Abstract
The present study investigated county-level correlates of human trafficking arrest levels in Ohio. Study variables were comprised of measures derived from social disorganization, social capital, and physical contexts of Ohio counties ( N = 88). A negative binomial regression analysis was conducted to examine the relationship between county arrest counts and independent variables. Larger counts of human trafficking arrests were explained by higher levels of racial/ethnic heterogeneity, a social disorganization measure. Additionally, an increase in demand reduction strategy use was associated with a predicted increase in human trafficking arrest count. Further research on the influence of social variables and anti-human trafficking efforts on human trafficking arrest levels is needed to better understand how to effectively identify and combat human trafficking.
Published Version
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