Assessment of the impact of the Russia’s war on the development of foreign trade in goods in the urbanized territories of Ukraine
Bibliographic record
Abstract
The article reveals the problems that arose in the field of foreign trade policy formation and implementation as a result of the Russian invasion of the territory of Ukraine. Foreign trade is one of the components of the formation of the national economy, and its state affects the gross national product, the country's balance of payments and other socio-economic indicators of the country's development. Using the methods of analysis and synthesis, comparison and generalization, an analysis of the commodity and geographical structure of foreign trade in goods was carried out before and after the full-scale invasion of Russia into the territory of Ukraine. The consequences of the changes that occurred in the structure of export-import operations were analyzed. Reduction of export and import volumes for almost all groups of goods and reduction of shares of all regions of the world in favor of EU countries. The leading place in the product structure of exports is occupied by goods of agricultural industry, and in imports – mineral products. The directions for the formation of state policy in the field of regulation of foreign trade operations in the short-term, medium-term and strategic dimensions, which are determined by the National Council for the Recovery of Ukraine from the Consequences of the War, are substantiated. Foreign trade policy, which is formed under the influence of risks and threats of war, is aimed at developing and increasing the volume of foreign trade with EU countries and the USA, Japan and Canada. The priority areas of foreign trade development are: defense-industrial complex; metallurgy and metalworking; agro-industrial complex; engineering; mining industry; furniture and woodworking industries. An important place is also defined for the development of innovative enterprises and knowledge-intensive production, which will ensure the transition to a developing economy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".