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Record W2293500716 · doi:10.14288/1.0088921

"Can't be nailed twice": avoiding double taxation by Canada and Taiwan

2009· article· en· W2293500716 on OpenAlexaboutno aff
Emily Hsiang-hui Lee

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTaxation and Legal Issues
Canadian institutionsnot available
Fundersnot available
KeywordsDouble taxationLabour economicsEconomicsBusinessPolitical scienceFinance

Abstract

fetched live from OpenAlex

Canada and Taiwan have not entered into a tax treaty. Consequently, because each jurisdiction uses different connecting factors, that is 'residence' in Canada and 'income source' in Taiwan, double taxation may occur for individuals subject to tax in both jurisdictions. With the increasing number of Taiwanese immigrants to and investors in Canada, double taxation is becoming a significant problem. A treaty is probably the most efficient mechanism to resolve the double taxation problem. However, the political issue is how can a nation (Canada) enter into a treaty with a jurisdiction (Taiwan) that it does not recognize as a nation state? Despite facing the same problem, on May 29, 1996 Australia signed a tax agreement with Taiwan concerning the avoidance of double taxation and the prevention of tax evasion. The Australia-Taiwan Tax Agreement is unique because it was signed by two private sector organizations rather than by the respective governments. Using the same mechanism, New Zealand and Vietnam have signed tax agreements with Taiwan as well. This thesis analyses the likelihood of Canada entering into a tax treaty with Taiwan. In so doing, it considers how double taxation arises, reviews the foreign reporting rules and argues that a tax treaty between Canada and Taiwan is desirable. The conclusion is that, theoretically and pragmatically, a tax treaty (or agreement) between Canada and Taiwan is possible and needed in order to relieve punitive double taxation and to facilitate bilateral economic and trading relations between the two jurisdictions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.007
GPT teacher head0.162
Teacher spread0.154 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venuecIRcle (University of British Columbia)Same topicTaxation and Legal IssuesFrench-language works237,207