Declining fertility and increasing use of traditional methods of family planning: a paradox in Uttar Pradesh, India?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Uttar Pradesh (UP), with more than 220 million people, is the most populous state in India. Despite a high unmet need for modern family planning methods, the state has experienced a substantial decline in fertility. India has also seen a decline during this period which can be attributed to the increased prevalence of modern methods of family planning, particularly female sterilisation, but in UP, the corresponding increase was marginal. At the same time, Traditional Family Planning Methods (TMs) increased significantly in UP in contrast to India, where it was marginal. The trends in UP raise questions about the drivers in fertility decline and question the conventional wisdom that fertility declines are driven by modern methods, and the paper aims to understand this paradox. Fertility trends and family planning practices in UP were analysed using data from different rounds of National Family Health Surveys (NFHS) and the two UP Family Planning Surveys conducted by the UP Technical Support Unit to understand whether the use of TMs played a role in the fertility decline. As per NFHS-4, the prevalence of TM in India (6%) was less than half that of UP (13%). The UP Family Planning Survey in 25 High Priority Districts estimated that 22% of women used TMs. The analysis also suggested that availability and accessibiility of modern contraceptives might have played a role in the increased use of TMs in UP. If there are still couples who make a choice in favour of TMs, they should be well informed about the risks associated with the use of traditional methods as higher failure rate is observed among TMs users.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it