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Record W7128688509 · doi:10.65672/fs.2025.4.2

Development of the Government Securities Market of the Republic of Moldova through Increasing the Investment Attractiveness of These Instruments

2025· article· en· W7128688509 on OpenAlexaboutno aff
Rodica Hincu, Ana Litocenco

Bibliographic record

VenueFINANCIAL STUDIES · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBanking, Crisis Management, COVID-19 Impact
Canadian institutionsnot available
Fundersnot available
KeywordsRomanianAttractivenessGovernment (linguistics)Investment (military)Broker-dealerInvestment bankingThe RepublicFinancial instrument

Abstract

fetched live from OpenAlex

In the current period, when countries, including the Republic of Moldova, need to identify financial resources, the need is constantly growing, and investors are increasingly interested in diversifying their investment portfolios into safe and profitable financial instruments. The development of the government securities market and increasing the attractiveness of these financial instruments are becoming primary considerations and objectives. The purpose and objective of this article is to provide an analysis of the particularities of the Moldovan government securities market, international experiences and best practices on this topic (Romania, Hungary, Türkiye, Brazil, Canada) with a view to identifying opportunities for development of the Moldovan government securities market. The development opportunities identified by the authors as a result of the research focus on aspects aimed at increasing the attractiveness of Moldovan government securities and diversifying the investor base, such as market accessibility, the diversity of instruments, financial benefits, and opportunities to manage related investment risks. The methodology includes analytical, descriptive, synthesis, quantitative, qualitative, comparison, and graphical methods.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.040
GPT teacher head0.273
Teacher spread0.233 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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