СВІТОВІ ПІДХОДИ ДО ВИЗНАЧЕННЯ ПРАВОВОГО СТАТУСУ КРИПТОВАЛЮТ
Bibliographic record
Abstract
The article is dedicated to a research of the legal nature of cryptocurrencies. Approaches to definition of the legal nature of cryptocurrency in the different countries of the world are analysed. World approaches to definition of the legal nature of cryptocurrency, regulation of the activity connected with use of cryptocurrency, approaches to the taxation and licensing of activity in the sphere of a turn of cryptocurrencies are generalized. Legislative approaches to regulation of activity of ICO, definition of a concept of mining of the different countries of the world are analysed. The conclusion is drawn that the nature of cryptocurrency can be considered as a kind of property. The conclusion is also drawn that the cryptocurrency can be considered as goods and be a subject of the barter agreement. As for unification of positions concerning cryptocurrencies at the level of national regulation in the different countries of the world, they can be reduced in three groups. In some countries cryptocurrency and operation with them are directly forbidden (Bangladesh, Ecuador, China - for legal entities). For the majority of the countries regulation of cryptocurrencies is carried out at the level of the recommendations of regulators which have no binding character (at the federal level in the USA, in Germany, Norway). And at last, in some countries there is already a so-called fragmentary regulation of operations with cryptocurrencies (the State of New York in the USA, Great Britain, Sweden, Australia, Japan). Legislative requirements concerning the status of persons who carry out the activity connected with a turn of cryptocurrencies (Japan, the USA, Sweden) are established. Attempts at the legislative level to settle activity of ISO are made (Japan, Canada, the USA, Singapore, the bill in the Russian Federation). In some countries the concept of mining is also officially defined (Poland, Sweden).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.102 |
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; both teacher heads agree on what is shown here.
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".