Aging gracefully? Why old autocrats hold competitive elections
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
This article examines the conditions under which dictators hold competitive elections, and looks specifically at the role played by a dictator’s age. Drawing on previous studies arguing that uncertainty increases the likelihood of competitive elections, I argue that as a dictator ages, uncertainty over the future increases within the regime, because government insiders’ expected payoffs for supporting the incumbent decline as s/he ages. As a result, I argue that older dictators are more likely to hold competitive elections in order to reduce uncertainty. The article also tests an implication of the argument: if uncertainty over the future drives elections, then it should be mitigated in regimes with a clear successor. Using a large-N, cross-national dataset on autocrats and competitive elections between 1960 and 2012, this article examines the argument and finds that as dictators age, they are more likely to hold competitive elections, all else equal. The analysis also finds that the effect of autocrats’ age on competitive elections is mitigated in one-party regimes where there exists an established succession rule, while the effect is more apparent in personalist regimes without such a system.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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