Polygyny and Farm Households' Resilience to Climate Shocks
Bibliographic record
Abstract
Climate change and weather shocks pose major challenges for household income security and well-being, especially for smallholder farmers’ communities. In such communities, imperfect risk insurance and labor markets may induce households to use traditional institutions such as polygyny to harness their size and composition to their resilience strategies against these shocks. This paper tests this hypothesis by analyzing how polygyny’s interaction with droughts affects crop yields. For identification, the paper relies on the spatial variation in polygyny’s prevalence across Mali’s rural communes and the randomness of drought episodes. The findings show that polygynous communities are more resilient to drought-induced crop failure. Exploration of the mechanisms shows that polygynous communities diversify their income sources more than monogamous ones, including via child marriage—a phenomenon known to undermine women’s outcomes. As the literature links polygyny to underdevelopment, interventions to eliminate it should make formal resilience and adaptation strategies available to drought-prone communities. Failure to do so may entrench political opposition to enforcing a ban on polygyny and child marriage.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".