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Record W2901727062 · doi:10.6000/1929-7092.2018.07.37

The Influence of the Credit Policy of Commercial Banks on the Modernization of the Russian Economy Structure

2018· article· en· W2901727062 on OpenAlexvenueno aff
Ternovskaya Helena, Lavrishko Alexander

Bibliographic record

VenueJournal of Reviews on Global Economics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsnot available
Fundersnot available
KeywordsModernization theorySustainable developmentInvestment (military)BusinessEconomic systemNational economyCommercial bankProcess (computing)EconomicsFinancial systemEconomyMarket economyFinanceEconomic growthPolitical science

Abstract

fetched live from OpenAlex

The model for the development of the Russian economy is based on the need for its structural adjustment. A big role in this process is played by commercial banks, whose credit policy is not yet aimed at actively supporting of investment processes in the economy. The purpose of the article is to study the directions and instruments of the influence of credit activity of commercial banks on the sectoral structure of the Russian economy. Based on analysis of the characteristics of Russian bank’s credit policy measures were proposed to enhance its targeted focus on the modernization of Russia's economic structure through the development and support of special lending programs, including with regard to spatial development requirements. For this, a methodology has been developed to justify the choice of the region for their most effective implementation using the Gale-Shapley theorem. The set of proposed measures can contribute to strengthening the role of commercial banks in ensuring sustainable development of the national economy based on the impact on its structure.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.021
GPT teacher head0.296
Teacher spread0.275 · 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 designTheoretical or conceptual
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

Citations2
Published2018
Admission routes1
Has abstractyes

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