Mutual Recognition Based on Substituted Compliance: An Integral Component of the SEC’s Mandate
Bibliographic record
Abstract
The U.S. Securities and Exchange Commission (“SEC”) must utilize mutual recognition based on substituted compliance to maintain American preeminence in the global securities market. In fact, mutual recognition based on substituted compliance facilitates the SEC’s ability to fulfill its statutory mandate-- to protect investors; maintain fair, orderly, and efficient markets; and facilitate capital formation. Currently, all US investors may have access to foreign exchanges in the global securities market without the protection of the U.S. federal securities laws; at a minimum, the SEC must take action to fulfill the first prong of its statutory mandate--to protect investors. In addition, maintaining efficient markets and facilitating capital formation requires that U.S. securities markets remain competitive in the U.S. and the global securities market. This article recommends the use of a hybrid model (MRSC), which relies primarily on the framework and key assessment criteria described in the article written by the Director and Senior Counsel of its Office of International Affairs, Ethiopis Tafara, and Robert J. Peterson, respectively, entitled A Blueprint for Cross-Border Access to U.S. Investors: A New International Framework, 48 Harv. Int’l L.J. 31 (Winter 2007), with certain structural modifications from the regulatory framework used to establish Nasdaq Canada in two Canadian provinces—Quebec and British Columbia. Unlike the Tafara and Peterson and Nasdaq Canada models, MRSC focuses exclusively on assessing the regulatory comparability of foreign exchanges for the purpose of exempting the foreign exchange from the registration requirements under § 6 of the Securities Exchange Act; it expressly excludes assessing regulatory comparability of the members of the foreign exchange to exempt the members of the foreign exchange from the registration requirements of the federal securities laws. MRSC is designed to allow the SEC to assess regulatory comparability for foreign exchanges in order to compete effectively in the global securities market.
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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 | 0.033 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".