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Record W4402760976 · doi:10.3390/jrfm17090422

Integrating Money Cycle Dynamics and Economocracy for Optimal Resource Allocation and Economic Stability

2024· article· en· W4402760976 on OpenAlexvenueno aff
Constantinos Challoumis - Κωνσταντίνος Χαλλουμής

Bibliographic record

VenueJournal of risk and financial management · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsnot available
Fundersnot available
KeywordsStability (learning theory)Resource allocationDynamics (music)Resource (disambiguation)EconomicsComputer scienceOperations researchEngineeringMarket economySociology

Abstract

fetched live from OpenAlex

This paper integrates two theoretical frameworks to explore optimal resource allocation and the dynamics of the money cycle in a hypothetical economy. It examined the theoretical background of the problems of choice. The first framework considers an economy governed by an omniscient authority responsible for production and distribution decisions, focusing on the logic of choice and efficient resource allocation. The second framework introduces the concept of the new economic system of Economocracy, emphasizing the role of the Money Cycle theory in economic management and governance. By combining these frameworks, the paper provides a comprehensive understanding of productive and distributive efficiency and examines the impact of the money cycle on economic stability and growth. A mathematical modeling of the money cycle is presented to highlight the relationship between money distribution, economic capacity, and overall economic health. The integrated approach offers valuable insights for optimizing resource allocation and enhancing economic resilience.

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)0.007
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 score0.005
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0030.006
Open science0.0010.003
Research integrity0.0020.002
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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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

Citations21
Published2024
Admission routes1
Has abstractyes

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