Influence of gender norms on unassisted homebirths in Afghanistan: A qualitative study
Bibliographic record
Abstract
Despite efforts to promote gender equality in Afghanistan from 2002 to 2021, the country continues to face significant challenges in women's health, including high rates of unassisted homebirths and maternal mortality. This study explores the influence of gender norms on unassisted homebirths in Afghanistan, where conservative societal norms often dictate women's roles and access to healthcare. A qualitative case study design was employed to explore unassisted homebirths in Afghanistan. Data were collected from Afghan refugee men and women who had relocated to Canada. In-depth interviews were conducted with nine women who had experienced unassisted homebirths, and focus group discussions were held with six men and eight women to gather their experiences and observations of homebirths in their communities. The findings highlight a range of factors, including gender norms that burden women with exhaustive household and agricultural responsibilities, financial dependence on male family members that restricts their autonomy, and male-dominated decision-making processes that severely limit their agency in health-related choices. Additionally, social norms requiring women to seek permission from husbands or a male family member and have a mahram (husband or a permissible male companion) to access healthcare were found to compound barriers to skilled birth attendance. The research underscores the need for gender-sensitive strategies that engage family members, particularly male relatives and mothers-in-law, to promote skilled birth attendance and empower women through health education and improving their economic opportunities to make autonomous health decisions. Addressing these gender norms and power dynamics is crucial for reducing unassisted homebirths.
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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 | 0.019 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".