Providing for Victim Redress within the Legislative Scheme for Tackling Foreign Corruption
Bibliographic record
Abstract
This article examines the prospects for victim redress for the corporate commission of foreign corruption, using Canada as a case study. Such cases are typically addressed by negotiated settlements, with Canada’s new “remediation agreement” regime embracing an intention to provide “reparations for harm done to victims or to the community.” Further work, however, needs to be done on defining who is a victim, with the SNC-Lavalin affair having focussed much attention on employees, pensioners and shareholders, with barely a mention of the overseas victims of the alleged crimes. To this end, the article examines comparable efforts undertaken in England to ensure the interests of the overseas victims of economic crime are taken into account. The creation of a fund to which the financial penalties for foreign corruption could be directed to support the provision of development assistance to affected foreign countries is also considered.\nDans le présent article, nous examinons les perspectives de réparation pour les victimes de corruption commise par les entreprises à l’étranger, en utilisant le Canada comme étude de cas. De tels cas sont généralement réglés par des accords négociés, le nouveau régime canadien d’« accord de réparation » prévoyant de fournir « des réparations pour les dommages causés aux victimes ou à la communauté ». D’autres travaux sont cependant nécessaires pour définir qui est une victime, l’affaire SNC-Lavalin ayant beaucoup attiré l’attention sur les employés, les retraités et les actionnaires, avec à peine une mention des victimes étrangères des crimes présumés. À cette fin, l’article examine les efforts comparables entrepris en Angleterre pour garantir la prise en compte des intérêts des victimes étrangères de la criminalité économique. La création d’un fonds dans lequel les sanctions financières pour corruption étrangère pourraient être versées dans le but de soutenir la fourniture d’une aide au développement aux pays étrangers touchés est également envisagée.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".