Carrying on the Tradition: Justice Rothstein's Contribution to Canadian Tax Law
Bibliographic record
Abstract
In this article, we review a selection of Justice Rothstein’s tax judgments with the object of making two observations about his contribution to Canadian tax law. First, Justice Rothstein, who was appointed to the Supreme Court two years after Justice Iacobucci retired, and in many ways stepped into his shoes as the Court’s tax judge, continued Justice Iacobucci’s formalist tradition. We provide evidence of Justice Rothstein’s formalist approach by examining one case he rendered while serving on the Federal Court Trial Division, Neuman; and two cases that were decided when he sat on the Federal Court of Appeal, Singleton and Stewart. Each of these cases was appealed to the Supreme Court. We also review one case rendered while he was sitting on the Supreme Court, Craig.\nOur second point is that Justice Rothstein’s tax decisions illustrate why he was so widely admired as a judge. They are well written and technically competent. They are always well organized and free of jargon. They often refer to and engage with the relevant academic literature, they are closely reasoned, and they deal straightforwardly with the arguments, as he sees them, on both sides of the issues. He wrote many leading judgments, but in one area in particular, the application of the General Anti-Avoidance Rule (GAAR), he wrote the first appellate court judgment while serving on the Federal Court of Appeal (the provision was enacted in 1988). This decision guided courts for a number of years. While on the Supreme Court he continued his work in this complex area of law and his judgments at the Supreme Court have laid the foundation for the future development of the rule. A review of Justice Rothstein's GAAR decisions supports our second point.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.026 | 0.022 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".