Contraception in India: Exploring Met and Unmet Demand
Bibliographic record
Abstract
Our study examines factors influencing demand for contraception for spacing as well as for limiting births in India. Data on socio-economic, demographic and program factors affecting demand for contraception in India are from the National Family Health Survey, 1998--99. The recent document from the National Rural Health Mission has completely ignored the use of contraception in controlling fertility in India. Empirical results of our study suggest giving priority to and focusing attention on supply-side factors such as a regular and sustained supply of quality contraceptive methods to improve accessibility and affordability. Further, strengthening the information, education and communication (IEC) component of the reproductive and child health (RCH) package would allay misapprehensions about the side effects and health risks of contraception. Focusing attention on demand-side factors such as women's empowerment through education, gainful employment and exposure to mass-media would help reduce the unmet demand for family planning. The resulting reduction in fertility would hasten the process of demographic transition and population stabilization in India.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".