Bibliographic record
Abstract
Based on Becker, Kane, Niskanen, and Peltzman’s ideas, we develop a model to explain why deposit insurance is adopted even though policymakers are aware of its pitfalls in both theory and practice. In our model, the regulator acts as both a bureaucrat and an entrepreneur to maximize his self-interest through administering a deposit insurance scheme. The theory postulates that adoption of deposit insurance is more likely under the following conditions: the scheme is (i) publicly administered and (ii) privately funded, with (iii) non-risk rated insurance premium and (iv) compulsory membership; and there is (v) a larger deposit market with (vi) at least two groups of banks (good vs. bad), (vii) lower government ownership of banks, and (viii) higher economic freedom, such that one group exerts its political influence and gains from deposit insurance. Empirically our theory is supported by the stylized facts, cross-country binary-choice regression results and a case study of Canada.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".