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Record W3082655641 · doi:10.17742/image.in.11.2.9

Overview of Key Legal, Political, and Social Challenges Facing Global Vaccination Efforts

2020· article· en· W3082655641 on OpenAlexvenueno aff
Nicola Sahar, Olivia Lee, Steven J. Hoffman, Lathika Sritharan

Bibliographic record

VenueImaginations Journal of Cross-Cultural Image Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsKey (lock)Political sciencePolitical economySociologyLawComputer scienceComputer security

Abstract

fetched live from OpenAlex

Despite the proven safety and effectiveness of vaccines, they are not utilized as widely as they should be. This article provides a high-level overview of five key challenges affecting the global vaccine uptake. First, availability is affected by the research costs and counterfeit vaccines. Second, accessibility is affected by distribution not being proportionate to need, and by poor infrastructure. Third, affordability is affected by intellectual property protections and costs of manufacturing and distribution. Fourth, appropriateness is affected by the way vaccine effectiveness varies and presents risks for immunocompromised populations. Fifth, acceptability is affected by controversies regarding risks and cultural objections.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.127
GPT teacher head0.467
Teacher spread0.340 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2020
Admission routes1
Has abstractyes

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