The Timing of Elections and Neonatal Mortality: Evidence from India
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 This paper uncovers evidence of political cycles in developmental outcomes in the Indian context. Comparing children born to the same mother, it shows that children born 0–11 months before scheduled state legislative assembly elections have a significantly lower risk of neonatal mortality. The effect of being born just before elections is higher in politically more competitive regions. The paper provides some evidence of the channels behind this result. The usage of prenatal care increases before elections and mothers of children born before elections are more likely to have antenatal checkups and tetanus injections during pregnancy. Components of antenatal checkups, like the probability of having a blood test or an abdominal examination during pregnancy, also increase before elections. The improvement in child health outcomes before elections seems to be driven by a transfer of resources from non-election to election years rather than an overall improvement in child health outcomes.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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