"Simple, Easy, and Intelligible": Republican Political Ideology and the Implementation of Vaccination in the Early Republic
Bibliographic record
Abstract
First introduced in 1798 by the English doctor Edward Jenner, smallpox vaccination generated a sensation in Europe and America in the first quarter of the nineteenth century. Vaccine became highly politicized in the American republic as enthusiasts debated how to implement the new preventive; some promoters argued that it was suitable for democratized use by self-reliant householders, while others insisted that the complexity of the procedure should limit its use to trained experts and "learned physicians." Disagreement centered on the place of knowledge in the republic and its accessibility to private citizens. The debate over proper vaccinators entered national politics in 1813 when Congress established the National Vaccine Institute (NVI) in response to the proposal of a Baltimore almshouse physician. Founded on the premise that it would supply any citizen—physician or not—with vaccine, the NVI represented an egalitarian view of science and medicine that held such knowledge both suitable and essential for virtuous republican citizens. This essay finds that from the introduction of vaccination to the United States in 1800 through the destruction of the National Vaccine Institute in 1822, debates about proper vaccinators and medical knowledge played an important role in a broader debate about knowledge, social hierarchy, and the shape of the American republic.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.037 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".