Open Access. Powered by Scholars. Published by Universities.®
- Publication
- File Type
Articles 1 - 2 of 2
Full-Text Articles in Law
Neither Savior Nor Bogeyman: What Waits Behind The Door Of Third-Party Litigation Financing?, Jeremy Kidd
Neither Savior Nor Bogeyman: What Waits Behind The Door Of Third-Party Litigation Financing?, Jeremy Kidd
Jeremy Kidd
The arguments for and against third-party litigation financing are based on incorrect assumptions regarding the impacts on total litigation. A formal model incorporating the choices of plaintiff, lawyer, and financier shows only minimal impact on total litigation, largely positive. However, after addressing the potential for long-term, strategic behavior by financiers, it is obvious that some dangers remain. Divorced from the dramatic claims of proponents and opponents, litigation financing is merely a tool that can be used for good or bad, and differentiating by types of claims and the incentives of the parties allows that tool to be appropriately used.
What's Good In Theory May Be Flawed In Practice: Potential Legal Consequences Of Poor Implementation Of A Theoretical Sample, Melanie S. Williams, A. Lynn Phillips, G. Michael Phillips
What's Good In Theory May Be Flawed In Practice: Potential Legal Consequences Of Poor Implementation Of A Theoretical Sample, Melanie S. Williams, A. Lynn Phillips, G. Michael Phillips
Melanie S. Williams
The article discusses the problem of the use in litigation of statistical sampling. Sample-based research is increasingly used in cases as diverse as products liability, antitrust, intellectual property, and criminal law, among others. Sample-based research provides objective evidence upon which decisions, damages and liability may rest. Despite its importance, however, statistical evidence is often misused and misunderstood by attorneys who may be unfamiliar with the underlying form of analysis. The paper explores common errors when using litigative samples, comments upon best practices for the use in law of sample-based research, and demonstrates the importance of sound statistical sampling and data …