Agrarian insurance in Russia: condition, difficulties, and ways of their overcoming
Bibliographic record
Abstract
The article discusses the history of the development of state support for the agrarian producers sector in Russia and, in particular, the federal system of subsidizing agrarian insurance. It is shown that the main problems that violate the further progressive development of the agrarian insurance market are the destabilization of subsidies, the prevalence of compulsory insurance elements, the imperfection of legal support of insurance business and taxation of insurance activities, the decrease in the solvency of the population, the lack of clarity of state policy, and insufficient insurance culture of agrarian producers. The main directions of the development of agrarian insurance are proposed, one of which is the development of pilot projects for agrarian income insurance. It was analyzed on the experience of agrarian producers insurance in the USA and Canada, which led to the identification of the most critical factors that must be taken into account when developing the structure of income insurance. It is concluded that the essential factors in the development of agrarian insurance are the availability of the necessary volume of data on prices and the level of productivity in the region and sufficient support from the state.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".