Bibliographic record
Abstract
A major contribution of the public-choice school is the recognition by Gordon Tullock that contestable rents give rise to social losses because of unproductive resource use. Contestable rents usually are politically assigned privileges. Contestable rents can also be found outside of government decisions. We describe the example of rents in academia in different cultures. The primary empirical question regarding rent seeking concerns the magnitude of the social loss from the contesting of rents. Direct measurement is impeded by lack of data and indeed denial that rent seeking took place. Contest models provide guidance regarding social losses. We provide a generalized contest model. Social losses from rent seeking are diminished in high-income democracies because rent seeking usually takes place by groups seeking ‘public good’ benefits. Rents are also less visible in democracies, because political accountability requires that rents be assigned in indirect non-transparent ways. These restraints are not present in autocracies, where rent seeking is also facilitated by corruption and by the need to influence a smaller number of decision makers. Ideology can influence whether rent seeking is recognized to exist.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".