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Record W4210884687 · doi:10.1111/tran.12533

The US military's malaria research in Kenya and the geopolitics of global health

2022· article· en· W4210884687 on OpenAlexaff
Killian McCormack

Bibliographic record

VenueTransactions of the Institute of British Geographers · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGeopoliticsMilitarismGlobal healthMainstreamPolitical scienceEconomic growthInternational relationsEmpireSociologyPublic administrationPoliticsHealth careLaw

Abstract

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Abstract The US Army Medical Research Directorate – Africa, also known as the “Walter Reed Project,” is at the forefront of the US military's malaria research and surveillance practices. Since its establishment in Kenya in 1970, the Walter Reed Project's research capacity and infrastructure has significantly expanded, now placing it in a civilian‐led global health network. In this paper, I trace the development of the Walter Reed Project's malaria research and surveillance practices in Kenya from 1970 to today. I explore the geopolitical logics driving the Walter Reed Project's development, its growing infrastructure in Kenya, and its changing relationships with civilian institutes and global health networks. In doing so, I demonstrate the intersections between geopolitics and global health the Walter Reed Project reveals. The paper demonstrates how the Walter Reed Project brings geopolitical logics to bear on its collaborative global health research practices; how it reveals an often overlooked position of state power and geopolitics in mainstream global health networks; and how its health intervention sites in Kenya are points in a geopolitical topography of war‐making, connected to geographies of militarism, empire, and violence in disparate spaces. The paper reveals the attachments to war that underpin the military's global health engagement practices and that permeate mainstream global health networks and sites of health intervention.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.005
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.334
Teacher spread0.312 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2022
Admission routes1
Has abstractyes

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