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Record W2139402243 · doi:10.19030/iber.v13i3.8591

The Permanent Establishment Concept In Double Tax Agreements Between Developed And Developing Countries: Canada/South Africa As A Case In Point

2014· article· en· W2139402243 on OpenAlexaboutno aff
Lee‐Ann Steenkamp

Bibliographic record

VenueInternational Business & Economics Research Journal (IBER) · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTaxation and Legal Issues
Canadian institutionsnot available
Fundersnot available
KeywordsTax treatyDouble taxationTreatyDeveloping countryInternational taxationInternational economicsInternational tradeContext (archaeology)Tax reformDirect taxTax avoidanceEconomicsForeign direct investmentOrder (exchange)Value-added taxTax policyBusinessPublic economicsPolitical scienceEconomic growthLawMacroeconomicsFinanceGeography

Abstract

fetched live from OpenAlex

In this era of globalisation, developing countries have resorted to double tax agreements in order to attract foreign direct investment. The extent to which a countrys tax treaty policy favours developing countries or not depends upon the extent to which the country is prepared to adopt provisions from the UN model tax convention as opposed to the OECD model. Developing countries in particular should carefully consider the design of their tax treaties so as to effectively combat tax avoidance, without sacrificing foreign direct investment. To this end, the Canada/South Africa tax treaty is compared and contrasted with these two models. The concept of permanent establishment is reviewed in this context. It was found that the Canada/South Africa tax treaty is overwhelmingly based on the OECD model. This could indicate that South Africa has a deliberate tax treaty policy of ceding taxing rights to other countries. Thus, developing countries are seemingly unable or unwilling to make use of the UN model so as to retain greater source taxation. A number of recommendations are made to broaden the scope for the source taxation of business income in the developing country.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.897
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.309
Teacher spread0.254 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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