Exploring the link between household structure and women’s household decision-making autonomy in Mauritania
Bibliographic record
Abstract
Governments in sub-Saharan African countries aim to increase married women's household decision-making autonomy as it remains a critical determinant of desirable health behaviours such as healthcare utilisation, antenatal care visits, and safer sex negotiation. However, very few studies explore how household structure (i.e., monogamous or polygamous) is associated with married women's household decision-making autonomy. Our paper seeks to address this gap. Using the 2019-20 Mauritania Demographic and Health Survey, a nationally representative dataset, and applying logistic regression analysis, we explore how married women's household structure is associated with their household decision-making autonomy. We find that 9% of married women are in polygamous marriages, while 63% and 65% are involved in decision-making about their health and large household purchases, respectively. Additionally, 76% and 56% are involved in decision-making about visiting family or relatives and household expenditures. After accounting for socio-economic and demographic factors, we find that compared to women from monogamous households, those from polygamous households are less likely to participate in decision-making about their health (OR=0.65, p < 0.001), making large household purchases (OR=0.65, p < 0.001), visiting family or relatives (OR=0.72, p < 0.001), and household expenditure (OR=0.58, p < 0.001). Based on our findings, we recommend the urgent need to review and re-evaluate policies and approaches seeking to promote gender equality and women's autonomy in Mauritania. Specifically, it may be critical for intervention programmes to work around reducing power imbalances in polygamous household structures that continue to impact married women's household decision-making autonomy adversely. Such interventions should centre married women's socio-economic status as a central component of their empowerment strategies in Mauritania.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".