Corruption and Development: The Need for International Investigations with a Multijurisdictional Approach Involving Multilateral Development Banks and National Authorities
Bibliographic record
Abstract
We argue that while Multilateral Development Banks (“MDBs”) and national governments have mechanisms to fight corruption, the objectives and outcomes of these enforcement mechanisms diverge. MDBs are interested in the causes and effects of corruption from a development perspective and, as such, tend to sanction small and medium enterprises and individuals, while national governments are focused on a more punitive outcome, targeting larger multinational corporations. This article examines the enforcement objectives articulated in national legislation, namely the US Foreign and Corrupt Practices Act and its Canadian counterpart, the Corruption of Foreign Public Officials Act, as well as several Canadian cases, on the one hand, and the tools and outcomes of MDBs’ sanctions systems on the other. We conclude that national enforcement efforts and MDBs’ sanctions outcomes intersect in their fight against international corruption in that their results are complementary; the former punishing large-scale offenders while the latter ensuring the integrity of development projects.
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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 | 0.022 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.026 |
| Scholarly communication | 0.017 | 0.033 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".