Waiting for the State: Sex Work and the Neoliberal Governance of Sexuality
Bibliographic record
Abstract
Focussing primarily on a public HIV/AIDS prevention clinic, this article considers the changing relationship between sex workers and the Costa Rican state, demonstrating that the state's approach to policing the sex industry has been defined by a shift from collective repression to neoliberal individualism. Instead of the indiscriminate sanitary raids and mass incarceration of the past, waiting for health care has come to play a central role in how sex workers interact with the neoliberal state. Significantly, this move towards making sex workers into individuals accountable for their own health has included undocumented migrants. However, the individualising effect of neoliberal state formations has occurred specifically within the public health sector, as the state does make an important distinction between sex workers in its use of immigration raids at San José's most notorious sex tourism business. Neoliberal rationalities of sexual governance ultimately separate and differentiate, and this article demonstrates the ways in which neoliberal state power operates both through the mundaneness of waiting at the HIV/AIDS prevention clinic and through the spectacle of immigration raids. Thinking about how the Costa Rican state has approached the control of sex work demonstrates the inconsistencies and contradictions of neoliberal governance, and the selectivity of neoliberal state formation.
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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 | 0.007 | 0.032 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".