Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The rapid development of information technologies, the globalization of the world economy, and the formation of a digital economy in Ukraine lead to the transformation of socio-economic relations. The growth of digitalization of the economy, the large-scale introduction of information technologies into all spheres of human life contribute to the emergence of new industries, one of which is the crypto industry, with the appearance of which in 2008, the money market totally changed forever. More and more markets are collapsing, while more and more regulators from different countries are busy implementing legislation regarding the legalization, use and taxation of cryptocurrencies. The article is devoted to the study of the peculiarities of cryptocurrency legalization in Ukraine. The peculiarities of the law “ Pro virtualʹni aktyvy” and the stages of its implementation are considered. The draft law on amendments to the Tax Code of Ukraine regarding cryptocurrency taxation has been analyzed. The number of cryptocurrency users in Ukraine and other countries of the world, such as the USA, Venezuela, Kenya, North Africa, etc., was studied. The paper analyzes how countries such as Great Britain, the Netherlands, the USA, China, Japan and Canada regulate the cryptocurrency market and whether transactions with them are legalized at the legislative level. Conclusions were also made regarding the feasibility of legalizing cryptocurrency in Ukraine.So far, we have the Law, but for the final settlement of these issues, many different by-laws, instructions and documents still need to be developed. But already today it can be said that the State is dealing with the issue of cryptocurrency relations and is on the way to its settlement.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it