Tax Discrimination and Trade in Services: The Search for Balance in Canada-U.S. Relations
Bibliographic record
Abstract
The trading relationship between Canada and the United States represents the largest bilateral flow of goods and services in the world. Notwithstanding this significant trade relationship and the obligations of non-discrimination assumed under trade agreements, both countries boast tax legislation that may negatively impact the competitive position of service providers of the other country. This article examines some of these tax measures and compares the tax treatment of nonresident service providers performing services in the other country to the tax treatment of domestic service providers. The article also considers the tax treatment of the domestic entity hiring the service provider. The article begins with a short overview of the commitments made in the World Trade Organization Agreement and in the North American Free Trade Agreement with respect to non-discrimination and, in particular, to most-favourednation treatment and national treatment. The article also presents the articles of the Canada-US. Income Tax Treaty that most affect cross-border service providers, including the recently signed Ffth Protocol that will have a significant impact. Selected provisions and administrative practices of Canadian and U.S. taxing regimes are then examined as to the potential impact on the competitive position of cross-border service providers. The article ends with a proposal to remove some of the current tax obstacles for service providers supplying services between Canada and the United States, and with a brief look at the broader question of whether more enhanced tax cooperation might better serve the needs of Canada and the United States in this area. This article will be of interest to those who advise cross-border service providers as well as to those with a broader interest in how tax and trade agreements potentially affect them.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".