Legislative Action on Human Trafficking: Towards a Data-Driven Policy
David J. Corliss, PhD | September 19 | 2:45-3:45 PM
Topic: Legal, Research | Knowledge Level: Intermediate, Advance | Location: TBD
Previous statistical analysis of state-level human trafficking reporting in the Polaris data has identified demographic, economic, and sociological drivers of human trafficking. This enables a prediction of the number of reported victims to be expected for each state. States with high-performing programs and practices for identifying victims have a higher reported rate than that predicted by demographic and socio-economic drivers alone. This study compares the legislative environment of higher performing states, such as Ohio, to those with fewer reported cases for the same expected underlying rate. In this way, insight is gained as to which legislative actions are more effective in identifying victims. For example, training of emergency room workers is a very effective practice, yet at least 37% states have no such requirement. A statistical model derives data-driven recommendations for which legislative actions have the largest effect in driving the reporting of human trafficking victims.
· Identify and recommend legislative actions effective at identifying more human trafficking victims
· Advocate for more research on data-driven recommendations to combat human trafficking