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Record W4200286023 · doi:10.18280/ijsse.110608

The Formation of a Safety Ecosystem in the Context of Ensuring the National Homeland Security

2021· article· en· W4200286023 on OpenAlexvenueno aff
Олександр Поліщук, Yulia O. Bobrova, Yuriy Bobrov

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBanking, Crisis Management, COVID-19 Impact
Canadian institutionsnot available
Fundersnot available
KeywordsHomeland securityContext (archaeology)HomelandComputer securityRisk analysis (engineering)State (computer science)Environmental resource managementComputer scienceBusinessPolitical scienceEnvironmental scienceTerrorismLawGeography

Abstract

fetched live from OpenAlex

Today, the issue of creating conditions for homeland security is relevant, under which any socio-economic system can be comfortable and is not threatened by the negative influence of any external and internal factors. The main purpose of the study is to form a methodological approach to the formation of an appropriate defense ecosystem in the context of ensuring homeland security. To achieve this goal, we applied analysis and synthesis methods to study the current state of the homeland security level and the methodology for the formation of the IDEF0 functional model to represent the proposed defense ecosystem. The methodological approach can have the practical importance for state structures dealing with the issue of ensuring homeland security. The result of the study was the formation of a decomposition of the first, second and third levels of the functional model of the defense ecosystem in the context of ensuring homeland security. The article has limitations which are associated with the choice of the security system of Ukraine, since in the context of a pandemic, it was difficult to gain access to information from other countries. In the future, the proposed methodological approach is planned to be applied to the homeland security systems of other countries.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.113

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.012
GPT teacher head0.228
Teacher spread0.217 · 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 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

Citations14
Published2021
Admission routes1
Has abstractyes

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Same venueInternational Journal of Safety and Security EngineeringSame topicBanking, Crisis Management, COVID-19 ImpactFrench-language works237,207