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This fourth episode in the season for “Research and Considerations for Sexual Assault Cases” of the National Institute of Justice’s (NIJ’s) Just Science podcast series is an interview with Dr. Rachel Lovell, Research Assistant Professor at Case Western Reserve University, and Mary Weston, Assistant Prosecuting Attorney at the Cuyahoga County Prosecutor’s Office, who discuss a recently published article that details the case for an “Investigate all” approach to sexual assault kit potential evidence.
Background information for the interview notes that as more jurisdictions submit for analysis their previously untested sexual assault kits, the analyses are finding that many submissions of DNA findings do not result in a CODIS match. The issue addressed in the presented interview is whether investigators should continue their investigative efforts even though there is not an immediate suspect identified through a CODIS submission and match. In the current interview, Dr. Rachel Lovell and Mary Weston argue for investigating all previously untested sexual assault kits, whether or not there is a CODIS hit. Based on their joint research regarding the benefits of the analytical processing of sexual assault kits, even though there is no DNA found or no CODIS matches, they conclude that the testing of all sexual assault kits is cost-effective. Among the benefits, even without a CODIS DNA match, is the discovery of the patterns of a serial rapist when the same DNA is found in more than one case, the ability to obtain a conviction based on the DNA prior to a subsequent arrest, increased cooperation from a sexual assault victim, and evolving ability to determine an increasing number of physical characteristics of a suspect from DNA, even though there is no direct match with a known person’s DNA.
- What happens when sexual assault kits go untested? A focal concerns analysis of suspect identification and police pre-arrest decisions
- A Problem in Forensic Science Highlighting the Differences between the Bayes Factor and Likelihood Ratio
- The A Posteriori Probability of the Number of Contributors When Conditioned on an Assumed Contributor