Polygamy and safe sex negotiation among married women: evidence from Cameroon
Bibliographic record
Abstract
BACKGROUND: Research indicates that women in polygamous relationships may be exposed to unique sexual and reproductive health challenges. However, there are very few studies that examine whether polygamy is associated with safe sex negotiation among married women in sub-Saharan Africa, including Cameroon. METHODS: Using the 2018 Cameroon Demographic and Health Survey, we apply logistic regression analysis to compare two indicators of safe sex negotiation (i.e., the ability to ask for condom use and refuse sex against their partner) between polygamous (n = 1,628) and monogamous (n = 5,686) women aged 15-49 years old. RESULTS: We find that 67% and 50% of married women can ask for condom use and refuse sex against their partner, respectively. Multivariate analysis further reveals that women in polygamous relationships are less likely to report they can ask for condom use (OR = 0.71, p < 0.001) and refuse sex (OR = 0.64, p < 0.001) in comparison to their monogamous counterparts. CONCLUSIONS: Our analysis found that in Cameroon, women in polygamous relationships, Muslim women, married women with inadequate HIV knowledge, those who had never been tested for HIV and women with lower socioeconomic status are less likely to negotiate for safe sex. Based on these findings, we discuss several implications for policymakers, including the establishment of a comprehensive family planning educational program and the deployment of community health workers to disseminate educational initiatives pertaining to safe sex negotiation to community members.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".