Thresholds of Empire: Women, Biosecurity, and the Zika Chemical Vector Program in Puerto Rico
Bibliographic record
Abstract
The recent emergence of a new strand of the Zika virus evinces the global entwinement of viral, human, and animal ecologies on a dynamic planet. Capable of shaping physiological development in utero and transmittable by both mosquitoes and sex, Zika ignited fears about the plasticity of the human form in the face of infectious disease, the permeability of nation-state borders to infectious disease, and the lifetime health care costs of infectious disease. In the United States, these fears were mapped onto the “unincorporated territory” of Puerto Rico, where one fifth of the population was predicted to contract the virus. This article examines U.S. government chemical intervention in Puerto Rico, which I argue was underpinned by a contradictory mapping of the island as inside the United States in terms of risk and outside the United States in terms of rights. Puerto Rican women were spatialized as the threshold between the agency of the virus and the future of the U.S. population. When they were perceived to fail in properly managing their bodies and homes, aerial chemical fumigation was threatened in an aggressive display of U.S. sovereign power. This article offers careful and critical geographic analysis of how imperial state power is extended in the name of health and how women in different places are made into biosecurity objects. It also notes a broader destructive logic that positions the reproductive capacities of poor women outside of Northern states as the pivot between an increasingly unruly nonhuman world and the future. Key Words: biosecurity, chemical geographies, empire (Puerto Rico), gender, Zika.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".