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Record W4389986412 · doi:10.1080/17441692.2023.2290117

Surviving pandemic control measures: The experiences of female sex workers during COVID-19 in Nairobi, Kenya

2023· article· en· W4389986412 on OpenAlexaff
Hellen Babu, Rhoda Kabuti, Mamtuti Paneh, Emily Nyariki, James Pollock, Jennifer Liku, Alicja Beksinka, Mary Kungu, Pooja Shah, Tara Beattie, Joshua Kimani, Janet Seeley

Bibliographic record

VenueGlobal Public Health · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Toronto
FundersMedical Research CouncilDepartment for International Development, UK Government
KeywordsSex workMental healthPsychological interventionPandemicQualitative researchMedicineSocial stigmaStigma (botany)Reproductive healthUnemploymentPopulationSocioeconomicsEnvironmental healthPsychologyCoronavirus disease 2019 (COVID-19)Economic growthNursingPsychiatrySociologyFamily medicine

Abstract

fetched live from OpenAlex

At the beginning of the COVID-19 pandemic, the Kenya Ministry of Health instituted movement cessation measures and limits on face-to-face meetings. We explore the ways in which female sex workers (FSWs) in Nairobi were affected by the COVID-19 control measures and the ways they coped with the hardships. Forty-seven women were randomly sampled from the Maisha Fiti study, a longitudinal study of 1003 FSWs accessing sexual reproductive health services in Nairobi for an in-depth qualitative interview 4-5 months into the pandemic. We sought to understand the effects of COVID-19 on their lives. Data were transcribed, translated, and coded inductively. The COVID-19 measures disenfranchised FSWs reducing access to healthcare, decreasing income and increasing sexual, physical, and financial abuse by clients and law enforcement. Due to the customer-facing nature of their work, sex workers were hit hard by the COVID-19 restrictions. FSWs experienced poor mental health and strained interpersonal relationships. To cope they skipped meals, reduced alcohol use and smoking, started small businesses to supplement sex work or relocated to their rural homes. Interventions that ensure continuity of access to health services, prevent exploitation, and ensure the social and economic protection of FSWs during times of economic strain are required.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.069
GPT teacher head0.371
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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