Bibliographic record
Abstract
Current Canada Revenue Agency (CRA) guidance suggests that cryptoassets (such as bitcoin) should generally be taxed as commodities for the purposes of the Income Tax Act. However, recent changes in the regulation of entities that facilitate the purchase and sale of cryptoassets (crypto trading platforms) under securities law have introduced new ways of understanding transactions involving cryptoassets. Many crypto trading platforms hold cryptoassets on behalf of users rather than delivering the cryptoassets directly to them, and the Canadian Securities Administrators has taken the position that this relationship among crypto trading platforms and their users itself constitutes a security. To date, there has been no guidance from the CRA relating to the taxation of these securities, which are known as "crypto contracts." This article considers potential income tax implications arising from the existence of crypto contracts by exploring how income taxation would differ for users of crypto trading platforms if they were taxed on crypto contracts rather than cryptoassets. Specifically, the article considers the treatment of transactions as being on income or capital account, the availability of elections to treat transactions on capital account, the applicability of section 49.1 of the Income Tax Act, and the income taxation of staking rewards earned through crypto trading platforms. Rather than offering conclusions on these topics, this article aims to provide a framework for thinking about crypto contracts from a Canadian income tax perspective and to provoke further thought from Canadian tax professionals.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.025 | 0.002 |
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".