Does Female Reservation Affect Long-Term Political Outcomes? Evidence from Rural India
Why this work is in the frame
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Bibliographic record
Abstract
Although many studies have explored the \n impacts of political quotas for females, often with \n ambiguous results, the underlying mechanisms and long-term \n effects have received little attention. This paper uses \n nation-wide data from India spanning a 15-year period to \n explore how reservations affect leader qualifications, \n service delivery, political participation, local \n accountability, and individuals willingness to contribute \n to public goods. Although leader quality declines and \n impacts on service quality are often negative, gender quotas \n are shown to increase the level and quality of women's \n political participation, the ability to hold leaders to \n account, and the willingness to contribute to public goods. \n Key effects persist beyond the reserved period and impacts \n on females often materialize only with a lag.
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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 | 0.003 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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