Foreign Investment: Laws and Policies Regulating Foreign Investment in 10 Countries
Bibliographic record
Abstract
A letter report issued by the Government Accountability Office with an abstract that begins "Foreign acquisitions of U.S. companies can pose a significant challenge for the U.S. government because of the need to balance the benefits of foreign investment with national security concerns. The Exon-Florio amendment to the Defense Production Act authorizes the President to suspend or prohibit foreign acquisitions of U.S. companies that may harm national security. To better understand how other countries deal with similar challenges, GAO was asked to identify how other countries address the issues that Exon-Florio is intended to address. Specifically, this report describes selected countries' (1) laws and policies enacted to regulate foreign investment to protect their national security interests and (2) implementation of those laws and policies. This report updates a 1996 GAO report that describes how four major foreign investors in the United States--France, Germany, Japan, and the United Kingdom--monitored foreign investment in their own countries to protect national security interests. It also examines foreign investment in six additional countries: Canada, China, India, the Netherlands, Russia, and the United Arab Emirates (UAE). GAO reviewed selected laws and regulations and interviewed foreign government officials and others concerning their implementation and any planned changes to their foreign investment laws, regulations, and policies."
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".