Legal problems of the use of orphan works in digital age
Bibliographic record
Abstract
The aim of this paper is to consider the mechanisms of legalization of use orphan works, based on a comparative analysis of the legal regulation in the United States, the EU and European countries; identify priority ways to reform and to develop proposals for improving copyright law in Ukraine. In the first section the concept of the orphan works and the circumstances which caused emergence of the orphan works are revealed. It has been established that the problem of orphan works mostly concerns works whose authors died and heirs cannot be found. In the second section the models of legalization of orphan works in the United States, Canada, the EU and European countries are analyzed and these interferences formed a proposal for Ukrainian legislation. In the third section the background of development of legislation of orphan works in Ukraine are studied. The neсessity to study the legal regulation of the United States, the EU and European countries in light of the recodification of the Civil law of Ukraine and seeking way of its renovation is substantiated. Developing effective mechanisms of using orphan works are stated to become relevant in the process of digitization of libraries’ collections and to have gained a new momentum in recent years. Its result has been provided open access to the works on the Internet.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".