Description of original award (Fiscal Year 2019, $499,483)
The proposed study will leverage past work on measuring human trafficking and apply proven methods in novel ways to advance the methodology for trafficking prevalence estimation.
The proposed project uses a mixed-methods approach to study the prevalence of trafficking victimization, using the hidden prevalence estimation (HPE) method. The HPE method uses administrative data from institutions where victims intersect with jail systems and providers of social services (e.g., homeless shelters, jail booking facilities, hospital emergency departments) to sample individuals. The proposed total sample size is 700 subjects.
The estimation method relies on calculating the probability that people within the county will appear at the places of collection, allowing the applicant to model the size of the entire population relative to the size of the general population.
The project team will partner with several agencies in a single state. The project team will also partner with a local organization (e.g., university, survey firm) to assist in survey data collection.
Given that these findings will be particularly relevant for both practitioners and policymakers, the applicant will develop policy briefs and presentations for targeted audiences, such as investigators, prosecutors, healthcare and social service providers, legislators, and managers of local, state, and federal agencies.
"Note: This project contains a research and/or development component, as defined in applicable law," and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14). CA/NCF.
- Examining the Black Box: A Formative and Evaluability Assessment of Cross-sectoral Approaches for Intimate Partner and Sexual Violence
- Access to Justice for Adolescents and Young Adults Experiencing Intimate Partner Violence: Effectiveness and Accessibility of Civil Protection Orders
- Preventing the next sext: A behavioral economic approach to understanding nude photo sharing decisions in a high school community