Bibliographic record
Abstract
Purpose - The purpose of this paper is to identify and examine motivating factors for why public and private actors initiate costly and risky civil actions to recover loss due to corruption in an era of increasing multilateral consensus and cooperation against corruption and organised crime. Design/methodology/approach - Research into recent global trends and types of civil lawsuits against corruption is conducted. Several cases, particularly from Canada, Hong Kong, the USA and the UK, are used to illustrate the attractions and difficulties of civil litigation. The implications of the recent international treaties on corruption are analyzed. Qualitative findings are made on a range of motivational factors that lie behind different types of civil actions against corruption. Findings - The paper notes an apparent rise in interest in civil actions against corruption and describes five types of actions brought by governments and companies. Civil actions are indicative of the want of better alternatives to recovery. While recent anti‐corruption treaties help to remove barriers to civil actions, the treaties themselves cannot explain the increased interest in civil lawsuits. Full explanation lies in the empowering effect of suing, the political significance of these lawsuits particularly for a new regime suing to recover plundered property from the old regime, and the ease by which a lawsuit can be launched. Originality/value - This paper contributes to the literature in identifying types of civil actions against corruption, the practical and political motivations behind civil actions, and the positive relationship between international cooperation regimes and civil actions.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".