Economic and Legal Mechanisms of Interstate Support for Agricultural Producers
Bibliographic record
Abstract
The transitional stage in the agrarian economy requires an optimal combination of state protection and market levers. At present, the state regulatory influence on the development of agriculture remains, on the one hand, quite significant, and on the other, insufficiently effective. There is no systemic integrity in the practice of state regulation of the agricultural sector. The relevance of the study is that in transition economies, agrarian protectionism was initially caused by somewhat different circumstances, and the protectionist policy was formed in fundamentally different conditions. The authors demonstrate that protectionism in industrial-type transition economies inherited a huge mechanism of state support for the agro-industrial complex in the depths of a centrally planned economy. Everywhere this support constituted a heavy burden of national finances, and one of the primary tasks of reforms in transition economies, including agrarian reforms, was precisely the release from this burden. It causes sharp liberalization of agrarian policy in almost all countries. The method of analysis was used to investigate the main directions, methods, and mechanisms of state regulation of the economy in different countries; the priority areas of state regulation of prices in the agro-industrial complex industry were highlighted. The practical significance of the study is that macroeconomic reforms in countries with an industrial type of development led to a rapid deterioration in the financial situation of the agricultural sector.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".