LIMITATIONS AND EXCEPTIONS OF ECONOMIC COPYRIGHT: BALANCE OF PRIVATE AND PUBLIC INTERESTS
Bibliographic record
Abstract
The article is devoted to the research of the balance between private and public interests through the concept of exceptions and limitations on economic rights of author. The concept of free use of works applied in the legislation of Ukraine is analyzed, as well as exceptions and limitations on copyrights inherent in the copyright of the European Union. It is concluded that the concept of «free use» in the context of copyright is not used in the legislation of most countries of the world, and is inherent in the Ukrainian Law of Ukraine «On Copyright and Related Rights». Copyright limitations and exceptions in the specific cases are envisaged in the laws of different countries of the world by the following two main systems: a system of general abstract principles implemented in common law countries ('fair use' in the US and 'fair dealing' in the UK, Canada). The first approach is characterized by the fact that a generally exhaustive list of ways of free use of works is provided for in a legislative act and does not allow for the consideration of additional general principles. The second, implies that the court applies the general principles (first and foremost the principle of fair use) and pre-established criteria to determine the lawfulness of a use. The three-step test of the Berne Convention and its relevance to the copyright of Ukraine and the EU are being analyzed. The three-step test, as one of the means of ensuring a balance of private and public interest in copyright, can be used both in law-making and in court-specific dispute resolution. The different approaches to copyright exceptions proposed in the draft Wittem Group's copyright code are explored compared to those existing in the European Union Directive on the harmonization of certain aspects of copyright and related rights in the information society. It is noted that the draft Wittem Group's Copyright Code differs from that adopted in the EU and Ukraine in that it provides for an open list of cases of use of copyright objects, thereby altering the existing balance of interests towards the public. Copyright restrictions in the said Directive apply to specific proprietary rights under certain conditions, which may include the purpose, subjects and specific scope, which provides for a list of exceptions and restrictions that are considered to be closed and not subject to extended interpretation in their content.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.035 |
| Scholarly communication | 0.017 | 0.018 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".