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Record W4382135593 · doi:10.3390/jrfm16070305

Model Framework for Consumer Protection and Crypto-Exchanges Regulation

2023· article· en· W4382135593 on OpenAlexvenueno aff
Aleksandr P. Alekseenko

Bibliographic record

VenueJournal of risk and financial management · 2023
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsnot available
FundersRussian Science Foundation
KeywordsCryptocurrencyBusinessHackerLaw and economicsLiabilityComputer securityCommerceEconomicsFinanceComputer science

Abstract

fetched live from OpenAlex

Cross-border insolvency of crypto-exchanges, cyber-risks, transnational character of activities with cryptocurrencies, and financial frauds on the Internet are among the key threats for individuals who use Bitcoin as an investment. Moreover, crypto-exchanges impose consumer agreements containing provisions limiting their liability for hacker attacks and other clauses promoting inequality in relations with investors. All the named obstacles highlight the vulnerability of unsophisticated individuals investing in digital assets and have pointed out the necessity to adopt an internationally recognized model of rules for crypto-exchanges, otherwise, it will be impossible to effectively protect the rights of investors engaged in the activities of intermediaries exchanging and keeping decentralized cryptocurrencies. The purpose of the study is to elaborate on the fundamentals for constructing an international legal framework protecting consumers from risks arising from the activities of crypto-exchanges dealing with decentralized cryptocurrencies. Based on the methodology of comparative legal study, this paper examines the judicial practice of various countries and the legislation of jurisdictions popular among crypto-exchanges. The research explores the nature of Bitcoin, describes the types of crypto-exchanges and discusses the main approaches to crypto-exchanges regulation. It argues that an international framework on crypto-exchanges should be based on understanding Bitcoin as a commodity which is situated in the place of crypto-exchange incorporation, licensing of crypto-exchanges, and self-regulation.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.759
Threshold uncertainty score0.182

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.244
Teacher spread0.225 · 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 teacher head, not a consensus.

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

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

Citations11
Published2023
Admission routes1
Has abstractyes

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