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Identification of Effective Strategies to Disrupt Recruitment of Victims in Human Trafficking: Qualitative Data, Systems Modeling, Survivors, and Law Enforcement

NCJ Number
Lauren Martin; Kayse Lee Maass; Kelle Barrick; Thomas Sharkey; Amy Farrell; Cynthia Matthias; Barış Tezcan; Martha Williams; Tonique Ayle; Teresa Forliti; Joy Friedman; Mikki Mariotti; Christine Nelson; Camille Brown; Melissa Florey
Date Published
91 pages

This study using a mixed methods approach to gather evidence about recruitment of victims into sex trafficking in order to develop conceptual and analytic models found that relationships structure recruitment networks.


This study found that recruitment networks are structured by relationships and identified how, why, and when at least seven recruitment mechanisms (coercion and force, fraud, belonging, seduction, basic needs, glamorization, and normalization) are used and function. These results illuminate recruitment pathways and can be used to guide public investment and policy toward interventions with promise for preventing recruitment and promoting resilience against recruitment. This project used an innovative, transdisciplinary, and mixed methods approach to gather evidence about recruitment of victims into sex trafficking in order to develop conceptual and analytic models. The goal was to illuminate and understand the complex pathways of recruitment and re-recruitment, interventions and their cascading outcomes on recruitment into trafficking operations, the implications for victim wellbeing, and effects on broader society. This study focused on the state of Minnesota in order to develop a methodology and an approach within the context of one state to reduce logistical barriers and see if models worked. Through a mixed methods research approach that incorporated qualitative and computational modeling and centered lived-expertise from a survivor-centered advisory group, this study uncovered insights into the structure and function of sex trafficking recruitment. In addition to these descriptive and conceptual insights, the authors developed a computational mathematical model called a Markov Chain that models how a person’s susceptibility to being recruited and re-recruited into trafficking is affected by their ability to access services and supports. This model serves two purposes. First, it visualizes the complex recruitment and re-recruitment pathways that victims of trafficking experience from a systemic view of susceptibility. Second, the model can test the potential effectiveness of proposed interventions to prevent recruitment and re-recruitment. The Markov Chain could be used both to explore the effectiveness of current interventions and prospective interventions prior to implementation.