Legal Interventions and Access to Maternal Health Services by Women with Disabilities (WWD) in Bangladesh: Lessons from Canada
Bibliographic record
Abstract
This thesis investigates how and why women with disabilities are facing various kinds of barriers and challenges while accessing maternal health services. It tries to focus on the barriers in the built environment and attitudinal barriers that hinder the way of getting maternal health services by women with disabilities which they are entitled to. A literature review discusses the major barriers which women with disabilities encounter across different jurisdictions along with Bangladesh. The literature review on the accessibility of Bangladesh and real-life stories confirms the existence of some common barriers women with disabilities face while accessing maternal health services. Further, provisions of the international disability convention, the UN Convention on the Rights of Persons with Disabilities, were discussed to establish the state obligation of Bangladesh to ensure the health care rights of women with disabilities. Moreover, the importance of the compliance of the human-rights approach in a national legal framework was discussed. In addition, legal lacunas of Bangladeshi laws were examined and possible legal interventions are discussed. Concerning that, Canadian accessibility provisions were taken into consideration for discussion. To conclude, recommendations are provided including necessary legal reforms of existing laws, incorporating new concepts and provisions to ensure accessibility of maternal health service in Bangladesh.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".