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Policy Forum: Canada's Proposed Cryptoasset Legislation

2023· article· en· W4366569685 on OpenAlexvenueaboutno aff
Robert G. Kreklewetz, Laura J. Burlock

Bibliographic record

VenueCanadian Tax Journal/Revue fiscale canadienne · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsExciseFinanceLegislationBusinessTax reformGoods and servicesEconomicsPublic economicsLawPolitical scienceEconomy

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.026
GPT teacher head0.202
Teacher spread0.175 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes2
Has abstractyes

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Same venueCanadian Tax Journal/Revue fiscale canadienneSame topicTaxation and Compliance StudiesFrench-language works237,207