Experiences and self-care efforts among female sex workers in Nairobi, Kenya, during COVID-19
Bibliographic record
Abstract
Although the COVID-19 measures were aimed at the public good, they resulted in massive economic disruptions. We explored female sex workers’ (FSWs) experiences and self-care efforts following the deployment of COVID-19 containment measures in Nairobi, Kenya. Forty-seven women drawn from 1003 FSWs enrolled in the Maisha Fiti Longitudinal Mixed-Methods Study participated. An in-depth interview tool was used to capture FSW’ experiences and coping strategies during the COVID-19 pandemic after the Kenya government imposed containment measures that affected work, parenting, alcohol and substance use, exposure to violence, reproductive health service utilization, and mental health. All interviews were audio-recorded and transcribed verbatim. The data were thematically analysed and managed using Nvivo 12 software. The findings show that FSWs suffered major economic loss following the COVID-19 containment measures that limited their movements and locked them out of sex work locations. Being mothers and daily wage earners, women reported challenges actualizing self-care goals for themselves and their children. Due to income loss, increased vulnerability to food and housing security, and mental distress were commonly reported. Specific behavioural actions to prevent contracting COVID-19 in the context of sex work were limited, due to women's inability to maintain social distance from clients. While the COVID-19 containment measures were intended to protect the public's health, they resulted in significant economic disruption for FSWs, which affected their ability to care for themselves and their children. Addressing the social determinants of sex work and discriminatory exclusionary practices is important for meeting the self-care needs of marginalised populations, especially FSWs and their families.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".