Bibliographic record
Abstract
We assume that even though voters prefer the policies of their favoured leader they value democracy more greatly. This means that voters on both sides of a polarised policy divide would be willing to sacrifice their preferred policy if it would mean preserving democracy. However voters on one side are unsure whether voters on the other side share this commitment to democracy. We show that in such a situation an autocratic populist leader can act in ways that will undermine opposing voters beliefs that the leader’s supporters continue to value democracy. If these beliefs become pessimistic enough, a self-reinforcing cycle of mutual suspicion between voters on opposing sides leads to the inexorable demise of democracy and its replacement by autocratic rule. Understanding this, an elected leader who aspires to rule via non-democratic means may follow such autocratic populist policies in order to entrench their rule. JEL Classifications: D72, P16, P17, P48
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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 | 0.018 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".