A Comparison of Global and U.S. Human Trafficking Structures: UNODC vs. IOM/Polaris Datasets

Vernon Murray, PhD | September 20 | 9:00-10:00 AM

Topic: Research | Knowledge Level: Intermediate, Advanced | Location: TBD

Employing the Murray, Dingman, Porter, and Otte (2015) framework of nine human trafficking situations, the researchers computed two global trafficking structure frequency distributions. The first distribution was based on (N = 1,300+) coded United Nations Office on Drugs and Crime Human Trafficking Case Law database cases. Results indicate that 20% of victims are "Willing Assimilators," 30% are "Tricked and Trapped," and 40% have been "Trapped and Robbed." However, the ratios differ for the International Organization for Migration/Polaris data (N = 55,000+). Here, 55% are Willing Assimilators, 25% are Trapped and Robbed, and the remaining eight (out of nine) victim categories are all below 10%.  Overall, the findings suggest a global need for social marketing interventions to encourage economic development for Willing Assimilators (i.e. financially desperate voluntary victims). Global awareness campaigns regarding "trust assessment" would help reduce the incidence rate among the Tricked and Trapped (i.e. lured in and then enslaved). Finally, global social marketing efforts to encourage more effective law enforcement would help reduce incidence among the Trapped and Robbed (i.e. forced and coerced). The differences between the trafficking structures generated by the two datasets may be due to selection bias. For instance, anecdotal evidence suggests prosecutors target cases with the best chances of winning—hence, bias in the UNODC dataset. Similarly, the IOM/Polaris victims who called hotlines or presented at help stations may not represent a random sample of victims.

Presentation Objectives:

·  Describe the Murray et al. (2015) framework of human trafficking situations

·  Define the nine human trafficking victim situations based on the above framework

·  Present and discuss a global frequency distribution of the nine victim situations based on the UNODC coded data

·  Present and discuss a global frequency distribution of the nine victim situations based on the IOM/Polaris data

·  Discuss three possible reasons for the differences between the two frequency distributions

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