Constitutional Litigation, the Adversarial System and Some of Its Adverse Effects
Bibliographic record
Abstract
The authors of this article identify and analyze a specific and spectacular failure of the adversarial system. Between 1988 and 1990, in the Mercure and Paquette cases, the Supreme Court of Canada held that Saskatchewan and Alberta were obliged to enact and publish their laws in both French and English, but that they could also unilaterally abrogate this obligation if they so decided. They did. Twenty years later, in the Caron & Boutet case, the Provincial Court of Alberta disrupted the state of the law by holding that judicial and legislative bilingualism was and had always been constitutionally protected in Alberta, and thus in Saskatchewan as well.In this article, the authors try to elucidate this puzzling contradiction. They identify some of the consequences that result from subjecting important public law questions to an unbridled adversarial system. They also highlight the dangers of determining major constitutional questions on the basis of historical evidence adduced by parties with unequal means and resources. Caron & Boutet serves as a case study to that end, offering a sobering illustration of the pitfalls of the adversarial system in constitutional cases that turn on the proper understanding of historical events. The first section of this article sets the stage by presenting and analyzing the most important aspects of the Mercure, Paquette and Caron & Boutet cases. The second section underlines some of the inefficacies of the adversarial system in Canada from an evidentiary perspective, and notes the near impossibility, for disadvantaged parties, to present an adequate and complete evidence record. The authors conclude by reiterating the extent to which trial judges are the gatekeepers of access to justice and by underscoring the important function of funding mechanisms such as advanced cost orders and government initiatives, such as the Language Rights Support Program.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.071 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".