Comments on the September 29, 2014 FSB Consultative Document, ‘Cross-Border Recognition of Resolution Action’
Bibliographic record
Abstract
This CIGI Paper No. 51 was released on December 3, 2014 by the Centre for International Governance Innovation (CIGI) as a response to the Financial Stability Board’s (FSB) Consultative Document, “Cross-Border Recognition of Resolution Action.” Principally authored by CIGI Senior Fellow Steven L. Schwarcz (who works with the think tank’s International Law Research Program), the Paper comments on the policy measures proposed by the FSB, an international body that monitors and makes recommendations about the global financial system, to address the cross-border legal uncertainties of troubled systemically important financial firms. In that context, the Paper explains why a statutory approach is more effective than a contractual approach at removing obstacles in cross-border resolutions of those firms, and thus a better method to achieve financial stability. The Paper also recommends that the FSB establish a working group on statutory mechanisms for the cross-border resolution of financial firms.
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 | 0.012 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.049 | 0.023 |
| Insufficient payload (model declined to judge) | 0.052 | 0.031 |
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".