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Record W2599897339 · doi:10.1163/18748945-03001001

Transnationalism in Missionary Medicine

2017· article· en· W2599897339 on OpenAlexaffabout
Margo S. Gewurtz

Bibliographic record

VenueSocial Sciences and Missions · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Medicine and Tropical Health
Canadian institutionsYork University
Fundersnot available
KeywordsPrestigeChinaFormative assessmentTropical diseaseTropical medicineIndigenizationHistoryAncient historyAnthropologySociologyMedicineDiseaseArchaeology

Abstract

fetched live from OpenAlex

Kala-azar is a parasitic disease that was endemic in India, parts of Africa and China. During the first half of the twentieth century, developing means of treatment and identification of the host and transmission vectors for this deadly disease would be the subject of transnational research and controversy. In the formative period for this research, two Canadian Medical missionaries, Drs. Jean Dow and Ernest Struthers, pioneered work on Kala-azar in the North Henan Mission. The great international prestige of the London School of Tropical Medicine and the Indian Medical Service would stand against recognition of the clinical discoveries of missionary doctors in remote North Henan. It was only after Struthers forged personal relations with Dr. Lionel. E. Napier and his colleagues at the Calcutta School of Tropical Medicine that there was a meeting of minds to promote the hypothesis that the sand fly was the transmission vector.

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)0.009
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.063
Scholarly communication0.0080.007
Open science0.0010.010
Research integrity0.0030.007
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 head0.183
GPT teacher head0.394
Teacher spread0.211 · 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
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

Citations1
Published2017
Admission routes2
Has abstractyes

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