Ensuring Food Security of Ukraine in the Conditions of Globalization Dimensions
Bibliographic record
Abstract
The purpose of this article is to develop a model that implements the interaction of food security processes through the resource capacity of regions for self-sufficiency in the identification of threatening factors influencing its reproduction.Methodological support for assessing the food security of the country, which on the basis of targeted analytical studies of its domestic needs, reveals interregional relationships between the volume of its own agricultural production and the factors of import dependence of the state on world markets.Sub-indicators and food security indicators have been identified.Methods of research of food security of the country are substantiated.The level of self-sufficiency of food of Ukraine in agricultural and food products in the administrative centers of the country is calculated.The ratio of production and consumption of agricultural products and food products in Ukraine is substantiated.The ratio of imports to market capacity in the country is given.Partial indicators and integrated risk factors for loss of food security of Ukraine have been established.Predicted indicators of food security by land potential of agricultural production of the country, as well as its dependence on cattle, the level of self-sufficiency in fruits and berries, grain production and consumption are calculated.It is proved that given the strengthening of openness of the national economy, expansion of domestic and foreign agri-food markets, as well as European integration intentions of Ukraine, its level of food security should be carried out in the context of simultaneous evaluation of economic and social indicators and effective management.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".