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Record W4381799308 · doi:10.32370/ia_2023_06_6

Modern Threats to the Financial and Economic Security of Aerospace Enterprises

2023· article· en· W4381799308 on OpenAlexvenueno aff
Ганна Ліхоносова

Bibliographic record

VenueIntellectual Archive · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsAerospaceBusinessAccountingProfit (economics)Promotion (chess)FinanceIndustrial organizationEconomicsEngineeringPoliticsPolitical science

Abstract

fetched live from OpenAlex

The study provides an analysis of modern challenges and conditions in which Ukrainian business operates during hostilities, and their impact on accounting and tax activities. An analysis of laws and regulatory documents developed by the state for the functioning and improvement of the situation of enterprises affected by hostilities was carried out. Scientific publications and monographic editions, magazine articles and materials of scientific and practical conferences became the methodological basis of the research. Content analysis of scientific periodicals was used during the research; comparative critical analysis of existing approaches and methods of analysis of financial stability and tax burden; analysis of economic activity of enterprises in the aerospace industry; statistical methods of analysis. The main hypothesis of the study was the assumption of the possibility of restoring the country's production potential due to the introduction of the latest accounting and tax technologies of digital transformation of Ukraine, national projects for the development of entrepreneurship, digital interaction platforms for business relocation assistance. Using the example of an enterprise belonging to the aviation industry, the influence of social and behavioral challenges on the accounting and tax activities of this enterprise, namely: on calculations with the budget, the amount of profit and on calculations of labor remuneration, was investigated. Measures to improve business promotion under martial law are proposed.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.534
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.029
GPT teacher head0.243
Teacher spread0.214 · 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.

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
Published2023
Admission routes1
Has abstractyes

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