Theoretical and Practical Aspects of Counteracting Unfair Competition and Violation of Antimononpoly Laws
Bibliographic record
Abstract
Competition allows business entities to implement projects that can subsequently ensure the development of the socio-public system and the country as a whole. At the same time, an opportunity for personal development is also achieved for a business entity. At the same time, any activity aimed at increasing profitability and market share leads to the emergence of new market participants that can help destabilise the industry or bring innovations to it. This allows the implementation of scientific and technological progress due to the competition mechanism. The novelty of the study lies in the fact that unfair competition is understood only as an element of violation of economically sound norms for entrepreneurial activity. The authors consider the competition of bona fide type as an element of the formation of saturation of the commodity market. Moreover, the state is considered not only as a source of antimonopoly legislation, but also as a factor in the implementation of the principles of competition in the interests of society as a whole. The practical significance of the study is determined by the possibility of structuring the requirements for competition law on the basis of independent regulation and the additional use of judicial and restrictive measures to spread the practice of competition in any sector of the national economy.
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 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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.051 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".