The Foreign Corrupt Practices Act: Toward a Definition of "Foreign Official"
Bibliographic record
Abstract
opportunities and avoiding running afoul of U.S. law. 21 For example, in the energy industry, "the work of navigating ancient kingdoms and secretive relationships has become an integral part of finding new [oil] reserves, . . .[and] has led the industry . . . to the most difficult corners of the earth." 22These energy companies, and other types of businesses, have been targeted in the upswing of DOJ and SEC prosecutions under the FCPA that began in 2004. 23 Likewise, Wal-Mart, which has been rapidly expanding across the globe, found itself in trouble in Mexico in early 2012, and Hollywood studios have had to answer similar questions about their dealings in China and the accompanying FCPA implications. 24 These businesses will also need to conform to the United Kingdom Bribery Act 2010 ("U.K. Act"), which was passed in 2010 and went into effect in July 2011. 25 This statute is even broader in scope and more restrictive than the FCPA, even if some consider it "better crafted," because it is also fairer to firms. 26 The U.K. Act provides a compliance defense, which protects honest firms from suffering the most severe of consequences if a briber was "one rogue employee," and the firm had a clear and effective anti-bribery program. 27 Regardless of the U.K. Act's specific content, there can be no doubt that it presents additional anti-corruption hurdles that global businesses must meet if they want to avoid the courtroom. 28 As can be expected, the enthusiasm of the DOJ and SEC for the FCPA is not shared universally. 29Some have suggested 21.Nathan Vanderklippe, Jumping through hoops to win business in Libya: Canadian corporations face a thicket of ethical questions, hazy laws back home and local government greed, GLOBE & MAIL, Mar.22,
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".