Reducing the Potential for Future Financial Crises: A Framework for Macro-Prudential Policy in Canada
Bibliographic record
Abstract
Canada needs a policy framework and new governance structure beyond what is in place to reduce the potential for future financial crises. The authors make the case for establishing a formal committee with a mandate to identify potential systemic risks and to act promptly before they materialize. While Canada's system of regulating and supervising financial institutions might hold up as a model of good performance, changes can and should be made, say Jenkins and Thiessen. Future crises undoubtedly will have different antecedents than the last one, and we need to be sure that Canada's financial system will be equal to the task of dealing with them as they arise. The authors examine potential arrangements for macro-prudential policy in Canada and conclude that a formal committee is the preferred governance arrangement.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.014 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.022 | 0.020 |
| Insufficient payload (model declined to judge) | 0.005 | 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".