Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper focuses on Canada’s 2025 Financial System Stability Assessment. Canada has a large and highly developed financial system. The banking system is concentrated with six systemically important banks accounting for 94 percent of total banking assets. Nonbank financial institutions (NBFIs) are also important and include mutual and pension funds and insurance firms. The Financial Sector Assessment Program was conducted amid slowing economic growth, trade policy uncertainty, and heightened geopolitical risks. While financial sector oversight and crisis management frameworks are robust, they could be further strengthened to proactively address emerging challenges. Enhancing cooperation and information sharing between federal and provincial authorities is essential to effectively monitor risks across the financial sector, particularly concerning NBFIs. Significant strides have been made to enhance cyber resilience and monitor climate risks and the authorities are encouraged to further build upon these efforts. Anti-Money Laundering/Combating the Financing of Terrorism supervision and enforcement should be strengthened. Safety net schemes would benefit from further harmonization across jurisdictions and the insurance resolution framework should be strengthened.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it