Diversification of the Structure of Export Activities Under Conditions of Economic Crisis and Loss of Foreign Markets
Bibliographic record
Abstract
Havrylchenko O. V. Diversification of the Structure of Export Activities Under Conditions of Economic Crisis and Loss of Foreign MarketsThe article is aimed at analyzing the theoretical and methodological approaches to diversification of Ukrainian exports under conditions of economic crisis and loss of foreign markets.The essence and reasons for export diversification are considered, the structure and tendencies of development of national exports are explored.The carried out analysis of the structure and dynamics of Ukrainian exports showed the need to diversify Ukraine's products with the purpose to gradually turn into a State with an innovative knowledge-intensive economy.This will help to restore economic growth and achieve a certain level of competitiveness.According to the results of the analysis, a large diversification of Ukrainian exports due to the gradual decrease in Ukraine's focus on the CIS markets and, in particular, on the Russian market, is specified.Ukraine for now insufficiently uses trade opportunities with countries such as the United States, Germany, Great Britain, France, Japan and Canada.In general, the State underutilizes the trade potential with 75 world countries and thus underreceives about 6 billion US dollars.It is substantiated that in the conditions of economic crisis and loss of external markets it is advisable to use the opportunities of innovative and inertial directions of diversification.A methodology for evaluating export diversification at the regional and enterprise level is proposed, which should become the basis for determining methods of diversification and identifying measures aimed at optimizing the commodity structure of exports.Understanding the main stages of export diversification of enterprise is an important condition for its further implementation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".