The Role of Weather on Schooling and Work of Young Adults in Madagascar
Bibliographic record
Abstract
Abstract We examine the impact of rainfall variability and cyclones on schooling and work among a cohort of teens and young adults in Madagascar. We estimate a bivariate probit model using a panel survey conducted in 2004 and 2011 in this poor island nation, which is frequently affected by extreme weather events. Our results show that negative rainfall deviations and cyclones reduce the probability of attending school and encourage young men and, to a greater extent, women to enter the work force, and they reduce their French and math test scores. Less wealthy households are most likely to experience this school‐to‐work transition in the face of rainfall shocks. The finding is consistent with poorer households having less savings and more limited access to credit and insurance, which reduces their ability to cope with rainfall shortages. We also find that there are both contemporaneous and lagged effects of the weather shocks, and that they are of a similar magnitude. Our findings are robust to the use of a linear probability model, as well as a wide range of definitions of rainfall variations.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".