Resilient Leaders and Institutional Reform: Theory and Evidence
Why this work is in the frame
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Bibliographic record
Abstract
Strengthening executive constraints is one of the key means of improving political governance. This paper argues that resilient leaders who face a lower probability of being replaced are less likely to reform institutions in the direction of constraining executive power. We test this idea empirically using data on leaders since 1875 using two proxies of resilience: whether a leader survives long enough to die in office, and whether recent natural disasters occur during the leader's tenure. We show that both are associated with lower rates of leader turnover and a lower probability of a transition to strong executive constraints. This effect is robust across a wide range of specifications. Moreover, in line with the theory, it is specific to strengthening executive constraints rather than generalized political reform.
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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 | 0.000 | 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 | 0.001 |
| 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