Quarantinism and Sanitarism as Strategies for Social Order’s Management and Epidemic Control in 19th-Century Europe
Bibliographic record
Abstract
The history of social order’s management and epidemic control in nineteenth-century Europe provides a wealth of evidence for understanding how and why different countries responded to the challenges of dangerous infectious diseases. The two most significant preventive strategies used in the nineteenth century were quarantinism, which consists in limiting active economic activities, and sanitarism, which involves improving the sanitary conditions of the population. In 1947, the German physician and medical historian Erwin Ackerknecht, for the first time analyzed these strategies and thus initiated a discussion of the determinants of medical knowledge and public health. This debate is still ongoing and has been reinvigorated in the wake of the COVID-19 pandemic. Familiarity with some of the points made in that debate may be very useful today, as it will not only give a fuller impression of how some areas of historical science have developed, but also shed new light on the question of how humanitarians make their judgments about such a significant area as the field of public health. The article examines three plots: 1) the explanatory model of quarantinism and sanitarism proposed by Ackerknecht, 2) use of his model by a new generation of scholars who entered this debate in the last quarter of the twentieth century, and 3) the experience of reinterpreting this model to reflect new approaches, in particular the expansive model proposed by Peter Baldwin.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.052 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".