Hospitals of Industry: New York’s Progressive Era Labor Colonies
Bibliographic record
Abstract
Recent scholarship, including the work of scholars like Barbara Arneil (2017), asks researchers in places like the United States and Canada to revisit histories of colonialism closer to home. This dissertation analyzes one moment of domestic colonialism, in Progressive Era New York State. Using archival materials and scholarly literature, this research analyzes three instances of labor colonies: the New York City Farm Colony, New York State’s planned Industrial Farm Colony, and the Warwick Farm for Inebriates. Traced through each of these is a thread of the “Unemployable”—a label of rising salience often associated with homelessness, addiction, or non-deservingness of aid—for which the labor colony was a suitable remedy. During the Progressive Era, institutions like the New York City Farm Colony became increasingly focused on the Unemployable, and these institutions mandated sophisticated and intense kinds of agricultural and industrial work. Meanwhile, policymakers passed a state industrial farm colony law for people convicted of misdemeanors like disorderly conduct and public intoxication. Only due to the development of a national, wartime labor colony plan did the state colony not open. An interdisciplinary work of policy history offering a new approach, this dissertation features chapters on the history of the concepts of colony and vagrant, an archival history tracing the implementation of the state’s Unemployable labor colony institutions, an analysis of the policy process associated with the state labor colony bill, as well as a working out of the political theory behind colonies. The dissertation concludes with a reflection on the heterotopic nature of social policy and pathways for future historical, theoretical, and methodological development.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".