Bibliographic record
Abstract
Organic agriculture is a promising and increasingly demanded direction of “greening” agricultural activity, which has a great potential due to natural production technologies. Significant segments of organic products have been formed in the food markets of the developed countries; various institutional systems of the industry have been functioning for decades. Russian agribusiness is globally lagging behind in these matters, but the development of the economic environment has led to the objective necessity of adopting a law and a state standard that would define the requirements for the organic agriculture. Research on the prospects of the Russian food market in the global organic production system is becoming relevant. This work is a two-sided quantitative and qualitative approach to the study of existing production systems of organic food from the standpoint of the results and dynamics, on the one hand, and their organizational and economic structure, on the other. The findings and results are confirmed by the presented and systematized absolute and relative indicators of land areas certified for organic agriculture, the number of market entities, the consumption of organic food per capita and retail sales in the domestic markets. The qualitative characteristic of organic agriculture systems was reflected in constructing a set of schemes that clearly illustrate national features of the conduct methods, state regulation of production and turnover, research support, regulatory and supervisory support of the business under study. As a result, a comparative analysis of the leading world markets for organic food (USA, Germany, Canada and Austria) in comparison with the emerging market of Russia. The study is addressed to the global business community operating in the organic food market and to special research institutions.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".