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Record W7065852007

FINANCIAL ASPECTS OF RURAL TERRITORIAL COMMUNITIES: CURRENT STATE

2024· article· en· W7065852007 on OpenAlexaboutno aff

Bibliographic record

VenueThe Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsRevenuePosition (finance)State (computer science)Rural areaQuarter (Canadian coin)Work (physics)Sustainable development
DOInot available

Abstract

fetched live from OpenAlex

Introduction.The level of revenues to the general and special funds of the regional budget was studied. The purpose of the article is to study the financial aspects of supporting territorial communities in modern conditions. Results. It was substantiated that in 2021, Uzhhorod district accounted for the largest share of revenues to the general fund - 36.76%, and in 2022, this position was taken by Mukachevo district with an indicator of 40.28%. The Rakhiv district in the structure in both 2021 and 2022 occupied the last position, respectively 4.64 and 5.26%. Among all districts, the largest specific weight in the structure of revenues to the budget of Transcarpathian region in 2021 was occupied by rural territorial communities of Uzhhorod district - 8.56%, and in 2022 their specific weight increased to 10.01%. The specific weight of district revenues (general and special fund) to the Transcarpathian regional budget was calculated. The volume of revenues from rural territorial communities to district budgets within Transcarpathian region in the quarters of 2021-2022 has been substantiated. The volume of receipts of the districts to the general fund of the Transcarpathian region by quarter for 2021-2022 was analyzed. Conclusion. It was proven that the general fund of territorial communities is the main means of ensuring the functioning of the community, the implementation of socio-economic programs and ensuring the well-being of residents. Its effective use contributes to sustainable development and improving the quality of life in the community. Effective financing and management of resources in rural communities can contribute to the sustainable development of the country's economy as a whole. Ensuring the financial stability of rural communities and the distribution of financial resources for the development of infrastructure, education, health care and other areas of life are key to ensuring equal opportunities and social justice. It has been established that the financial allocations of local governments can vary depending on their unique circumstances, economic opportunities and government policies. Therefore, together, the general and special funds of territorial communities provide the versatility of financing and allow communities to effectively solve general needs and specialized tasks aimed at the development and provision of the population's well-being.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.046
GPT teacher head0.321
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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes1
Has abstractyes

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