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Record W4380486273 · doi:10.1177/13691481231178248

COVID-19 vaccine apartheid and the failure of global cooperation

2023· article· en· W4380486273 on OpenAlex
Stephen Brown, Morgane Rosier

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe British Journal of Politics and International Relations · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of CanadaLeverhulme Trust
KeywordsAccountabilityMultilateralismBusinessEconomic growthTollPolitical scienceDevelopment economicsEconomicsPoliticsMedicineLawImmunology

Abstract

fetched live from OpenAlex

The equitable distribution of COVID-19 vaccines is one of the most important tests of global cooperation that the world has faced in recent decades. Collectively, global leaders failed that crucible abysmally, creating a 'vaccine apartheid' that divided the world according to income into countries with widespread access and those without. Why, given that leaders were fully aware of the risks and injustice of vaccine inequity, did governments of wealthy countries hoard doses, impede the expansion of vaccine manufacturing and otherwise prevent equitable access to vaccines? We argue that their decisions to act selfishly are best explained by governments' accountability to domestic constituencies, their lack of leadership and commitment to multilateralism and their adoption of short-term perspectives, as well as their unwillingness to curb the influence of profit-oriented global pharmaceutical companies and, to a certain extent, of an additional private actor, the Bill and Melinda Gates Foundation.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.019
GPT teacher head0.321
Teacher spread0.301 · 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