Colonial Medicine, the Body Politic, and Pickering’s Mangle in the Case of Hong Kong’s Plague Crisis of 1894
Bibliographic record
Abstract
The eruption of bubonic plague in Hong Kong in 1894 was the flashpoint of the Third Pandemic, marking a critical juncture in the story of plague and plague fighters, and was also a galvanizing moment in the history of the port colony. The spread and containment of plague was accomplished through the agency of human actors, among them a rapidly growing Chinese population in the basin of Victoria Peak, a colonial regime governing from atop the Peak, an emerging class of Chinese elites, and teams of foreign scientists arriving in Hong Kong in hot pursuit of the pathogen. The arc of the plague was also potentiated by nonhuman agents: Hong Kong’s subtropical, monsoonic environment, the mountainous geography of the territory that supported various configurations of power, as well as migratory and commercial flows between China, the British empire and Hong Kong’s harbour, the ghosts of Chinese socio-religious tradition, heterogenous schemas of the body and disease in Chinese and Western medicine, and, of course, the fleas that bite rats, vectors of infection. I suggest that the writing of a history of plague in Hong Kong hinges on weaving together these streams of human and non-human agency. In particular, looking at Hong Kong in this moment of iatric crisis through the lens of the mangle, Andrew Pickering’s contribution to the evolving field of science studies, reveals how human and non-human agents constitute the experience of embodiment, the practice of medical science, the logics of imperialism, and not merely the writing of the histories of such.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.051 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".