Bibliographic record
Abstract
We posit the problem of an autocrat who has to allocate access to the executive positions in his inner circle and define the career profile of his own insiders.Statically, granting access to an executive post to a more experienced subordinate increases political returns to the post, but is more threatening to the leader in case of a coup.Dynamically, the leader monitors the capacity of staging a coup by his subordinates, which grows over time, and the incentives of trading a subordinate's own position for a potential shot at the leadership, which defines the incentives of staging a palace coup for each member of the inner circle.We map these theoretical elements into structurally estimable hazard functions of terminations of cabinet ministers for a panel of postcolonial Sub-Saharan African countries.The hazard functions initially increase over time, indicating that most government insiders quickly wear out their welcome, and then drop once the minister is fully entrenched in the current regime.We argue that the survival concerns of the leader in granting access to his inner circle can cover much ground in explaining the widespread lack of competence of African governments and the vast heterogeneity of political performance between and within these regimes.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 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".