PROBLEMS AND PROSPECTS OF THE DEVELOPMENT OF THE WORLD MARKET OF ORGANIC PRODUCTS IN THE CONDITIONS OF MACROECONOMIC INSTABILITY
Bibliographic record
Abstract
The purpose of the article is to study the current state, identify problems and prospects for the development of the world market of organic products in conditions of macroeconomic instability. The agricultural sector is recognized as one of the most key and dynamic sectors of the world economy. In particular, organic production is becoming a necessary link in ensuring sustainable and ecologically safe food. The rapid development of this sector is determined not only by national trends, but also by controversial processes at the international level. The main factors contributing to the growth of the organic products market have been identified, among which the following are highlighted: increased consumer awareness of healthy eating and environmental protection; the spread of organic certification, the growth of e-commerce and online platforms. The authors analyzed the current state of the world market of organic products. It was determined that the USA, Germany, France, China and Canada stand out among the countries that occupy leading positions at the world level in the production and consumption of organic products. A high level of consumption of organic products per capita is noted in countries such as Switzerland, Denmark and Luxembourg. The main problems of the instability of the development of the organic products market are outlined, namely: the increase in food prices due to inflation; the impact of geopolitical factors disrupting supply chains; an oversupply of organic products due to increased demand during the COVID-19 pandemic. In order to ensure food and environmental security, the governments of countries around the world support the production of high-quality and environmentally safe products in every possible way. The main current trends in the world market of organic products are: the growth of the price of organic products at a faster pace than for non-organic products; increasing innovation in organic farming; growth in the number of certified organic farms; increase in demand for certain segments of the product range (fruits and vegetables, baby food products); using artificial intelligence to track all stages of production and transportation of organic products.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".