Double Jeopardy: Maintaining Livelihoods or Preserving Health? The Tough Choices Sex Workers Faced during the COVID-19 Pandemic
Bibliographic record
Abstract
The COVID-19 pandemic and associated public health preventive measures such as lockdown and home confinement have posed unique challenges to female sex workers (FSW) globally, including in Canada where the sex trade is not formally recognized. In this commentary, we discuss the unintended consequences the pandemic has had on various social determinants of health among FSW. We draw on a review of scholarly and grey literature, complemented by our experience with the Exit Doors Here program, a sex work exiting program implemented in Toronto, Canada. Due to COVID-19, many FSW suddenly lost their main source of income, work conditions became riskier, and sheltering-in-place presented challenges for women with no safe housing. The slowdown of social and health care services also meant FSW were not receiving the required attention. We make recommendations for intersectoral mitigation strategies to limit the short- and long-term impacts of COVID-19 on FSW health and livelihoods. Recommendations focus on addressing women's marginalizing circumstances and speak to a gender transformative approach to the COVID-19 recovery. Our recommendations are relevant to FSW and other marginalized groups, in the current context and in the context of future health, social, and economic crises.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".