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Record W2068159741 · doi:10.1080/13691058.2011.590901

Gendered HIV risk patterns among polygynous sero-discordant couples in Uganda

2011· article· en· W2068159741 on OpenAlexafffund
Katherine A. Muldoon, Kate Shannon, Sarah Khanakwa, Moses Ngolobe, Josephine Birungi, Wendy Zhang, Anya Shen, Rachel King, Robert Mwesigwa, David Moore

Bibliographic record

VenueCulture Health & Sexuality · 2011
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of British ColumbiaAIDS Vancouver
FundersCanadian Institutes of Health Research
KeywordsPolygynyHuman immunodeficiency virus (HIV)DemographyMedicineObstetricsEnvironmental healthVirologySociologyPopulation

Abstract

fetched live from OpenAlex

Stable serodiscordant relationships and sexual concurrency are pathways that contribute to the HIV epidemic in sub-Saharan Africa. However whether polygyny imparts the same risks as informal concurrent relationships remains an open research question. Using data collected at enrollment from a cohort study of sero-discordant couples, this analysis investigates how polygynous relationships differ from those involving only a single female spouse and whether men involved in polygynous partnerships are more likely to report HIV-risk behaviour than those in single spouse partnerships. Of 444 enrolled couples, 111 (25%) were polygynous and 333 (75%) were single-spouse partnerships. We found that polygynous men were more likely to report controlling sexual decision-making and to report any unprotected sex with unknown sero-status partner. After controlling for potential confounders, polygynous men were still more likely to report unprotected sex with an unknown sero-status partner. In this sample of sero-discordant couples we found indication of excess HIV-risk behaviour among men involved in polygynous relationships.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.180
GPT teacher head0.431
Teacher spread0.252 · 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

Citations14
Published2011
Admission routes2
Has abstractyes

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