Secular changes in child marriage and secondary school completion among rural adolescent girls in India
Bibliographic record
Abstract
BackgroundChild marriage (<18 years) and school drop-out disproportionately affect girls living in impoverished households in rural areas, with long-term economic and health consequences.Improving retention in education, and delaying age at marriage and first pregnancy have received substantial attention at the national and global level, in line with the Millennium Development Goals and the Sustainable Development Goals (SDGs) (2015-2030). MethodsWe examined changes over time in economic, education and child marriage indicators among adolescents from rural households in (i) Northern Karnataka (the most deprived region of Karnataka), (ii) Karnataka state, and (iii) all India, using individualized data from four pre-existing, nationally-representative datasets (District Level Household and Facility Surveys (DLHS 2-4) (2002/4-2012/3) and the National Family Health Survey (NFHS-4) (2015-16)). ResultsAt the national and state level, we found large improvements in secondary educational attainment among girls and boys living in rural settings (proportion of adolescents completing age-appropriate secondary school education (all India): girls 12.4% 2002/3 vs. 31.6%2015/6; boys 18.9% 2002/4 vs. 36.8%2015/6).We also observed large reductions in child marriage and early child-bearing rates (proportion of married women aged 18-24 years married <18 years: 62.4% 2002/4 vs. 23.8%2015/6; proportion of married girls aged <19 years who are pregnant or have children: 62.4% 2002/4 vs. 21.9%2015/6).In addition, we found evidence of "clustered deprivations", whereby girls in rural areas from the poorest families and lowest castes continue to experience multiple forms of disadvantage, with child marriage significantly associated with scheduled caste / scheduled tribe (SC/ST) caste (odds ratio (OR)=1.25,95% confidence interval (CI)=1.18-1.32),poorest quintile (OR=2.38,95% CI=2.21-2.55)and illiteracy (OR=2.09,95% CI=1.95-2.23);and not completing secondary education significantly associated with SC/ST caste (OR=1.52,95% CI=1.45-1.59),poorest quintile (OR=4.17,95% CI=3.90-4.46),and child marriage (OR=2.05,95% CI=1.85-2.26). ConclusionsThe results show substantial improvements in economic, educational and child marriage indicators at the state and national level over the past 14 years.The government has implemented multiple programmes and policies to address child marriage and school drop-out, and these trends suggest such efforts may be having a positive impact.If India is to achieve the SDGs, designing targeted interventions to reach those who continue to be left furthest behind is going to be key.Child marriage, defined as marriage under the age of 18 years, is associated with a range of adverse economic and health outcomes, including inter-generational poverty, early and inadequately spaced pregnancies, intimate partner violence, poor mental health, poor utilization of maternal health services, maternal and child mortality, and
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".