Bibliographic record
Abstract
Too Big to Fail? The Newfoundland Bank Crash of 1894 In the Newfoundland Bank Crash of 1894, the commercial banks in a duopolistic loan market both went under simultaneously. The banking system was "free", as central bank, deposit insurance, and lender of last resort were all absent. The objective of this study is to shed light on our understanding of the working of a duopolistic bank loan market and to provide lessons for banking regulation and policies, the too-big-to-fail doctrine in particular. Our regression results suggest a price leader-follower relationship before 1887, and a drastic decline in exports that year triggered a regime change into simultaneous loan expansion that ultimately precipitated a systemic banking failure. The short-lived liquidity crisis, however, was alleviated by entries of Canadian banks. More important, results of intervention analysis suggest that the Crash did not have any significant adverse impact on the fishery sector, the pillar of the single-resource economy. (JEL E5, G2, N2)
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".