Policy Forum: Canada's Proposed Cryptoasset Legislation
Bibliographic record
Abstract
Cryptoasset miners verify and record transactions, maintaining the integrity and security of the blockchain network. The Department of Finance ("Finance") has recently proposed new Excise Tax Act (ETA) provisions regarding the goods and services tax (GST)/harmonized sales tax (HST) treatment of crypto mining. Under these proposed provisions, crypto mining activities provided to anonymous recipients will not be subject to GST/HST, but the crypto miners performing these activities will also not be eligible to recover any GST/HST paid on their business inputs (and thus will be forced to bear the brunt of the tax themselves). We believe that Finance's decision to tax what it can identify—the business inputs of Canadian crypto miners—is a roughly balanced but reasonable approach. Although Finance might be legitimately criticized as departing from Canada's decision to eliminate the cascading of tax found in the former origin-based federal sales tax, it seems impossible to administer a destination-based transactional tax such as the GST/HST when faced with "anonymous" recipients (the users of the crypto miner's services). Finance appears to have minimized the cascading of tax by including a carve-out for identifiable recipients of a crypto miner's services, allowing the regular zero-rating rules in the ETA to apply in limited circumstances. In the face of utter uncertainty, Finance's reactive approach is likely the best that it can do. Given the rapid evolution and inherent decentralization of the crypto space, a more broadly based proactive approach would seem imprudent at this time.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.018 | 0.005 |
| Scholarly communication | 0.018 | 0.004 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.044 | 0.012 |
| Insufficient payload (model declined to judge) | 0.047 | 0.007 |
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".