Bibliographic record
Abstract
The United Kingdom has committed to using the proceeds of deferred prosecution agreements (DPAs) in foreign bribery cases to compensate the victims of corruption in low-income countries. It has executed this policy by making direct payments to foreign governments and injecting capital into infrastructure projects that support vulnerable populations. However, this policy has come under intense scrutiny because the capital put towards compensation is statistically insignificant compared to what the government retains for itself. Seizing on the immediacy of these criticisms, this Article explores why the United Kingdom’s policy of compensating the victims of foreign bribery has faltered and proposes realistic suggestions for improvement to the extant DPA regime. Its aims are threefold. First, to study how victim compensation operates in practice. This involves an interpretation of understudied regulatory guidance documents, an analysis of international best practices with a particular focus on the United States and Canada, as well a description of the normative dimensions of the applicable international law framework. Regarding this last point, the Article argues the United Nations Convention Against Corruption does not require states to share the proceeds of corporate settlement agreements. Second, this Article analyses recent judicial decisions and develops the argument that, in approaching the task of approving corporate settlement agreements, courts and regulators have attempted to transplant principles from adjacent fields of law which have proven wholly inapposite. Decisionmakers have borrowed too heavily from the law regarding compensation orders. These orders, designed to assist individual victims following the conviction of a natural person, have proven unsuitable for corporate corruption cases resolved prior to trial. Relatedly, courts have adopted a narrow understanding of compensation that is fundamentally at odds with the explicit terms of applicable government policy. Finally, this Article advances five proposals for reform which would collectively ensure that compensation is delivered in a greater number of cases.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".