Preliminary draft. Comments welcome. Do not quote. Lender of last resort policies: from Bagehot to Bailout
Bibliographic record
Abstract
I thank David Longworth for comments, and the Bank of Canada for giving me the time and ideal colleagues to think about these issues. discussions of the need for a lender of last resort often start by stating that British and United States 19th century experience illustrated the need for a lender of last resort; this article reexamines that lesson lenders of last resort emerged in England and the United States in response to banking panics, which in turn reflected legislative restrictions, most importantly on the substitution between bank notes and bank deposits, but also, in the United States, on branching in Canada there were no legislative restrictions of that sort, and, largely as a result, there were no banking panics in Canada and the central bank (the Bank of Canada) was not established until 1934; the need for a lender of last resort is not inherent in a fractional reserve banking system, but depends on the legislative environment; furthermore, the lender of last resort justified in the 19th century environment was one which created market
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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 | 0.007 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.529 | 0.228 |
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".