Policy Forum: Sailing Beyond the Sunset? Are De Jure Control and Other Bright-Line Tests Relevant After Deans Knight and the New GAAR?
Bibliographic record
Abstract
This article takes readers on a voyage through the Supreme Court of Canada's decision in Deans Knight Income Corp. v. Canada and subsequent cases that apply its interpretation of the general anti-avoidance rule (GAAR). The author draws on metaphors from Greek philosophy and sailing to aid—and lighten—the discussion of the immortality of corporations, bright lines, and the Income Tax Act. The author argues that the majority of the Supreme Court in Deans Knight committed a "purpose error": in applying GAAR, the majority overemphasized subsection 111(5)'s primary purpose of stopping corporate loss trading at the expense of the legislation's other purposes, including providing certainty to public companies with high shareholder turnover. Future cases decided under the amended GAAR may be even more vulnerable to a purpose error. The author then considers whether other bright-line tests in the Act are vulnerable to the same sort of purpose error if GAAR is applied. For example, he examines whether the 30-day time limit in the Act's stop-loss rules could be abused by waiting an extra day to comply with the rule, whether waiting one more day to sell a house could abuse the "flipped property" rules in subsections 12(12) to (14), and whether buying one more share to meet an ownership threshold could abuse part IV or section 113. While each of those strategies could arguably be abusive under the approach taken in Deans Knight, it would be an error to always interpret the rules so broadly. Courts should consider Parliament's purpose in using a bright-line test before applying GAAR, and ask how arbitrary and potentially manipulable the line is.
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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 | 0.032 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.023 |
| Scholarly communication | 0.021 | 0.010 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.034 | 0.020 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".