WAYS OF CHANGING THE LEGAL REGULATION OF CRYPTOACTIVES: AN ANALYSIS OF FOREIGN EXPIRIENCE
Bibliographic record
Abstract
The proliferation of cryptocurrency transactions and the increase in their value raises the question of the need for a final solution to the problem of legal regulation of their circulation. The urgency of this task is exacerbated by the fact that leaving cryptoassets out of the legal field promotes their use in illegal activities and deprives the state of significant revenues from their proper taxation. The purpose of this article is to study the approaches to the legal regulation of the circulation of cryptoassets, which are recently formed in the world, to determine the positive experience and opportunities to borrow successful legislative decisions. The article analyzes approaches to the regulation of relations arising from cryptocurrencies in the United States, Canada, Great Britain, Germany, Austria, Estonia, China, Singapore and Australia. Particular attention is paid to the analysis of the European unified approach to the regulation of cryptocurrencies for all European countries, as well as cryptocurrency services. According to the results of the study, it is concluded that today the attitude to cryptocurrencies differs depending on the level of development of the country. However, recently there has been a tendency to focus efforts on the implementation of cryptoassets in the legal field and ensure legal regulation of their circulation. In general, 2020, the year of the pandemic and the transfer of life to the online format, was marked by special attention to the development of legal regulation of cryptocurrency circulation. Of particular concern to the authorities are features of cryptocurrencies such as decentralization and anonymity, which allow these assets to be used to launder criminal proceeds and finance terrorism. It is in this direction that government regulation of cryptocurrency circulation has been moving recently. Most countries in the world of cryptocurrency regulation focus on licensing cryptocurrency exchanges, identifying their users, taxing, and countering money laundering and terrorist financing. These principles are the basis of the unified approach to the regulation of cryptocurrency activities for all European countries proposed by the European Commission. It is noteworthy that both in the European unified approach to the regulation of cryptoassets and in their legal regulation in some European countries and the United States, it is proposed to classify cryptocurrencies and divide them into several categories depending on the functions they perform. These approaches to the classification of cryptoassets should be considered when determining the legal framework for regulating the circulation of cryptoassets (virtual assets) in Ukraine.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".