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Record W2256450146

The Minister's Burden Under GAAR

2006· article· en· W2256450146 on OpenAlexaffabout
Daniel Sandler

Bibliographic record

VenueSSRN Electronic Journal · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTaxation and Legal Issues
Canadian institutionsWestern University
Fundersnot available
KeywordsTaxpayerSupreme courtLawTax avoidancePrima facieTaxable incomePolitical scienceIncome taxEconomicsDouble taxation
DOInot available

Abstract

fetched live from OpenAlex

The long-awaited Supreme Court of Canada decisions in Canada Trustco and Mathew, described by some as the most important Supreme Court tax cases in a generation, have provoked significant discussion and controversy. This article examines one particular aspect of the guidelines provided by the Supreme Court in analyzing the application of section 245 (the general anti-avoidance rule [GAAR]): the minister's burden under GAAR. In setting out the three requirements for GAAR to apply - a tax benefit, an avoidance transaction, and abusive tax avoidance - the Supreme Court indicated that it is the taxpayer's burden to refute the first two, and the minister's burden to establish the third. While there is no specific burden imposed on the minister under the first two requirements, the author suggests that the assumptions upon which the minister's GAAR assessment is based must set out a prima facie case. The author suggests that the first requirement, a tax benefit, should not pose any difficulty for the minister, in light of the Supreme Court's interpretation of this term. In most cases, where the taxpayer has benefited from some deduction in determining income or taxable income, it is simply a matter of identifying that deduction. It is only in other cases - for example, where the tax benefit results from a deferral or a recharacterization of income - that the minister must identify an alternative arrangement for comparison. The second requirement, an avoidance transaction, similarly should not pose difficulties for the minister if the minister's arguments recognize and are shaped by a taxonomy of tax-avoidance transactions. The author suggests that all tax-avoidance transactions fit one of three fact patterns: substitutable transactions, tax attribute trading, and tax attribute fabrication. Within this taxonomy, all tax-avoidance cases should easily meet the first two requirements of a GAAR analysis; it is on the third requirement that the courts should focus. The minister should choose the appropriate cases to litigate accordingly. The third requirement in a GAAR analysis, abusive tax avoidance, involves both questions of fact and questions of law. The author suggests that in discussing subsection 245(4), the Supreme Court appears to confuse a litigant's, specifically the minister's, burden of proof - an evidentiary burden in questions of fact - with the court's obligation to answer questions of law. The author suggests that subsection 245(4) involves two distinct inquiries: the first, a question purely of law, is to interpret the legislative intent of the statutory provisions in issue; the second, a mixed question of fact and law, is to determine whether the avoidance transaction frustrates the legislative intent so established. In the author's view, it is inappropriate for the court to combine these two distinct inquiries into one overall inquiry involving a mixed question of fact and law. Furthermore, the author maintains that the minister has no burden of proof in the first inquiry. Legislative intent is a matter for the court to decide. Finally, given the important questions of law that must be considered in any GAAR case, the author questions the Supreme Court's obvious reluctance to hear further GAAR cases and its apparent admonishment of the Federal Court not to interfere with Tax Court decisions.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.672
Threshold uncertainty score0.660

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.016
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0110.008
Scholarly communication0.0110.002
Open science0.0020.004
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.007
GPT teacher head0.212
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2006
Admission routes2
Has abstractyes

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