Some Aspects of Harmonisation of Ukraine’s Competition Legislation to EU Standards
Bibliographic record
Abstract
In modern conditions, obtaining information about market dynamics, trends in demand, and alternative offers from competitors is vital to support the effective operation of enterprises. It is also common business practice to discuss legislative initiatives, non-confidential technical information, quality and safety standards, and various aspects of the industry. However, the direct or indirect exchange of information may be accompanied by various wrongful intentions of economic entities (for example, elimination of competitors, creation of entry barriers, agreement on price levels, certain discounts, sales volumes, and the market's geographical distribution, etc.). In Ukraine, there are currently no analogues of a full-fledged guide to information exchange between competitors, which determined the relevance of this study. The purpose of the study is to establish regulatory, economic principles for assessing the exchange of information between enterprises operating in the relevant market, in the context of compliance with legislation on protection of economic competition; analysis of the progressive international practice of cessation of violations in the form of information exchange, which leads to distortion of economic competition. In Ukraine, it is necessary to adopt the Guidelines for the Exchange of Information between Competitors (from now on referred to as "the Guidelines"), raising awareness of the business community (including associations and chambers of commerce), lawyers, and society in general regarding the main aspects of the competition compliance with competition law in order to promote fair business activities, protect the competitive environment and, as a consequence, improve consumer welfare.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".