Connecting International Organized Crime Research to Policy and Practice: The Strategic Context in the U.S. and the U.K.

• NCJ Number: 234633
• Date Published: November 2010
• Length: 9 pages
• Agencies: NIJ
• Publication Type: Conference Material

Annotation

After providing a background discussion of the role of threat assessment and strategies regarding the threat that international organized crime (IOC) poses to both the United States and the United Kingdom, this paper address measurement and data requirements, whether IOC is a new problem, and the drivers of IOC and their impact on future growth.

Abstract

The United States and the United Kingdom have both conducted threat assessments of IOC that have led to the development of strategic plans to address the threat. Other countries that have conducted threat assessments as a basis for strategy development are Belgium, Canada, the Netherlands, Germany, Sweden, and the Czech Republic. These and other threat assessments of IOC and associated strategies have three elements in common: their use of statistics to indicate the magnitude of IOC, the use of historical analogy or trend analysis to improve understanding of the contemporary situation, and the use of current information to forecast the future growth of IOC. The contents of this paper reflect the discussions of a small expert working group hosted by the U.S. Justice Department's National Institute of Justice for the purpose of exploring the role academic research could play in formulating more accurate or effective threat assessment and strategies for addressing IOC. The primary conclusion from the meeting was that researchers and practitioners have much to offer one another in the process of developing better threat assessment and strategy documents for countering IOC. In the realm of measurement and statistics, a partnership between researchers and practitioners could result in a wider breadth of data and measurement tools. Also, practitioners could consult with historians of organized crime to ensure that analogies are correctly applied and to avoid inaccurate extrapolations when data are not available. 10 notes