The Supreme Court's 2012 Tax Cases: Formalism Trumps Pragmatism and Good Sense
Bibliographic record
Abstract
The Supreme Court of Canada released decisions in four cases in the 2012 year. We argue that each illustrates the Court's formalistic approach to interpreting tax legislation. Each of the following four cases is evaluated in turn. Canada v Craig relates to the circumstances under which a taxpayer can offset losses incurred in a farming business against income earned from a completely different source. Fundy Settlement v Canada required determining the residency of a trust for tax purposes. Canada v GlaxoSmithKline Inc. focused on the circumstances to be taken into account in determining an arm's-length price in the transfer pricing context. Finally, Calgary (City) v Canada, a goods and services tax issue, looked at whether a particular supply of good and services constituted a single supply or multiple supplies and whether a grant or subsidy was given for a public purpose or was consideration for a supply.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.025 | 0.019 |
| Scholarly communication | 0.029 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.016 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 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".