Final Report: Combating Wildlife Crime Toolkit (version 1.3)

This indicator is linked to Key Result 11.4, which is part of Group Box 11, "Increased risks for wildlife criminals." The indicator is relevant for activities applying strategic approaches 2-8 and 10 in the toolkit, which all include Group Box 11. The probability of conviction is defined as the likelihood that prosecution for a given wildlife (or associated) crime will result in a conviction. It is calculated as the number of prosecuted wildlife (or associated) crimes that result in conviction divided by the total number of prosecuted wildlife (or associated) crimes. The indicator is derived from USFWS 2014, Rosero 2010, and Akella & Cannon 2004. Conviction is defined as a criminal prosecution of an individual resulting in a formal declaration of guilt by the authorities in the same jurisdiction as the arrest was made. Prosecuted wildlife (or associated) crimes are instances of criminal proceedings being brought against an individual for a wildlife (or associated) crime by the authorities in the same jurisdiction as the arrest was made. Associated crimes include, but are not limited to, money laundering, trafficking in narcotics or timber, document fraud, tax evasion, corruption and bribery, and non-payment of fees. Higher values for this indicator are considered better, assuming a fair and just system where those who are innocent are found innocent. However, it is essential to note that the data available to track this indicator may be biased toward lower-level perpetrators, and project teams should consider designing indicators that incentivize the capture of the largest-impact criminals. The data source for this indicator is official records held by relevant authorities within jurisdictions. The design of data collection instruments and protocols for data collection and analysis should be informed by robust statistical methodologies and best practices in the field. Implementers should respect data ownership rights as well as data sensitivity issues, and all data collected should be archived and made available through the Development Data Library (DDL) per ADS Chapter 579, USAID Development Data. The frequency at which these data are measured will depend on the type of evidence, available survey techniques, and available records. Data should be reported at least annually. An initial baseline measure must be established, and the general basis on which targets are set for the indicator should be explained.