Scientific Medicine in the Time of Cholera: the Johns Hopkins Ethos and US Friendly Power in North China, 1919
Bibliographic record
Abstract
Abstract Vashti Bartlett, a Johns Hopkins nurse and member of the American Red Cross Commission to Siberia, was part of a global expansion of United States (US) influence before and after World War I. Through close examination of Bartlett’s extensive personal archives and her experiences during a 1919 cholera epidemic in Harbin, North China, we show how an individual could embody a “friendly” or “capillary” form of imperialist US power. Significantly, we identify in Bartlett yet another form that US friendly power could take: scientific medicine. White, wealthy, female, and American, in the context of her international nursing activities Bartlett identified principally as a scientific practitioner trained at Johns Hopkins where she internalized a set of scientific ideals that we associate with a particular “Hopkins ethos.” Her overriding scientific identity rendered her a useful and conscientious agent of US friendship policies in China in 1919.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.027 | 0.025 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".