Maternal Health and Social Determinants: A Study in Jammu and Kashmir
Bibliographic record
Abstract
Maternal health is a key indicator of women's health and status. The bio-medical theories attribute health to several biological and medical factors. The social determinant theories, on the other hand, have established that the social circumstances play dominant role in deciding health, morbidity and health care delivery. Social practices, like patriarchy, create long term social deprivations. The Ottawa Charter of Health Promotions passed in 1986 recognizes peace, shelter, education, food, income, a harmonious eco-system, resources, social justice and equity as essential pre-requisites for health. Situated within this background, this paper locates the status of maternal health in Jammu and Kashmir, the northernmost state of India and identifies the social determinants of maternal health. This work is based on the secondary sources in general and the data provided by District Level Household and Facility Survey (DLHS-3), India in particular. The data shows that place of delivery (government hospital, private clinic or home) is not a major determinant of delivery complications but the socio-cultural background like education, income and place of residence are important determinants. Even institutional delivery increases with the education level and wealth of the women. Rural-urban gap in institutional delivery was seen to be 35.9 percent. Despite being a comparatively richer state, anaemia is a very important determinant of maternal health in the state. The paper concludes that policy intervention is required to ensure empowerment, freedom, peace, justice and inclusion of women for sustainably improving the maternal health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".