COMPARATIVE ANALYSIS OF STATE SUPPORT FOR AGRICULTURE OF UKRAINE WITH SOME FOREIGN COUNTRIES
Bibliographic record
Abstract
In this article it was found that the importance of agricultural development is due to the direct impact of this area on the living standards of citizens, which largely depends on the welfare of the population, including per capita income and social living conditions. It is proved that providing organizational, legal and economic measures for sustainable development of agricultural production will provide an opportunity to increase production of relevant products, improve its quality and safety, and, consequently, its competitiveness, both domestically and internationally. It is analyzed that despite the focus on the development of other sectors of the economy, in particular, technology, in most developing countries much of the territory is occupied by the agro-industrial sector, and among the population from 70 to 90% are employed in agriculture. Therefore, it was proved that the development of agriculture will always be relevant and require attention from scientists in various fields of science. This article noted that the structure of the agricultural sector, as well as the specific set of mechanisms of state regulation in different countries is different. At the same time, it is noted that some countries seek intensive development of this sector of the economy, while others suffer losses. In the presented article we have analyzed the current state of agriculture in Ukraine and identified problems that stand in the way of its development; In order to solve the existing problems, the experience of advanced foreign countries, including the United States, the European Union, Canada and Japan, was analyzed, and the factors due to which these countries managed to achieve stable growth in agriculture were identified. Based on the research, practical recommendations were provided, which we propose to take into account in the formation of state regulation of the agricultural sector in 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".