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Record W4380202881 · doi:10.34172/hpp.2023.05

Access to medicines through global health diplomacy

2023· review· en· W4380202881 on OpenAlexaff
Vijay Kumar Chattu, Bawa Singh, Sanjay Pattanshetty, K. Srikanth Reddy

Bibliographic record

VenueHealth Promotion Perspectives · 2023
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsBruyèreUniversity of OttawaUniversity of Toronto
Fundersnot available
KeywordsEssential medicinesAccess to medicinesDiplomacyGlobal healthBusinessSustainable developmentRight to healthQuality (philosophy)Economic growthHealth careMedicinePolitical scienceDeveloping countryLawEconomics

Abstract

fetched live from OpenAlex

The World Health Organisation (WHO) emphasizes that equitable access to safe and affordable medicines is vital to attaining the highest possible standard of health by all. Ensuring equitable access to medicines (ATM) is also a key narrative of the Sustainable Development Goals (SDGs), as SDG 3.8 specifies "access to safe, effective, quality and affordable essential medicines and vaccines for all" as a central component of universal health coverage (UHC). The SDG 3.b emphasizes the need to develop medicines to address persistent treatment gaps. However, around 2 billion people globally have no access to essential medicines, particularly in lower- and middle-income countries. The states' recognition of health as a human right obligates them to ensure access to timely, acceptable, affordable health care. While ATM is inherent in minimizing the treatment gaps, global health diplomacy (GHD) contributes to addressing these gaps and fulfilling the state's embracement of health as a human right.

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)0.006
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 score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.001

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 head0.743
GPT teacher head0.642
Teacher spread0.101 · 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

Citations34
Published2023
Admission routes1
Has abstractyes

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