Bibliographic record
Abstract
The four essays published here provide a useful overview for anyone interested in understanding the issues and policy environment surrounding financial system stability. The first three essays consider different aspects of the question, What is financial stability/instability? The first essay, by John Chant, Special Adviser at the Bank in 2001–02, considers how financial instability differs from other kinds of instability, how it is different from the volatility normally associated with a well-functioning financial system, and how instability can be propagated within the financial system and to the real economy. In the second essay, Alexandra Lai tackles some of the problems raised by Chant; in particular, the difficulty of understanding the nature of crises. She reviews a range of theoretical approaches that have been pursued in order to understand the potential instabilities in domestic financial systems. In his essay, Mark Illing provides four case studies of episodes often thought of as periods of financial stress or crisis—the stock market crash of October 1987, the near-collapse of Long-Term Capital Management in 1998, the failures of the Canadian Commercial Bank and the Northland Bank in 1985, and the Bank of New York's 1985 computer problem. The fourth essay, by Fred Daniel, provides a context for more general discussions of the role of policy in promoting financial stability, by providing an overview of the current institutional arrangements that condition financial behaviour in Canada and how the Bank of Canada interacts with other agencies who share responsibility for financial stability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".