ТРАНСФОРМАЦІЯ СИСТЕМИ РОЗВИТКУ ЕКСПОРТНОГО ПОТЕНЦІАЛУ УКРАЇНИ НА ОСНОВІ ТОРГОВЕЛЬНОГО ДОСВІДУ КРАЇН G7
Bibliographic record
Abstract
The relevance of this research stems from the profound transformation of Ukraine’s foreign economic activity under conditions of full-scale war, disruption of trade relations, decline in industrial production, and logistical constraints. At the same time, exports remain a key factor in sustaining the balance of payments, currency stability, and economic recovery. Enhancing export potential is therefore viewed not only as an economic necessity but also as a strategic priority requiring coordinated interaction between state institutions, businesses, and international partners. The study addresses the problem of Ukraine’s fragmented and insufficiently coordinated export promotion system, which particularly hinders small and medium-sized enterprises due to limited access to financial, logistical, and analytical resources. Global transformations caused by military aggression and instability necessitate a systemic rethinking of export policy. The aim of the research is to substantiate theoretical foundations and propose a hierarchical model for strengthening Ukraine’s export potential, drawing on the trade experience of the G7 countries. A review of recent academic and institutional publications demonstrates wide coverage of Ukraine’s export challenges but insufficient attention to the development of a comprehensive multi-level model. Existing studies analyze structural shifts in trade, logistical disruptions, and institutional barriers, while reports by USAID, EBRD, UkraineInvest, and the Export Promotion Office emphasize the lack of effective coordination and SME support mechanisms. The analysis of G7 trade dynamics for 2015–2023 reveals two dominant models—export-oriented (Germany, Italy, Canada) and import-dependent (USA, France, Japan, United Kingdom)—shaped by industrial structure and foreign policy. Ukraine, in contrast, demonstrates vulnerability to external shocks, with the deepest trade deficit recorded in 2022–2023 due to war, port blockades, and declining industrial exports. Agricultural goods remain dominant, while industrial output and logistics infrastructure suffer significant losses. On this basis, the article proposes a hierarchical model integrating strategic, institutional, and operational components of export development. Its implementation would strengthen export-oriented industries, modernize infrastructure, improve human capital, and enhance Ukraine’s resilience in global trade. The proposed framework can thus serve as a foundation for post-war economic recovery and the formation of an effective state export support policy adapted to contemporary geopolitical and economic challenges.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.011 |
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".