"Economic substance": Drawing the line between legitimate tax minimization and abusive tax avoidance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The general anti-avoidance rule (GAAR) in section 245 of the Income Tax Act is about drawing a line between legitimate tax minimization and abusive tax avoidance. However, the GAAR does not provide guidelines for determining whether a particular transaction is legitimate or abusive. In this article, the author argues that economic substance is a useful standard for drawing the line. It is not only called for by Parliament through the enactment of the GAAR, it is also justified on theoretical grounds, and is consistent with the textual, contextual, and purposive approach to statutory interpretation. Moreover, the author argues, economic substance is the best method for balancing conflicting policy concerns in Canadian income tax law. The Supreme Court of Canada also recognized the relevance of economic substance in the recent Canada Trustco decision. However, economic substance is a relatively new concept in Canadian tax law. The article advances our understanding of this concept by addressing four questions: (1) Why should economic substance analysis be relevant in GAAR cases? (2) What does “economic substance” mean? (3) What are the relevant factors in determining the economic substance of transactions? (4) How can an economic substance analysis be applied in GAAR cases?
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it