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Record W3124335097 · doi:10.60082/2817-5069.3291

Strategic Behaviour and Leadership Patterns of Modern Chief Justices

2018· article· en· W3124335097 on OpenAlexvenueaboutno aff
C. L. Ostberg, Matthew E. Wetstein

Bibliographic record

VenueOsgoode Hall law journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDissenting opinionSupreme courtVotingCharterScholarshipRoberts CourtPolitical scienceIdeologyPeriod (music)Economic JusticeLawTask (project management)Majority opinionSociologyManagementPoliticsEconomics

Abstract

fetched live from OpenAlex

This study uses strategic behaviour, leadership change, and feminist theories to examine patterns of judicial activity by the three post-Charter chief justices of the Supreme Court of Canada. Building on prior scholarship, we use various methods to examine patterns of majority voting, dissenting activity, opinion writing, ideological voting, and panel size across the 1973 to 2014 period. While Chief Justices Lamer and Dickson exhibited clear patterns of task leadership, we find strong evidence of strategic change by Chief Justice McLachlin following her elevation to chief. She moved from a prolific dissenter as a puisne justice to a chief who exhibited behaviour of both a task leader and a social leader, which scholars see as highly uncommon. Her efforts to solidify her central role as a collegial leader within her own court, which took place during a period of increasing panel sizes and a shrinking court docket, are remarkable.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.291

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.149
GPT teacher head0.318
Teacher spread0.169 · 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 designObservational
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
Published2018
Admission routes2
Has abstractyes

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