Consanguinity and Other Marriage Market Effects of a Wealth Shock in Bangladesh
Bibliographic record
Abstract
This paper uses a wealth shock from the construction of a flood protection embankment in rural Bangladesh coupled with data on the universe of all 52,000 marriage decisions between 1982 and 1996 to examine changes in marital prospects for households protected by the embankment relative to unprotected households living on the other side of the river. We use difference-in-difference specifications to document that brides from protected households commanded larger dowries, married wealthier households, and became less likely to marry biological relatives. Financial liquidity-constrained households appear to use within-family marriage (in which one can promise ex-post payments) as a form of credit to meet up-front dowry demands, but the resultant wealth shock for households protected by the embankment relaxed this need to marry consanguineously. Our results shed light on the socioeconomic roots of consanguinity, which carries health risks for offspring but can also carry substantial benefits for the families involved.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".