TRANSFORMATION OF THE AGRARIAN POLICY OF RUSSIA: REORIENTATION FROM IMPORT SUBSTITUTION TO STIMULATING AGRICULTURAL PRODUCTS EXPORT
Bibliographic record
Abstract
The agrarian sector of Russia is operating under conditions complicated by sanctions imposed by the USA, Canada, EU countries, Australia and other countries, as well as counter embargo on supply of agricultural products, raw materials and foodstuffs from these countries. It required the realignment of the agrarian and food policy in order to implement the import substitution concept. But in 2016 the agrarian policy of Russia changed its direction -from import substitution to stimulating the export of agricultural products and food. The new agrarian policy of Russia is oriented toward making the Russian agriculture competitive in the world food market. And this requires higher effectiveness of the agrarian production. The aim of the research is to conduct an empirical analysis of regional agriculture models under the conditions of reorientation of the agrarian policy of Russia -from import substitution policy to stimulating the export of agricultural products. The basis for our research was the data of the Federal State Statistics Service, of the Ministry of Agriculture of the Russian Federation and of the Information System “SPARK-Interfax”. To complete the research tasks, we used the methods of multidimensional classification, comparative, statistic and cluster analysis, matrixing. The research involved several stages. First, we analyzed the agrarian policy of the Russian Federation, taking into account the impact of sanctions and countersanctions. Second, we studied the spatial unevenness of Russia’s agriculture. Then, we identified the regional agricultural models in 2015, when the agrarian policy of the RF changed its direction from import substitution to stimulating the export of agricultural products and food. Finally, we substantiated the necessity to adapt the agrarian policy of Russia to interregional specifics. This will stimulate further growth of efficiency in the agriculture of Russia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".