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Record W3122505542 · doi:10.1353/tlj.2007.0004

The Reasonable Justice: An Empirical Analysis of Frank Iacobucci's Career on the Supreme Court of Canada

2007· article· en· W3122505542 on OpenAlexvenueaboutno aff
Benjamin Alarie, Andrew Green

Bibliographic record

VenueUniversity of Toronto Law Journal · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSupreme courtLawEconomic JusticePoliticsSociologyVotingPolitical science

Abstract

fetched live from OpenAlex

There are two widely shared views of Frank Iacobucci as a justice of the Supreme Court of Canada. The first is that he was a liberally inclined justice, particularly in the area of criminal law. That he has conventionally been regarded as a liberal despite being appointed in 1991 by the Progressive Conservative prime minister Brian Mulroney raises a number of questions. Is this conventional view of Justice Iacobucci actually correct? That is, is it borne out by his voting record over his more than thirteen years on the Court? If so, does this 'left of centre' claim hold fast beyond criminal law and extend to other areas of law? The second image of Justice Iacobucci is as a justice committed to building consensus on the Court by encouraging his fellow justices to reach agreement with him and with each other in deciding appeals. This second view also raises a series of questions. Was Justice Iacobucci the 'swing' justice on the Court in that the other justices needed to have him onside to form a winning coalition? Alternatively, was he part of a natural coalition on one side of most issues and able to persuade other, disinclined justices to join his view? Did his relative position on the Court shift depending upon the area of law at issue? Did Justice Iacobucci's leanings or preferences change over time? This article addresses these and other related questions using an empirical analysis of Justice Iacobucci's time at the Supreme Court of Canada.

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 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 score0.932
Threshold uncertainty score0.999

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.269
Teacher spread0.243 · 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

Citations16
Published2007
Admission routes2
Has abstractyes

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