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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 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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.842
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.007
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 head0.127
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations5
Published2020
Admission routes1
Has abstractyes

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