Dogs and the Making of the American State: Voluntary Association, State Power, and the Politics of Animal Control in New York City, 1850-1920
Bibliographic record
Abstract
In the summer of 1914, amid a rabies outbreak among the local dog population, New York City health commissioner Sigismund S. Goldwater railed against urban dogs as useless creatures that offered nothing but a public health threat. “Can you tell me,” he cried, “what dogs are good for in a city? In the country they are all right, but in a city they are a nuisance from the point of view of sanitation, and there is always the danger of rabies.” Goldwater called for a year-round muzzling requirement and a new, municipally run pound to address the problem. The American Society for the Prevention of Cruelty to Animals (ASPCA), which had possessed enforcement power over the city’s canine animal control laws since the mid-1890s, immediately objected that it already possessed the capacity and expertise to deal effectively with stray dogs, and the society’s superintendent, Thomas F. Freel, hinted that malign health officials sought to rid the city of dogs entirely. In response Deputy Health Commissioner Haven Emerson directly attacked the ASPCA for its inadequate control of strays. He declared, “You can quote me as saying that the Society for the Prevention of Cruelty to Animals does not cope with the situation confronting the city.”1
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".