Judgment and Opportunity: Decision Assignment on the McLachlin Court
Bibliographic record
Abstract
The workload of the Supreme Court of Canada is shared among the Court’s nine members, but is this sharing equal with respect to the writing of judgments? A simple count does not provide an answer because not all cases are equally important. This paper develops an objective measure of case importance—the Legal Complexity Index—and applies it to the cases decided by the McLachlin Court. It demonstrates that judgment-delivery opportunities for significant cases have not been shared equally, either overall or with respect to any of the major subdivisions of the caseload. Some judges enjoy the spotlight, while others are relegated to the margins. An assessment of the major correlates of this inequality—gender, seniority, and the “Chief Justice factor”—indicates that their combined impact poses a significant challenge for the Court. La charge de travail de la Cour supreme du Canada est partagee entre les neuf membres de la Cour, mais ce partage est-il egal pour ce qui est de la redaction des arrets? Un simple decompte ne donne pas la reponse, parce que tous les dossiers n’ont pas la meme importance. L’auteur elabore une mesure objective de l’importance des dossiers—l’indice de la complexite juridique—et l’applique aux affaires tranchees par la Cour presidee par la juge en chef McLachlin. Il montre que la redaction des decisions pour les dossiers de grande importance n’a pas ete partagee egalement, soit dans l’ensemble, soit pour ce qui est des grandes subdivisions du volume de travail. Certains juges sont en vedette tandis que d’autres sont relegues a l’arriere-plan. Une evaluation des principaux correlats de cette inegalite—sexe, anciennete et le « facteur du juge en chef »—revele que leurs incidences combinees representent un grand defi pour la Cour.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".