Understanding the factors associated with married women’s attitudes towards wife-beating in sub-Saharan Africa
Bibliographic record
Abstract
BACKGROUND: Intimate partner violence remains a major public health problem, especially in countries in sub-Saharan Africa. We examined the factors associated with married women's attitudes towards wife-beating in sub-Saharan Africa. METHODS: We used Demographic and Health Survey data of 28 sub-Saharan African countries that had surveys conducted between 2010 and 2019. A sample of 253,782 married women was considered for the analysis. Bivariate and multivariate logistic regression analyses were carried out, and the results were presented using crude odds ratio (cOR) and adjusted odds ratio (aOR) at 95% confidence interval. RESULTS: The pooled result showed about 71.4% of married women in the 28 countries in this study did not justify wife-beating. However, the prevalence of non-justification of wife-beating varied from 83.4% in Malawi to 17.7% in Mali. Women's age (40-44 years-aOR = 1.61, 95% CI 1.16-2.24), women's educational level (secondary school-aOR = 1.47, 95% CI 1.13-1.91), husband's educational level (higher-aOR = 0.55, 95% CI 0.31-0.95), women's occupation type (professional, technical or managerial-aOR = 1.66, 95% CI 1.06-2.62), wealth index (richest-aOR = 5.52, 95% CI 3.46-8.80) and women's decision-making power (yes-aOR = 1.39, 95% CI 1.19-1.62) were significantly associated with attitude towards wife-beating. CONCLUSION: Overall, less than three-fourth of married women in the 28 sub-Saharan African countries disagreed with wife-beating but marked differences were observed across socio-economic, decision making and women empowerment factors. Enhancing women's socioeconomic status, decision making power, and creating employment opportunities for women should be considered to increase women's intolerance of wife-beating practices, especially among countries with low prevalence rates such as Mali.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".