Bibliographic record
Abstract
The article deals with international experience of the state regulation in countries with developed agriculture sector. Origins of the current practice of state regulation of agriculture in the United States are analyzed. It is shown that the basic mechanism of state support for farmers in the US is price controls on agricultural products using two types of "price support", target price and mortgage. The peculiarities of state regulation of grain market in Canada are investigated. It is revealed that a characteristic feature of the regulation is two-tier system of payment based on grain farmers practice initial and final prices. The features of state intervention into the food market in Greece, Spain and Portugal and modification of intervention methods after their accession to the European Union are analyzed. The evolution and main characteristics of state regulation of agriculture in the EU are researched. International experience of state control over the production of certain agricultural products through market regulations (documents which record marginal production and marketing of agricultural products required to meet the needs of the population of individual regions and exports) is characterized. The role of budget support for family farms in agricultural development in Switzerland and Australia is revealed. The role of administrative measures of state regulation of agriculture in the United States, Poland and the Czech Republic is determined. The volume of state subsidies for agriculture in Ukraine and the countries is analyzed .
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".