Heterogeneous Treatment Under Regression Discontinuity Design: Application to Female High School Enrolment
Bibliographic record
Abstract
Abstract This paper undertakes a regression discontinuity (RD) framework with multiple cutoffs unlike typical RD setting where researchers normalize the score variable and pool all the observations. This paper explores this heterogeneity in the effect of Islamic mayor on female secular high schooling in Turkey using the multiple cutoff RD framework developed in Cattaneo et al . (2016). The presence of many parties in the 1994 municipality election in Turkey means that vote share of the strongest opponent party can vary substantially leading to different cutoffs. Meyersson (2014) finds that Islamic mayors of 1994 promoted female high schooling using a normalized and pooled RD framework, which averages the effect across all the different cutoffs. We extend his work by segregating the effect of Islamic mayor across different opponent party's vote shares. Our results suggest that the positive effect on female secular high school attainment was more pronounced in municipalities where the strongest opponent party was secular than where the opponent was conservative. This heterogeneity can be attributed to a policy change in 1999, which restricted religious high school graduates from entering universities.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".