Review of Fragile by Design: The Political Origins of Banking Crises and Scarce Credit by Charles Calomiris and Stephen Haber
Bibliographic record
Abstract
In Fragile by Design: The Political Origins of Banking Crises and Scarce Credit, Charles Calomiris and Stephen Haber hope to establish explanations for banking outcomes by researching through the lens of not just economics, but political science and history. They use case studies of five different countries to assist them in this task: Britain, the United States, Canada, Mexico, and Brazil. Through an investigation of each country’s unique history and governmental structure, Calomiris and Haber compare and contrast the development of each country’s banking system. For example, the United States has experienced 12 banking crises since 1840 but Canada has had zero. Through the case studies, Calomiris and Haber attempt to find out why. The book suggests that a country’s financial sector is determined by a process labeled the “Game of Bank Bargains” where politics and banking become intertwined, and powerful coalitions and incentives become extremely important. Thus how political institutions and coalitions differ explain the unique banking outcomes of different countries.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".