GAAR in Action: An Empirical Exploration of Tax Court of Canada Cases (1997-2009) and Judicial Decision Making
Bibliographic record
Abstract
This article presents a modest, exploratory empirical study of Canada's general anti-avoidance rule (GAAR) in action. The study examines the entire body of GAAR cases decided by the Tax Court of Canada in the period 1997-2009, as well as certain personal and societal attributes of the judges who decided these cases. The findings support three tentative conclusions. First, GAAR has been a game changer, albeit a modest one, with respect to the courts' approach to tax-avoidance cases. Second, while considerable uncertainty remains with respect to the application of GAAR, a pattern in judicial decisions appears to be emerging. Third, there are indications that a judicial smell test is at play in some GAAR decisions; in particular, judicial decision making in GAAR cases appears to have been influenced by the judge's attributes, including experience on the Tax Court, gender, preappointment experience, and regional ties. Because the data sets examined in the study are very small, these findings are by no means conclusive. Nevertheless, the hope is that they will help to advance empirical understanding of GAAR in action.
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| 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".