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Record W4386802621 · doi:10.1080/17441692.2023.2256822

Can we move beyond vaccine apartheid? Examining the determinants of the COVID-19 vaccine gap

2023· article· en· W4386802621 on OpenAlexaff
Lisa Forman, Carly Jackson, Kaitlin Fajber

Bibliographic record

VenueGlobal Public Health · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsWaiverGlobal healthHealth equityIntellectual propertyPolitical scienceRight to healthTreatyPublic healthEconomic growthSocial determinants of healthInternational Health RegulationsPandemicBusinessDevelopment economicsCoronavirus disease 2019 (COVID-19)EconomicsHealth careMedicineInfectious disease (medical specialty)Law

Abstract

fetched live from OpenAlex

While global health leaders call disparities in access to COVID-19 vaccines an 'apartheid,' this gap is not the first such disparity. The recurrence of these gaps in low and middle-income countries and especially in Africa, raises questions about their determinants and about the persistent failures of global health institutions to remediate them. We interrogate these determinants and questions by examining: (1) the distribution of COVID-19 vaccines; (2) primary determinants of vaccine access including availability and affordability; (3) factors affecting availability (hoarding, COVAX, and manufacturing capacity); and (4) factors affecting affordability (pricing, intellectual property rights (IPR), the TRIPS waiver and a potential pandemic treaty). We conclude that IPR constrained the affordability and availability of COVID-19 vaccines in ways inadequately addressed by COVAX and a waiver compromise thwarted by political, corporate, and philanthropic interests. While stronger limits to IPR in a pandemic treaty and a reformed International Health Regulations will not resolve structural inequities, they could meaningfully expand LMIC autonomy to protect public health. We urge equity-seeking Global South and North actors to fight for such IPR reforms as small and meaningful steps towards a more equitable global health order. Otherwise, criminally racist 'apartheids' will continue to be the norm when it comes to the distribution of essential health goods during global health emergencies.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.178
GPT teacher head0.364
Teacher spread0.186 · 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 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

Citations12
Published2023
Admission routes1
Has abstractyes

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