International Regulatory Co-operation: Case Studies, Vol. 2
Bibliographic record
Abstract
The world is becoming increasingly global. This raises important challenges for regulatory processes which still largely emanate from domestic jurisdictions. In order to eliminate unnecessary regulatory divergences and to address the global challenges pertaining to systemic risks, the environment, and human health and safety, governments increasingly seek to better articulate regulations across borders and to ensure greater enforcement of rules. But, surprisingly, the gains that can be achieved through greater co-ordination of rules and their application across jurisdictions remain largely under-analysed. This volume complements the stocktaking report on International Regulatory Co-operation: Rules for a Global World by providing evidence on regulatory co-operation in the framework of the Canada-U.S. Regulatory Cooperation Council, as part of EU energy regulation, under the Global Risk Assessment Dialogue, and in the area of prudential regulation of banks. The four case studies provided in this volume follow the same outline to allow for comparison.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".