Bibliographic record
Abstract
This Technical Note focuses on Systemic Risk Analysis in Canada. The financial system has remained stable amid sizable swings in output, inflation, and interest rates. Structural vulnerabilities persist among Canadian households, with high debt levels and rising debt-servicing costs compared to G7 peers. The corporate sector has remained resilient despite sluggish growth during the pandemic and tighter financial conditions thereafter. However, a materialization of downside macroeconomic risks could impact the financial sector through several channels. Financial Sector Assessment Program bank solvency stress tests indicate that the seven Canadian systemic Debt-to-Income (DTIs) are resilient to the adverse scenario. Liquidity stress tests show that the systemic DTIs are overall liquid and resilient to sizable withdrawals of funding and market valuation shocks. An interconnectedness and contagion analysis evaluated the impact of funding and credit shocks among the six Domestic Systemically Important Banks and across sectors and borders. This interconnectedness, and the associated risks, require vigilant monitoring and analysis to identify potential vulnerabilities that could emerge in times of stress.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.317 | 0.061 |
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".