International Trade in the Post-Soviet Space: Trends, Threats, and Prospects for the Internal Trade within the Eurasian Economic Union
Bibliographic record
Abstract
This paper discusses the dynamics of foreign trade in the post-Soviet space within the Eurasian Economic Union (EAEU) during the period from 2015 to 2021. Additionally, the paper analyzes export indicators in foreign and mutual trade of the EAEU member countries and diversification of the commodity structure as well as its dynamics based on the commodity concentration index for each member country. Our paper identifies the strengths and weaknesses of the EAEU, analyzes the opportunities and threats of development, and focuses on the trends and prospects. The main strengths include the institutional and legal structure of the EAEU single market, the historical, cultural, and economic proximity of the EAEU member countries, the transit potential of the territory, the high level of domestic trade, and the increasing share of ruble transactions in the trade turnover. The most significant weaknesses are the low efficiency of the institutional structure, the gap in the socio-economic level of development of the participating countries, unstable geopolitical situations in some member countries, the low level of recognition of the EAEU in the world market, economic and political conflicts of interests of the member countries, and the dependence on Western technologies in some key industries. Strategically important opportunities can be found in the creation and implementation of a long-term development strategy, diversification of trade with the Middle East and Asian countries, expansion in terms of the territorial composition, development of the institutional and legal structure as well as cooperation ties, as well as the cooperation in the field of technological innovation and financial security. Among the most significant threats were identified the outpacing growth in the share of EAEU members’ trade with China, the expansion of economic and political contradictions between the EAEU member countries, and the strengthening of the positions of alternative currencies in foreign trade.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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".