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Record W2901072078 · doi:10.6000/1929-7092.2018.07.42

Can the World Monetary System be Saved from Collapse by Monetary Gold

2018· article· en· W2901072078 on OpenAlexvenueno aff
Svetlana B. Varlamova, Marina B. Medvedeva

Bibliographic record

VenueJournal of Reviews on Global Economics · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Development and Digital Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsMonetary systemEconomicsMonetary hegemonyMonetary policyGold as an investmentMonetary economicsCommodityGlobalizationCapital (architecture)Gold standard (test)International economicsMarket economy

Abstract

fetched live from OpenAlex

The world community is gripped by the expectation of significant changes in the international monetary system, which has been permanently in crisis for decades. The uncertainty of the future gives rise to a sense of impending catastrophe, which must be prepared now, finding reliable anchors for preserving capital and providing an equivalent exchange in commodity markets. Historically, during a period of aggravation of the crisis of the international monetary system, monetary gold invariably remains as a reliable anchor, which is due not only to its unique properties, but also to the mentality of economic entities of all levels. The article deals with the basis of the emergence and periodic aggravation of the crises of the international monetary system, the causes of the new exacerbation, and the changing role of monetary gold in the process of globalization of the world economy. The role of international reserves in the gold reserve in the maintenance of socio-political stability is shown, the reasons determining the need to preserve and increase the gold reserves of central banks are substantiated.

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)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0070.012
Open science0.0010.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0080.003

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 head0.034
GPT teacher head0.219
Teacher spread0.184 · 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 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
Published2018
Admission routes1
Has abstractyes

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