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Record W4312226732 · doi:10.3390/jrfm16010016

International Trade in the Post-Soviet Space: Trends, Threats, and Prospects for the Internal Trade within the Eurasian Economic Union

2022· article· en· W4312226732 on OpenAlexvenueno aff
Vera Kot, Arina Barsukova, Wadim Striełkowski, Mikhail Krivko, Ľuboš Smutka

Bibliographic record

VenueJournal of risk and financial management · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
FundersČeská Zemědělská Univerzita v Praze
KeywordsEconomic unionDiversification (marketing strategy)International tradeGeopoliticsStrengths and weaknessesCommodityPoliticsPolitical scienceBusinessInternational economicsEconomicsMarket economyLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.915
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.276
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2022
Admission routes1
Has abstractyes

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