Legal Control Over Copyright Protection Using Blockchain Technology
Bibliographic record
Abstract
The development of digital information technologies predetermined the need to develop technical and legal mechanisms of copyright protection. Now the share of copyright in the national economies of most countries is very significant and continues to grow, the main task of national legal systems is to find and implement technical and legal solutions to protect copyright from digital piracy. One of these solutions is block chain technology. The relevance of the research topic rests at the novelty of this technology and the lack of study of issues in the field of theory and law enforcement related to the adaptation and legitimation of relations using block chain technologies, including in the field of copyright protection. The purpose of this article is to analyze the legal qualifications of block chain technology and its application in the field of copyright protection, legitimization of relations associated with the use of block chain technologies in the field of copyright protection. The study revealed that the block chain has features that allow for classification of this technology as a type of technical means of copyright protection, which is the theoretical significance of this study. It has been established that in the field of copyright protection, the block chain performs the function of fixing and confirming the legitimacy of ownership by the author or other right holder of the corresponding work, and provides control over access to the work during authorized use. In the course of the study, the authors assessed the provisions of the current procedural legislation for the use of block chain technologies as evidence in court proceedings for copyright protection and revealed that information from the block chain, including those confirming authorship, can be recognized by the courts as evidence.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".