A Question of Credibility: Enhancing the Accountability and Effectiveness of Credit Rating Agencies
Bibliographic record
Abstract
In the wake of the financial crisis, Credit Rating Agencies (CRAs) have been criticized for having played a significant role in the market turmoil. Numerous reports have identified failures on the part of CRAs that have affected the quality and integrity of the rating process. In light of the critiques, a strong consensus has emerged among policymakers that regulatory intervention is needed. In Canada, the European Union and the United States, policymakers have opted for registration systems. Three major areas of reform should be pursued. The first pertains to the elimination of regulatory references to ratings. The second area relates to the development of a due diligence obligation for institutional investors with respect to the creditworthiness of issuers. The final area of reform concerns the disclosure of information on underlying assets by issuers of structured finance products. Given that these reforms imply important changes to the regulatory landscape, an incremental approach is the preferable route.
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 | 0.130 | 0.476 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.045 |
| Scholarly communication | 0.022 | 0.028 |
| Open science | 0.010 | 0.007 |
| Research integrity | 0.085 | 0.059 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".