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Record W2526266002 · doi:10.1080/01436597.2016.1233491

PATH: pioneering innovation for global health at the public–private interface

2016· article· en· W2526266002 on OpenAlexaff
Michael Stevenson

Bibliographic record

VenueThird World Quarterly · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsBalsillie School of International Affairs
FundersGlaxoSmithKlineBill and Melinda Gates Foundation
KeywordsEconomic growthGlobal healthPublic healthPublic relationsMultidisciplinary approachDeveloping countryBusinessHealth carePolitical scienceSociologyEconomicsMedicineSocial science

Abstract

fetched live from OpenAlex

Seattle-based PATH is one of the world’s largest not-for profit organisations focused on improving health in low-income countries. This article argues the history of this understudied organisation is critical to understanding how collective action focused on facilitating developing countries’ access to essential health technologies is structured. Since its establishment almost 40 years ago, the organisation has been a catalyst for multidisciplinary public–private collaboration that has produced affordable, culturally appropriate health technologies. From its origins in reproductive health, enabling contraceptive technology transfers and advising on regulatory standards, to its more recent managerial roles in the development of inexpensive vaccines produced in developing countries, PATH has repeatedly illustrated how public–private collaboration in product research and development can increase poor populations’ access to essential health technologies. This in turn has provided substance to the contested narrative that engaging business is critical to reducing global health disparities.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.751
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.318
Teacher spread0.257 · 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.

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

Citations9
Published2016
Admission routes1
Has abstractyes

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