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Record W2896661900 · doi:10.6000/1929-7092.2018.07.30

Brics’ Foreign Debt Burden and its Impact on Core Institutional Basis

2018· article· en· W2896661900 on OpenAlexvenueno aff
Ravil Akhmadeev, Olga Bykanova, Tatyana Turishcheva

Bibliographic record

VenueJournal of Reviews on Global Economics · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsFinancial crisisDebtEconomicsEmerging marketsRedistribution (election)External debtInternational economicsGlobal imbalancesDebt crisisFinancial systemCapital (architecture)FinanceBusinessCurrent accountMacroeconomicsPolitical scienceExchange rate

Abstract

fetched live from OpenAlex

Creation of a multipolar international economy and economic relations is accompanied by shifting gravity centers of international finances, redistribution of positions on the global market for financial services in favor of large emerging countries and countries with transitional economies. This post crisis period triggered serious problems related to international capital inflows and outflows at the BRICS states. This is all due to a slow recovery of developed countries; a high probability of a full-scale debt crisis in some E.U. states; mounting uncertainties following financial reforms in some states, etc. But raising debt as an important way to finance speedy economic growth and import of technologies to the BRICS countries make their financial systems more vulnerable to exogenous stresses and shocks, which result in an unreasonable firming of national currencies. In our research, we have identified the risks and misbalances of global development, which affect BRICS, evaluated the influence of foreign debt and singled out the key growth trends. We have revealed the importance of the New Development Bank development, which will help solve urgent problems of its participants connected with their growing role in international economic relations: the creation of a regional financing mechanism as well as a core institutional basis to represent BRICS’ interests in the global financial structure and to become the missing link in interaction with global financial institutions.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.065
GPT teacher head0.310
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2018
Admission routes1
Has abstractyes

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Same venueJournal of Reviews on Global EconomicsSame topicEconomic Issues in UkraineFrench-language works237,207