CRYPTO MARKET EXPERIENCE: Navigating Regulatory Challenges in Modern Conditions
Bibliographic record
Abstract
The legal regulation of digital finance is at an initial stage. It has been proven that many countries are favorable to the full or partial recognition of cryptocurrency as a means of payment, among them: Spain - the official payment system; Germany - monetary unit and form of private money; USA - currency, form of money, Sweden - contractual means of payment; the object of money transfers in certain states, Canada - a means of calculation, etc. It has been established that in Ukraine, the conservative nature of legal regulation of financial relations is considered in the context of implementing digital financial technologies given the task of protecting both public interests and the interests of individuals. Conclusions have been made, first, the issue of legal evaluation of cryptocurrencies is still not finally resolved and their legal nature also remains debatable; second, cryptocurrencies being alternative settlement units pose a threat to the dominance of public currencies, as they enable competition between private financial agents and states; third, according to its essence, electronic money is a kind of electronic promissory note.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.020 | 0.024 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".