Banks on the Brink: Global Capital, Securities Markets, and the Political Roots of Financial Crises
Bibliographic record
Abstract
This innovative analysis investigates a complex issue of tremendous economic and political importance: what makes some countries vulnerable to banking crises, while others emerge unscathed? Banks on the Brink explains why some countries are more vulnerable to banking crises than others. Copelovitch and Singer highlight the effects of two variables in combination: foreign capital inflows and the relative prominence of securities markets in the domestic financial system. Foreign capital is the fuel for banks' potentially dangerous behavior, and banks are more likely to take on excessive risks when operating in a financial system with large securities markets. The book analyzes over thirty years of data and provides historical case studies of two key countries, Canada and Germany, each of which explores how political decisions in the 19th and early-20th centuries continue to affect financial stability today. The analyses in this book have crucial policy implications, identifying potential regulations and policies that can work to protect banking systems against future crises.
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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 | 0.001 |
| 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 | 0.001 | 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".