Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it