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Record W6996018378

Principles of Canadian Income Tax Law, 10th ed.

2022· article· en· W6996018378 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTaxation and Legal Issues
Canadian institutionsnot available
Fundersnot available
KeywordsState income taxGross incomeConsumption taxIndirect taxIncome taxTax reformValue-added taxInternational taxationTax avoidance
DOInot available

Abstract

fetched live from OpenAlex

Principles of Canadian Income Tax Law is an introduction to Canadian income tax law using clear, concise, and non-technical language. As with previous editions, the emphasis is on the principles of income tax law, the policies that influence and underlie the system, basic technical schemes and landmark court decisions. Tax law is portrayed as a rational system that contributes to Canada’s socio-economic fabric. This new edition is significantly rewritten, including a new introduction chapter, a completely rewritten chapter on the General Anti-Avoidance Rule (GAAR) and substantially revised chapters on specific anti-avoidance rules (SAARs) related to income shifting and on income earned through intermediaries. It generally follows the structure of the Income Tax Act, starting with section 2 and ending with section 245 (the GAAR). Most chapters follow a common structure that includes an overview of the legislative scheme in terms of the basic rules, purpose, and rationale and key concepts and principles. Some practical problems are added to many chapters. Key statutory provisions are distilled to their essence and explained in simple language. The focus is on the “what” and the “why” aspects of statutory interpretation as well as the application of the rules to relatable (or “real life”) situations. This text comes with finding tools that save research time, including a detailed table of contents, an exhaustive table of cases and a comprehensive topical index. -- Publisher description.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.018
GPT teacher head0.224
Teacher spread0.206 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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