Minimum Marriage Age Laws and the Prevalence Of Child Marriage and Adolescent Birth: Evidence from Sub-Saharan Africa
Bibliographic record
Abstract
CONTEXT: The relationship of national laws that prohibit child marriage with the prevalence of child marriage and adolescent birth is not well understood. METHODS: Data from Demographic and Health Surveys and from the Child Marriage Database created by the MACHEquity program at McGill University were used to examine the relationship between laws that consistently set the age for marriage for girls at 18 or older and the prevalence of child marriage and teenage childbearing in 12 Sub-Saharan African countries. Countries were considered to have consistent laws against child marriage if they required females to be 18 or older to marry, to marry with parental consent and to consent to sex. Associations between consistent laws and the two outcomes were identified using multivariate regression models. RESULTS: Four of the 12 countries had laws that consistently set the minimum age for marriage at 18 or older. After adjustment for covariates, the prevalence of child marriage was 40% lower in countries with consistent laws against child marriage than in countries without consistent laws against the practice (prevalence ratio, 0.6). The prevalence of teenage childbearing was 25% lower in countries with consistent minimum marriage age laws than in countries without consistent laws (0.8). CONCLUSION: Our results support the hypothesis that consistent minimum marriage age laws protect against the exploitation of girls.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".