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Record W2920327747 · doi:10.29063/ajrh2017/v21i2.8

High rates of Unintended Pregnancies among Young Women Sex Workers in Conflict-affected Northern Uganda: The Social Contexts of Brothels/Lodges and Substance Use

2017· article· en· W2920327747 on OpenAlexafffund
Putu Duff, Godfrey Muzaaya, Katherine A. Muldoon, Sabina Dobrer, Monika Akello, Josephine Birungi, Kate Shannon

Bibliographic record

VenueAfrican Journal of Reproductive Health · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsUnintended pregnancyReproductive healthSex workMedicinePregnancyPopulationDemographyOutreachOdds ratioCross-sectional studyEnvironmental healthFamily planningFamily medicineHuman immunodeficiency virus (HIV)Political scienceSociology

Abstract

fetched live from OpenAlex

This study aimed to examine the correlates of unintended pregnancies among young women sex workers in conflict-affected northern Uganda. Data were drawn from the Gulu Sexual Health Study, a cross-sectional study of young women engaged in sex work. Bivariable and multivariable logistic regression was used to examine the correlates of ever having an unintended pregnancy. Among 400 sex workers (median age=20 years; IQR 19-25), 175 (43.8%) reported at least one unintended pregnancy. In multivariable analysis, primarily servicing clients in lodges/brothels [Adjusted Odds Ratio (AOR= 2.24; 95% Confidence Interval: 1.03-4.84)], hormonal contraceptive usage [AOR=1.68; 95%CI 1.11-2.59] and drug/alcohol use while working [AOR= 1.64; 95%CI 1.04-2.60] were positively correlated with previous unintended pregnancy. Given that unintended pregnancy is an indicator of unmet reproductive health need, these findings highlight a need for improved access to integrated reproductive health and HIV services, catered to sex workers' needs. Sex work-led strategies (e.g., peer outreach) should be considered, alongside structural strategies and education targeting brothel/lodge owners and managers.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.032
GPT teacher head0.326
Teacher spread0.293 · 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.

Study designObservational
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

Citations15
Published2017
Admission routes2
Has abstractyes

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