The effect of extreme weather events on the frequency of child marriage: A systematic review of the evidence
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
Abstract Child marriage is considered a human rights violation, and its elimination is an explicit target of the United Nations Sustainable Development Goals. However, there is growing concern that climate change may be threatening efforts to eliminate child marriage. We conducted a systematic review to synthesise quantitative research on the relationship between climate change and child marriage and assess the risk of bias across these studies. We identified 18 studies from an interdisciplinary range of databases. Several studies found that child marriage was correlated with droughts and floods. However, because of the high risk of bias across studies, differences in the vulnerability of the populations studied, and differences in the definitions of extreme weather used, we are unable to draw broad conclusions about whether extreme weather events increase or decrease the rate of child marriage. We discuss common biases across studies and provide suggestions for improving the strength of evidence on this topic.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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