Description of original award (Fiscal Year 2022, $1,187,000)
Labor and sex trafficking continues to be on the agendas of federal, state, and local authorities. Reports and laws state the need for more and higher-quality human trafficking data. Human trafficking efforts by stakeholders, including the government, law enforcement, service providers, lawyers, nonprofit agencies, and researchers, call for reliable data collection and analysis. Southern Methodist University’s (SMU) Human Trafficking Project (“Project”) directly addresses the deficiencies in data collection and analysis and in the collaboration of expertise needed to ensure data efficacy and complete effective human trafficking research.
The Project will construct the SMU Human Trafficking Data Warehouse (“Data Warehouse”), create a human computational-machine learning game to scrape and complete human trafficking datasets, and consult with stakeholders who own datasets, are interested in collecting data, and have the need for human trafficking data for anti-human trafficking research and work. Research will determine the link between economics and human trafficking, the cost of doing nothing about human trafficking, the spatial and temporal patterns in human trafficking data and disparities in outcomes, and how to extract and complete human trafficking datasets using the integration of human-in-the-loop machine learning via human computation gaming.
The Data Warehouse provides for the secure collection, storage, cleaning, and filling in the gaps of the wide variety of human trafficking data types and sources. The Data Warehouse will be available to stakeholders with existing sources of human trafficking data as well as organizations and individuals involved in anti-trafficking work who are interested in collecting data. New methods will be used involving human computation gaming and machine learning to scrape and clean up data from additional sources that can be overlapped with existing data sources to create more robust data. During the course of the Project, plans will be formulated on how to best use data visualization to present data for dissemination in a format and method that practitioners, policy makers, and researchers can easily access, understand, and use.
SMU’s unique collaborative setting allows economics, information technology, gaming, public policy, law, education, theology, and other disciplines to come together to solve world problems. SMU contains vast resources, such the expertise of SMU Guildhall, the top computer gaming school, the super computer ManeFrame, SMU’s research centers, departments, and libraries, an interdisciplinary research group, and a law school.
This Project will invest in building expertise to drive effective research, policy making, and practice. This is done through the creation of interdisciplinary research teams made up of experts within and external to SMU. We also provide funding for postdoctoral, graduate, and undergraduate research in order to train new human trafficking researchers.
Competition by rival organizations and partnership for limited funding is a major problem in the anti-trafficking space. SMU works as an independent agency to coordinate government and nongovernment organizations, practitioners, and researchers to come together to solve issues related to human trafficking. We will provide expertise and resources to task forces, coalitions, and agencies in the U.S. and abroad.
The Project directly addresses the goals of the Byrne Discretionary Grants Program by collecting relevant data and conducting research that will work to improve the functioning of the criminal justice system, by addressing the human trafficking of juveniles, and by assisting organizations and individuals that work to improve the lives of victims of human trafficking. The Project targets one of the main goals of the Department of Justice to provide data, analysis, consultation, and collaboration that leads to the prevention and control of the crime of human trafficking and the just punishment for those guilty of human trafficking. “nca/ncf”
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