The dictator’s dilemma: The distortion of information flow in autocratic regimes and its consequences
Bibliographic record
Abstract
Humans have been arguing about the benefits of dictatorial versus democratic regimes for millennia. Despite drastic differences between the dictatorships in the world, one of the key common features is the Dictator’s Dilemma as defined by Wintrobe [1] : a dictator will never know the true state of affairs in his country and is perpetually presented distorted information, thus having difficulties in making the right governing decisions. The dictator’s dilemma is essential to most autocratic regimes and is one of the key features in the literature on the subject. Yet, no quantitative theory of how the distortion of information develops from the initial state has been developed up to date. I present a model of the appearance and evolution of such information distortion, with subsequent degradation of control by the dictator. The model is based on the following fundamental and general premises: a) the dictator governs aiming to follow the desired trajectory of development based only on the information from the advisors; b) the deception from the advisors cannot decrease in time; and c) the deception change depends on the difficulties the country encounters. The model shows effective control in the short term (a few months to a year), followed by instability leading to the country’s gradual deterioration of the state over many years. I derive some universal parameters applicable to all dictators and show that advisors’ deception increases parallel with the decline of the control. In contrast, the dictator thinks the government is doing a reasonable, but not perfect, job. Finally, I present a match of our model to the historical data of grain production in the Soviet Union in 1928–1940.
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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".