Bibliographic record
Abstract
The article is devoted to the study of the most significant features of the terms of wrap license agreements. In the domestic civil law science, the outlined topics are not properly developed. At the same time, the process of Ukrainian Civil Law recoding, attempts to reform both the Contract Law general principles and the provisions on disposal of intellectual property rights agreements, as well as globalization and European integration processes strengthening require intensification of scientific efforts. The author considers the features of wrap license agreements that directly affect their content. The contract theory and practice of the USA, Canada and the United Kingdom in the relevant field are analyzed and generalized. On this basis, the subject of wrap license agreements is formulated as the permission to use the objects of copyright and (or) related rights. It is proposed at the Civil Code of Ukraine level to consolidate the possibility of granting only non-exclusive licenses under the studied agreements. It is emphasized that under these agreements only the right to use the object of intellectual property rights could be provided. It is proved that the use of the object of copyright and (or) related rights for functional purposes coexists with its proper legal use. It is pointed to the need to ensure the possibility of temporary use of such an object outside Ukraine, if there is no term concerning the territory in the agreement. It is noted that when the licensor establishes the auto-prolongation of wrap license agreements, the licensee must be duly warned about this and provided with a transparent possibility to refuse the prolongation. The importance of establishing the non-paid presumption of wrap license agreements is substantiated. The most common in the software and databases mass markets payment models for the use of copyright and (or) related rights are named. Finally, it is concluded that it is necessary to conduct further research of the wrap license agreements and to enshrine them into the civil legislation of Ukraine.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".