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Record W4308913656 · doi:10.18847/1.16.10

La securitización de la pandemia de la covid-19 en la Organización de Estados Americanos

2022· article· en· W4308913656 on OpenAlexfundno aff
Diego A. Morales

Bibliographic record

VenueRevista de Estudios en Seguridad Internacional · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsnot available
FundersWilfrid Laurier UniversityYale University
KeywordsSecuritizationCoronavirus disease 2019 (COVID-19)Health securityPandemicPolitical scienceAntecedent (behavioral psychology)Relation (database)HumanitiesSociologyPublic healthMedicinePsychologyPhilosophyEconomicsDiseaseSocial psychologyNursingComputer science

Abstract

fetched live from OpenAlex

The current paper is aimed to contribute to the International Relation´s research agenda related with international security´s studies linked to health. It analyzes the incorporation process of covid-19 pandemic in the Organization of American States´ security agenda, as an international health crisis, using the securitization theory and through the speech analysis. Likewise, it was used descriptive and analytic generalization methods to support the interpretation of the data obtained. As results, it was possible to confirm that, since the establishment of multidimensional security´s concept in 2003 by the OAS, the incorporation of issues related to health at the hemispheric security agenda is increasingly frequent, being HIV/aids the first precedent. In addition, the covid-19 pandemic is positioned as a new paradigmatic example in international security studies and, therefore, as a clear antecedent for the analysis of future similar phenomena resulting from health crisis.

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)0.012
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.345
Teacher spread0.334 · 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 designNot applicable
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

Citations1
Published2022
Admission routes1
Has abstractyes

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