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Record W3114977971

State Regulation over Operations with Military Goods as an Protection Element of a State National Security

2020· article· en· W3114977971 on OpenAlexaboutno aff
Valentyn Halunko, Nataliia Varenia, С. М. Гусаров, Iryna Berezovska, Olеks, er Griza

Bibliographic record

VenueJournal of Legal Ethical and Regulatory Issues · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Sanctions and International Relations
Canadian institutionsnot available
Fundersnot available
KeywordsElement (criminal law)State (computer science)LicenseSanctionsNational securityOrder (exchange)Control (management)BusinessLawComputer securityInternational tradePolitical scienceEconomicsFinanceComputer scienceManagement
DOInot available

Abstract

fetched live from OpenAlex

The article is devoted to the study of the features of state regulation over operations with military goods as a protection element of the state national security. It was established that States in order to maintain peace and protect the interests of all States, have undertaken a number of obligations to ensure arms control, export control and combat with gunrunning. It was found that the state regulation over operations with military goods is carried out by drawing up supervision lists, issuing licenses\permits, exchanging information, compiling reports, and declarations, conducting inspections and imposing sanctions for law violation in this area. It is revealed the experience of Poland, Canada and Ukraine in the sphere of making state regulation over the military goods export. It is concluded that it is necessary to harmonize the legal regulation of regulation over operations with military goods in the European Union States; to create an electronic application system for obtaining a license\permit for operations with military goods in Ukraine; to strengthen cooperation between public and private entities in the sphere of regulation over operations with military goods.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.030
GPT teacher head0.275
Teacher spread0.244 · 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 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
Published2020
Admission routes1
Has abstractyes

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