Demographic and Socioeconomic Correlates of Neonatal, Post-neonatal and Childhood Mortality in Uttar Pradesh, India: A Study Based on NFHS-2 Data
Bibliographic record
Abstract
Though the levels of infant and child mortality in India have been declining over the years it is still considerably high among the north-central states. This paper using data of National Health and Family Survey (NFHS-2) 1998-99 tries to find out the effects of various spatial demographic and socio-economic factors on neonatal post-neonatal and childhood mortality in the large state of Uttar Pradesh in north-central India. It also tries to reexamine the hypothesis that endogenous (demographic or biological) factors are primarily responsible for neonatal mortality whereas exogenous (socio-economic) factors contribute more in the post-neonatal and childhood period. The results of multivariate analyses broadly confirm the hypothesis though maternal education and length of the preceding birth interval have profound positive effect on survival during all the period; neonatal post-neonatal and childhood. (authors)
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".