Policy Forum: The GST/HST Obligations of Non-Resident E-Commerce Firms—Jurisprudence and Policy
Bibliographic record
Abstract
E-commerce presents a broad range of challenges for policy makers. In the tax context, it has the potential to obscure the relationship between a firm and the appropriate taxing jurisdiction. This article explores the goods and services tax (GST)/harmonized sales tax (HST) obligations of non-resident e-commerce firms with no physical presence in Canada—specifically, whether those firms may be required to register for, collect, and remit GST/HST in respect of their activities in the Canadian market. Recent developments in the common law (albeit in a non-tax context) indicate that non-resident e-commerce firms with no physical presence in Canada may be found to be carrying on business in Canada. Since carrying on business in Canada is a key element in determining a person's GST/HST obligations, it is likely that non-resident e-commerce firms that are found to meet the requirement will be subject to such obligations in respect of taxable supplies made digitally in the Canadian market. That said, there is at present a great deal of uncertainty about the specific factors to be used in determining whether the activities of a non-resident e-commerce firm are sufficient to meet the carrying-on-business threshold. The author of this article recommends that Parliament should address this uncertainty by amending the Excise Tax Act to deem non-resident e-commerce firms to be carrying on business in Canada if they exceed specific de minimis sales thresholds.
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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 | 0.018 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.012 |
| Scholarly communication | 0.021 | 0.010 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.071 | 0.027 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".