The barriers to motherhood for disabled women in Ghana, Nigeria and Kenya
Bibliographic record
Abstract
While motherhood is a privilege for all women who desire it and make the decision to pursue the same, the narrative may be different for disabled women. Women with disabilities face diverse challenges in realizing their reproductive health rights and their desire to become mothers. The research explores the barriers to motherhood for disabled women in Ghana, Nigeria, and Kenya. The study specifically explores attitudes, superstition, culture, religion, gender roles, rate of disability among women in sub-Saharan Africa, womanhood expectations, sex education and violence, accessibility, gender discrimination and maternal health care. The social model of disability was used to understand better the barriers that disabled women face to becoming mothers. The research was carried out using a qualitative scoping review approach. An in-depth literature review on motherhood barriers among disabled women in Ghana, Nigeria, and Kenya was done. Over three months, the findings were analyzed and discussed. The findings indicated that women with disabilities faced challenges in accessing maternal healthcare facilities due to physical barriers, negative attitudes and stigma, socio-economic factors, discrimination and lack of comprehensive policies and social identities. The study suggested the urgent need for concerted efforts towards physical, social, economic, and policy-related factors to address the motherhood barriers faced by disabled women in Ghana, Nigeria, and Kenya.
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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 | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".