The Reasonable Justice: An Empirical Analysis of Justice Frank Iacobucci's Career on the Supreme Court of Canada
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.031 | 0.010 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".