International Regulatory Cooperation: Agency Efforts Could Benefit from Increased Collaboration and Interagency Guidance
Bibliographic record
Abstract
A letter report issued by the Government Accountability Office with an abstract that begins "All seven U.S. regulatory agencies that GAO contacted reported engaging in a range of international regulatory cooperation activities to fulfill their missions. These activities include the United States and its trading partners developing and using international standards, recognizing each other's regulations as equivalent, and sharing scientific data. U.S. agency officials GAO interviewed said they cooperate with foreign counterparts because many products they regulate originate overseas and because they may gain efficiencies--for example, by sharing resources or avoiding duplicative work. Cooperation can address both existing and avoid future regulatory differences. Officials also explained how cooperative efforts enhance public health and safety, facilitate trade, and support competitiveness of U.S. businesses. Several U.S. interagency processes require or enable interagency collaboration on international cooperation activities. The Regulatory Working Group (RWG), chaired by OMB and the Trade Policy Staff Committee (TPSC) are forums that have different responsibilities related to the regulatory and trade aspects of international regulatory cooperation. U.S. regulatory agency officials said the current processes could benefit from better information sharing among agencies on the implementation of international cooperation activities and lessons learned. Without enhancements to current forums, opportunities to share practices and improve outcomes could be missed. Executive Order 13609, issued in May 2012, tasked the RWG with enhancing coordination and issuing guidance on international regulatory cooperation, which the RWG is developing. Nonfederal stakeholders GAO interviewed reported challenges to providing input on U.S. agencies' international regulatory cooperation activities, in particular that they are not always aware of many of these activities and participation can be resource intensive."
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 | 0.144 | 0.192 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.039 | 0.036 |
| Open science | 0.005 | 0.031 |
| Research integrity | 0.026 | 0.021 |
| Insufficient payload (model declined to judge) | 0.048 | 0.019 |
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".