This article provides the first exhaustive quantitative account of the Supreme Court of Canada’s use of the term “cooperative federalism.” We find that cooperative federalism has appeared in twenty-four Supreme Court decisions from 1976 to 2019, and that these decisions have been more likely to favor the federal government than the provinces. Moreover, the Court’s use of the term can be divided between two distinct periods. During the formative period (1976–2009), the Court used the term fairly consistently. From 2010 to 2019, the Court has entered a contested period characterized by split decisions in which the Court is divided over differing conceptions of federalism. As cooperative federalism has transformed from a relatively vague concept into a more substantive constitutional principle, fissures over the term’s application have developed. This article shows how scholarly terminology can have an unexpected and even dispositive effect on judicial decisions, which can reflect uncertainty over how judges understand their institutional role.

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)0.005
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.199
Threshold uncertainty score0.929

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0300.020
Scholarly communication0.0140.003
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.027
GPT teacher head0.269
Teacher spread0.242 · 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 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

Citations2
Published2022
Admission routes2
Has abstractyes

Explore more

Same venuePublius The Journal of FederalismSame topicJudicial and Constitutional StudiesFrench-language works237,207