Bibliographic record
Abstract
This chapter examines the interpretive exercise under the Canadian GAAR, contrasting this interpretive exercise with ordinary interpretation under the textual, contextual and purposive (TCP) approach, and considering the way in which the object, spirit, and purpose of the relevant provisions is determined in order to decide whether an avoidance transaction is subject to the GAAR. The first part distinguishes the interpretive exercise under the GAAR from the TCP approach, explaining that ordinary interpretation under the TCP approach is rightly constrained by the text of the applicable provisions in a way that the interpretive exercise under the GAAR is not. The second part addresses the way in which the object, spirit, and purpose of the relevant provisions is interpreted, criticizing the “unified textual, contextual and purposive” approach adopted by the Supreme Court of Canada in Canada Trustco Mortgage Co.v. Canada, and arguing that separate inquiries into a misuse of specific provisions and an abuse having regard to provisions read as a whole is not only consistent with the Court’s admonition in Canada Trustco against judicial reliance on overarching or overriding policies that are not anchored in the interpretation of the relevant provisions, but mandated by the text of subsection 245(4).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.037 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".