Bibliographic record
Abstract
One of the key goals of political economy is to understand how institutional arrangementsshape policy outcomes. This paper studies a comparatively neglected aspect of this - theforces that shape heterogeneous performance of autocracies. The paper develops a simpletheoretical model of accountability in the absence of regularized elections. Leadershipturnover is managed by a selectorate - a group of individuals on whom the leader depends tohold onto power. Good policy is institutionalized when the selectorate removes poorlyperforming leaders from office. This requires that the selectorate's hold on power is not toodependent on a specific leader being in office. The paper looks empirically at spells ofautocracy to establish cases where it has been successful according to various objectivecriteria. We use these case studies to identify the selectorate in specific instances of successfulautocracy. We also show that, consistent with the theory, leadership turnover in successfulautocracies is higher than in unsuccessful autocracies. Finally, we show by exploitingleadership deaths from natural causes that successful autocracies appear to have found waysfor selectorates to nominate successors without losing power - a feature which is alsoconsistent with the theoretical approach.
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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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".