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                            Library & Multimedia
 A transdisciplinary approach for generating synthetic but realistic domestic sex trafficking networks
NCJ Number
              306219

Author(s)
          Daniel Kosmas;
                        Christina Melander;
                        Emily Singerhouse;
                        Thomas C. Sharkey;
                        Kayse Lee Maass;
                        Kelle Barrick;
                        Lauren Martin
Date Published

February 2023
Annotation
              Since one of the major challenges associated with applying Operations Research (OR) models to disrupting human trafficking networks is the limited amount of reliable data sources readily available for public use, since operations are intentionally hidden to prevent detection, and data from known operations are often incomplete, to help address this data gap, the authors propose a network generator for domestic sex trafficking networks by integrating OR concepts and qualitative research.
Abstract
              To help address this data gap, the authors propose a network generator for domestic sex trafficking networks by integrating OR concepts and qualitative research. Multiple sources regarding sex trafficking in the upper Midwest of the United States have been triangulated to ensure that networks produced by the generator are realistic, including law enforcement case file analysis, interviews with domain experts, and a survivor-centered advisory group with first-hand knowledge of sex trafficking. The output models the relationships between traffickers, so-called “bottoms”, and victims. This generator allows operations researchers to access realistic sex trafficking network structures in a responsible manner that does not disclose identifiable details of the people involved. The authors demonstrate the use of output networks in exploring policy recommendations from max flow network interdiction with restructuring. To do so, they propose a novel conceptualization of flow as the ability of a trafficker to control their victims. The results show the importance of understanding how sex traffickers react to disruptions, especially in terms of recruiting new victims. (Published abstract provided)
      
  
          Additional Details
Grant Number(s)
        2020-R2-CX-0022


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)


  
  
        
  Award
        Disrupting Human Trafficking Networks through Mathematical Modeling: Addressing Replacement Effects and Uncertain Information
    
  
  
Date Published: February 1, 2023
    
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