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Record W4387886906 · doi:10.15678/pg.2022.60.2.02

Health Security as a Global Public Good in the Conditions of the Revolution 4.0

2022· article· en· W4387886906 on OpenAlexaff
Salvatore Giacomuzzi, Martin Rabe, Ivan Titov, T. Zozul, Маріанна Кохан, Natalya Zyhaylo, Natascha Barinova, Kira Sedykh, Oleksandr Kocharian, Roman Kechur, K. Garber, Rüdiger Stix, M. Ertl, David Clowes

Bibliographic record

VenueJournal of Public Governance · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicBusiness and Economic Development
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsPublic healthGlobal healthPolitical scienceComputer securityBusinessComputer scienceMedicineNursing

Abstract

fetched live from OpenAlex

Objectives: Although the concept of health security is becoming accepted in public-health-related literature and practice, there is no full agreement on the scope and content. The aim of this paper is to draw attention to the definition of health security and its role within the Revolution 4.0. Research Design & Methods: This is a theoretical article and as such addresses a problematic situation concerning missing standards in health security and the Revolution 4.0. Findings: The WHO (2018) has stated unequivocally that ‘functioning health systems are the bedrock of health security’. The authors attempt to prove that health security in the conditions of the Revolution 4.0 needs to be defined more precisely and has to be implemented as a global public good nationwide with accepted minimal standards. Implications / Recommendations: H ealth security belongs to the sphere equally important to that of the Revolution 4.0. A concept of Health Security that is not widely accepted and implemented creates a problematic mélange for employees as well as for industrial development. These features will be considered. Contribution / Value Added: This paper tries to underline the relative shortage of common agreements on health within the Revolution 4.0.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.230
Teacher spread0.216 · 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 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
Published2022
Admission routes1
Has abstractyes

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