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
Economists who believe that government is essentially benevolent tend to regard inter-governmental competition as a source of negative externalities that lower welfare. In contrast the public choice perspective, particularly that motivated by the Leviathan model, sees such competition as potentially beneficial. This paper considers a world consisting of politicians of both kinds -- self-interested and welfare maximizing. However, imperfect information prevents identification of the latter. We model the political equilibrium of the model and then examine the consequences of introducing competition for mobile resources or yardstick competition. In both cases there is a trade-o# between e#ects on politician discipline and selection. Contrary to the existing view, we show that competition is most likely to be welfare improving for voters when it is more likely that politicians are benevolent and bad for welfare when it is most likely that politicians are of the rent seeking type. # We are grateful to a number of seminar participants for helpful comments. 1 1
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.013 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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