Household Decisions to Utilize Maternal Healthcare in Rural and Urban India
Bibliographic record
Abstract
With the onset of pregnancy, a household must add the health of the expectant mother and the unborn child to its overall objective. Data from the Government of India's National Sample Survey Organization is utilized to analyze the determinants of women's decisions to register for pre- and postnatal healthcare, utilize maternal healthcare and select a place for childbirth. The data show that the level of schooling mothers have attained has a significant, positive effect on decisions to register and utilize these healthcare services in both rural and urban areas. In contrast, distance to a maternal health facility centre inhibits decisions to register for and utilize these services in rural India. In addition, awareness of healthy behaviour and factors that affect such knowledge at the household and community level are key determinants of whether maternal-child healthcare services are used. The findings demonstrate that the health status of women and children in India can be improved significantly by strengthening IEC (Information, Education and Communication) efforts on the demand side and reducing access barriers on the supply side.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".