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Record W4223644085 · doi:10.32721/ctj.2022.70.1.ctp

Corporate Tax Planning: Choosing a Vehicle for Resource Business Ventures

2022· article· en· W4223644085 on OpenAlexvenueaboutno aff
Nicholas J. McIsaac

Bibliographic record

VenueCanadian Tax Journal/Revue fiscale canadienne · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsSuccessor cardinalBusinessNegotiationResource (disambiguation)Context (archaeology)Relevance (law)Income taxFinanceIndustrial organizationEconomicsPublic economics

Abstract

fetched live from OpenAlex

In the Canadian mining industry, it may be commercially beneficial for two or more corporations to undertake a business venture together to explore a resource property and subsequently develop and operate a mine. Four vehicles are commonly used to carry on such ventures: incorporated joint ventures, unincorporated joint ventures, general partnerships, and limited partnerships. This article highlights some of the income tax issues that must be considered when negotiating a choice of vehicle with an arm's-length party. The article focuses on key provisions of the Income Tax Act (Canada) that apply in the context of resource business ventures including, in particular, the flowthrough share, successor, at-risk, and tax shelter investment rules. The relevance and tax implications of these provisions are discussed, in turn, for each of the four vehicles, with a view to assisting the parties to the venture in making an informed decision.

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)0.003
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: none
Teacher disagreement score0.670
Threshold uncertainty score0.655

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.003
Scholarly communication0.0090.003
Open science0.0010.002
Research integrity0.0020.002
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 head0.054
GPT teacher head0.196
Teacher spread0.143 · 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
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 routes2
Has abstractyes

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