RESEARCH OF THE NATIONAL ORGANIC AGRICULTURE SYSTEMS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 it