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Record W3199094698 · doi:10.1080/17441692.2021.1977973

Priorities for global access to life-saving interventions during public health emergencies: Crisis nationalism, solidarity or charity?

2021· article· en· W3199094698 on OpenAlexaff
Nchangwi Syntia Munung, Samuel J. Ujewe, Muhammed O. Afolabi

Bibliographic record

VenueGlobal Public Health · 2021
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsCanadian Institutes of Health Research
FundersNational Heart, Lung, and Blood Institute
KeywordsSolidarityGlobal healthPublic healthPolitical scienceNationalismEconomic growthEquity (law)Psychological interventionPreparednessInternational healthHealth policyPublic administrationDevelopment economicsPublic relationsMedicinePoliticsLawEconomicsNursing

Abstract

fetched live from OpenAlex

Access to COVID-19-vaccines by the global poor has unveiled the impact of global health and scientific inequities on access to life saving interventions during public health emergencies (PHE). Despite calls for global solidarity to ensure equitable global access to COVID-19 vaccines, wealthy countries both in the north and southern hemisphere may find a charity-based approach more appealing and are using the opportunity to forge neo-colonial cooperation ties with some African countries. Solidarity is undoubtedly an ideal equity-based principle of public health emergency of international concern (PHEIC). However, its application may be wanting especially as crisis nationalism is more likely to inform the public health policy of any country during a PHEIC, even when they are strong advocates of global solidarity. African countries, on the other hand, must re-appraise their heavy reliance on international aids during PHE and recognise the importance of boosting their epidemic preparedness including research and translation of its findings to practice.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.751
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.300
GPT teacher head0.496
Teacher spread0.196 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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