Michael Zeheter, Epidemics, Empire and Environments: Cholera in Madras and Quebec City, 1818–1910
Bibliographic record
Abstract
What did nineteenth-century Madras and Quebec have in common? Both were within the empire, although that might be said of many towns and cities of the world. Both had to confront cholera and other epidemics whereby the limits of medical knowledge would be sorely tested and all the problems facing public health reform laid bare. Yet this was also true of Britain and across most of Europe too. The shared identity of the two settlements rests essentially with the manner in which Michael Zeheter contrasts their reactions to the onset of disease. His book occasionally loses the reader amid the wealth of detail provided; furthermore, throughout the work attention switches between the histories of the two cities, treating each as separate studies while attempting to draw out the differing contexts within which local officials had to work. Madras and Quebec varied enormously in terms of size, climate, population and culture. Madras was a sprawling and predominantly Indian city, which had gown rapidly since the late eighteenth century and which contained a population of approximately 400,000 by 1871. Quebec was a town of largely European settlement; in the early 1840s its French and English speaking citizens numbered only about 45,000. But if the logic for this comparative study is not immediately apparent, careful scholarship certainly justifies the work, and the author’s broad thesis, that public health continuously and permanently contributed to the formation of the state and the stabilization of colonial rule, is worthy of such meticulous investigation. Dense as the prose appears sometimes, this is research the way it used to be.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".