Pox Americana the great smallpox epidemic of 1775 - 82
Bibliographic record
Abstract
Publisher description: A horrifying epidemic of smallpox was sweeping across the Americas when the War of Independence began, and yet we know almost nothing about it. Elizabeth A. Fenn reveals how deeply variola affected the outcome of the war in every colony and the lives of everyone in North America. By 1776, when military action and political ferment increased the movement of people and microbes, the epidemic worsened. Fenn's research shows us how smallpox devastated the American troops at Quebec and kept them at bay during the British occupation of Boston. Soon the disease affected the war in Virginia, where it ravaged slaves who had escaped to join the British forces. During the terrible winter at Valley Forge, General Washington had to decide if and when to attempt the risky inoculation of his troops. In 1779, while Creeks and Cherokees were dying in Georgia, smallpox broke out in Mexico City, whence it followed travelers going north, striking Santa Fe and outlying pueblos in January 1781. Simultaneously it moved up the Pacific coast and east across the plains as far as Hudson's Bay. The destructive, desolating power of smallpox made for a cascade of public-health crises and heartbreaking human drama. Fenn's work shows how this tragedy was met and what its consequences were for America.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".