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Record W3160425885 · doi:10.1136/bmjgh-2021-006209

Flashing red lights: the global implications of COVID-19 vaccination passports

2021· article· en· W3160425885 on OpenAlexafffund
Kristin Voigt, Evrard Nahimana, Anat Rosenthal

Bibliographic record

VenueBMJ Global Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsVaccinationGlobal healthEquity (law)PandemicSolidarityInequalityPolitical scienceEconomic growthDevelopment economicsCoronavirus disease 2019 (COVID-19)Health careEconomicsMedicineLawPoliticsVirologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

### Summary As COVID-19 vaccination roll-outs are progressing in wealthy parts of the world, several countries are implementing or investigating COVID-19 vaccination passports that restrict access to restaurants, sports events or universities to those who have been fully vaccinated against COVID-19. While these discussions focus on domestic implementation, we must assume that, once introduced, vaccination passports will be applied to international travel. We argue that the global health community must participate in the debate about such schemes with an eye to equity and highlight their global implications. We emphasise two concerns. First, vaccination passports attached to international travel before equitable access to vaccines has been established will exacerbate global inequalities by effectively excluding from travel the millions of citizens of poor countries who are suffering from the health impact and the social and economic fallout of the pandemic, with little prospect of gaining access to vaccines any time soon. Such inequalities are rooted in a long history of colonialism and exploitation; global restrictions based on vaccination status will amplify these historic injustices. Second, such schemes will undermine global solidarity, increasing the risk that the pandemic is seen as a local issue rather than a genuinely global problem. Vaccination passports raise many ethical issues. Arguments for restrictions on people’s freedoms, such as lockdowns or quarantines, lose their traction when individuals have been fully vaccinated and therefore—as increasing evidence …

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)0.001
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: none
Teacher disagreement score0.904
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.046
GPT teacher head0.441
Teacher spread0.395 · 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

Citations32
Published2021
Admission routes2
Has abstractyes

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