The Emergence of Political Accountability*
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
Abstract When and how do democratic institutions deliver accountable government? In addressing this broad question, we focus on the role played by political norms—specifically, the extent to which leaders abuse office for personal gain and the extent to which citizens punish such transgressions. We show how qualitatively distinct political norms can coexist because of a dynamic complementarity, in which citizens’ willingness to punish transgressions is raised when they expect such punishments to be used in the future. We seek to understand the emergence of accountability by analysing transitions between norms. To do so, we extend the analysis to include the possibility that, at certain times, a segment of voters are (behaviorally) intolerant of transgressions. Our mechanism highlights the role of leaders, offering an account of how their actions can instigate enduring change, within a fixed set of formal institutions, by disrupting prevailing political norms. We show how such changes do not depend on “sun spots” to trigger coordination, and are asymmetric in effect—a series of good leaders can (and eventually will) improve norms, whereas bad leaders cannot damage them.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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) | 0.001 | 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