Development of rural areas in Ukraine through the prism of experience of developed countries: ecological and social aspects
Bibliographic record
Abstract
The peculiarities of rural development of developed countries are studied and it is established that the governments of developed economies, in particular USA, Canada, China, EU countries, Japan, seek to create effective mechanisms for sustainable (ecologically balanced) rural development, promote rural national traditions, change the quality of thinking and the way of life of the rural population. The main problems of rural development of Ukraine in terms of social and environmental aspects are highlighted. Although the problem of land degradation remains relevant, there is no effective mechanism to address it, including through a subsidy program that would address the national code of sustainable agricultural practices. The solution of these problems necessitates the development of a radically different approach to substantiate the provisions of agricultural policy of the state in terms of increasing the profitability of business entities in the agricultural sector of Ukraine and the sustainability of socio-ecological and economic development of rural areas. residents of rural areas. The directions of improvement of development of rural territories in Ukraine, taking into account ecological and social aspects of experience of the developed countries are revealed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".