Essential, Illustrative, or … Just Propaganda? Rethinking John Snow's Broad Street Map
Bibliographic record
Abstract
For more than a century John Snow's iconic map of an 1854 cholera outbreak in the Broad Street area of Soho, London, has been the very definition of how to discover the source of a disease. Some now argue, however, that the map was merely an illustrative and not very imaginative graphic. Here we argue that this position is incorrect. Snow's mapping of the Broad Street outbreak produced a spatial argument that was a critical evidentiary statement. This position requires us to ask, If that is true, is the map in part responsible for Snow's inability to convince contemporaries of his argument that cholera was water-borne and not airborne? In doing so, we use mid-nineteenth-century methodologies to demonstrate that the problem was not in the map but in Snow's handling of the data. This review of a seminal study in the history of disease studies not only informs historical perspective but, in its conclusions, speaks to the utility of medical mapping in contemporary disease studies, where spatialization of a disease event remains a critical method of investigation.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".