‘A paradise among leprosariums’: Hansen’s disease and affective containment in the Panama Canal Zone
Bibliographic record
Abstract
The Panama Canal Zone’s American administration established Palo Seco Leper Colony in 1907 in order to contain individuals with Hansen’s disease. Yet containment was never a simple strategy. This article argues that American observers used rhetoric to transmute their fear of Hansen’s disease into pity, imagining isolation as a form of care and buttressing the United States’ claim that the curative violence of incarceration was part of a beneficent global project of humanitarianism, civilization, and modernity. At the same time, residents at Palo Seco often reworked or simply rejected these affective claims, and close attention to the archival record finds examples of their anger, love, and hope, as well as pain, stigma, and loneliness. Residents were labelled and consigned, ostensibly made static and ordered through diagnosis, but the site hosted a dynamism and disorder—in both senses of the word—that American imperialism professed to control, but never could. Palo Seco was a kind of emotional contact zone where managers, commentators, and residents negotiated the affective scripts and sentiments of their imperial encounter. Attention to these subjectivities testifies to the humanness, the ragged edges, and the profound affect of the imperial enterprise and its ableist institutions.
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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 | 0.002 | 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 | 0.017 | 0.019 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".