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Record W2154567812 · doi:10.1371/journal.pone.0089593

Monitoring What Governments “Give for” and “Spend on” Vaccine Procurement: Vaccine Procurement Assistance and Vaccine Procurement Baseline

2014· article· en· W2154567812 on OpenAlexaboutno aff
E. Anthony S. Nelson, David E. Bloom, R. T. Mahoney

Bibliographic record

VenuePLoS ONE · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsProcurementBusinessAllianceGross domestic productFiscal yearEconomic growthFinanceEconomicsPolitical scienceMarketing

Abstract

fetched live from OpenAlex

BACKGROUND: The Global Vaccine Action Plan will require, inter alia, the mobilization of financial resources from donors and national governments - both rich and poor. Vaccine Procurement Assistance (VPA) and Vaccine Procurement Baseline (VPB) are two metrics that could measure government performance and track resources in this arena. VPA is proposed as a new subcategory of Official Development Assistance (ODA) given for the procurement of vaccines and VPB is a previously suggested measure of the share of Gross Domestic Product (GDP) that governments spend on their own vaccine procurement. OBJECTIVE: To determine realistic targets for VPA and VPB. METHODS: Organization for Economic Co-Operation and Development (OECD) and World Bank data for 2009 were analyzed to determine the proportions of bilateral ODA from the 23 Development Assistance Committee (DAC) countries disbursed (as % of GDP in current US$) for infectious disease control. DAC country contributions to the GAVI Alliance for 2009 were assessed as a measure of multilateral donor support for vaccines and immunization programs. FINDINGS: In 2009, total DAC bilateral ODA was 0.16% of global GDP and 0.25% of DAC GDP. As a percentage of GDP, Norway (0.013%) and United Kingdom (0.0085%) disbursed the greatest proportion of bilateral ODA for infectious disease control, and Norway (0.024%) and Canada (0.008%) made the greatest contributions to the GAVI Alliance. In 2009 0.02% of DAC GDP was US$7.61 billion and 0.02% of the GDP of the poorest 117 countries was US$2.88 billion. CONCLUSIONS: Adopting 0.02% GDP as minimum targets for both VPA and VPB is based on realistic estimates of what both developed and developing countries should spend, and can afford to spend, to jointly ensure procurement of vaccines recommended by national and global bodies. New OECD purpose codes are needed to specifically track ODA disbursed for a) vaccine procurement; and b) immunization programs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.061
GPT teacher head0.290
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2014
Admission routes1
Has abstractyes

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