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Record W2908020660

Зарубежный опыт правового регулирования отношений в сфере оборота криптовалюты

2018· article· ru· W2908020660 on OpenAlexaboutno aff
Долгиева Мадина Муссаевна

Bibliographic record

VenueCyberLeninK (CyberLeninka) · 2018
Typearticle
Languageru
FieldSocial Sciences
TopicSecurity, Politics, and Digital Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsCryptocurrencyLatin AmericansChinaLegislationGovernment (linguistics)SanctionsBusinessInternational tradeEconomyGeographyPolitical scienceEconomicsLaw
DOInot available

Abstract

fetched live from OpenAlex

The article discusses the foreign experience of cryptocurrency regulation since the beginning of their widespread use on the example of the United Kingdom, the United States, Canada, Australia, Ukraine, Japan, China and Latin America countries. Most of the countries, such as Venezuela, the United States, Canada, Australia, some EU countries, as well as such financial and technological giants as China and Japan are positive-expectant concerning the status of cryptocurrencies. The neutral position of a number of countries (the European Union led by Germany, Latin American countries) is due to the lack of developed legislation regulating cryptocurrency relations. In Ecuador, Thailand, Vietnam, Iceland and Bangladesh cryptocurrencies are prohibited. Venezuela became the first country in the world to create its national cryptocurrency-Petro. Its value is sunstantiated by reserves of natural resources of the country, and the price equals to a barrel of oil. By Petro, the Venezuelan government expects to overcome the economic crisis caused by the USA sanctions and to attract billions of dollars in investments. Venezuela's national cryptocurrency is built on a blockchain platform. It can be used for payments in the country and exchanged for other cryptocurrencies. In Russia, international experience in the field of regulation of cryptocurrency relationships and determining its status resulted in early adoption of the law on the cryptocurrency and the possible emergence of a national cryptocurrency - cryptolabs.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.006

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 head0.039
GPT teacher head0.327
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2018
Admission routes1
Has abstractyes

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