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Global development financial institutions: the experience of project financing

2024· article· en· W4405949841 on OpenAlexaboutno aff
Artem S. Barakhovsky, Elena V. Mikhina, Dmitriy A. Andreev

Bibliographic record

VenueTyumen State University Herald Social Economic and Law Research · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsFinanceBusinessProject finance

Abstract

fetched live from OpenAlex

There is a significant research interest in project financing as a tool for active development of investment activity in Russia. The novelty of such research lies in studying the role, practical significance, and potential opportunities of development financial institutions (DFIs) in project financing. Using the methods of analysis and synthesis, grouping and comparison, the authors have analyzed the global practice of DFIs, which identifies the main vectors for the institutions’ current activities, achievements, and problematic aspects in promoting project financing. The cases of DFIs in Canada, Germany, and Brazil show the specifics of DFIs’ activities in project financing to solve social and economic problems, to overcome global problems and challenges, and to achieve sustainable development goals. Majority of the research focuses on the organizational, functional, regulatory, and legal support for the activities of DFIs as a tool for implementing investment projects. The other countries’ experience serves as a possible model for application in Russia. The comparison of the main parameters of DFIs in different countries identifies the strengths and weaknesses in their functioning, which is important for the Russian researchers and investors.

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)0.000
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 score0.971
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.111
GPT teacher head0.338
Teacher spread0.227 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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