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Record W2258357073

Retroactivity and the General Anti-Avoidance Rule

2007· article· en· W2258357073 on OpenAlexaboutno aff
Benjamin Alarie

Bibliographic record

VenueTSpace (University of Toronto) · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTaxation and Legal Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPresumptionLegislationLawSupreme courtPolitical scienceLaw and economicsSociology
DOInot available

Abstract

fetched live from OpenAlex

The General Anti-Avoidance Rule (the GAAR) was originally introduced in Canadian income tax law in 1988 with prospective effect. The GAAR was amended in May 2005 to broaden its scope (by bringing under its ambit the regulations, treaties, etc.) and to lessen the burden of persuasion faced by the Minister in the misuse or abuse demonstration. What is peculiar about this amendment is that it was explicitly stated to have retroactive effect to the date the GAAR was first in effect - September 12, 1988. This chapter discusses the retroactive nature of the amendment of the GAAR. It proceeds in three stages. First, it provides an account of the relevant law surrounding the effectiveness and applicability of retroactive legislation in Canada, outlining the general presumption against retroactive legislation and addressing how express terms can override this presumption in many (but not all) contexts. Particular attention is paid to how Canadian courts have approached the application of retroactive enactments to pending proceedings. Second, this background is used to evaluate the Supreme Court of Canada's handling of the amendment of the GAAR in its first GAAR judgment (Canada Trustco). Finally, the chapter closes with a discussion of the policy underlying retroactivity and the GAAR more generally, suggesting that so long as retroactive fiscal legislation is possible (as it is in Canada) it is somewhat curious that so much reliance is placed on the GAAR. Enacting retroactive specific anti-avoidance rules (perhaps with a penalty) is possible and, from a policy perspective, arguably more effective and desirable at curbing aggressive tax avoidance.

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)0.010
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.509
Threshold uncertainty score0.988

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0080.023
Scholarly communication0.0100.004
Open science0.0040.005
Research integrity0.0050.011
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 head0.011
GPT teacher head0.221
Teacher spread0.210 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2007
Admission routes1
Has abstractyes

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