"Can't be nailed twice": avoiding double taxation by Canada and Taiwan
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".