Linking crime rates to relationship factors: The use of gender-specific data

The present study built on, and extended beyond, Steffensmeier and Haynie's efforts (2000) to understand social control factors at the macro level. It focused especially on gendered relationship factors as predictors of gender-disaggregated arrest rates for serious adult crimes. There are two aspects of social control that function to discourage crime: structural factors and relationship factors. Most previous studies had focused on the former aspect, examining the effects of a locale's structural disadvantages on its gender-disaggregated crime rates. In the present study, the authors addressed the latter aspect, in particular, the kinds of relationship factors built on marriage and employment. The evaluation was conducted using data recorded by the national census, the State of Ohio's Boards of Elections, and the FBI's Uniform Crime Reports for Ohio. The developed negative binomial regression models illustrate the general hypothesis that women and men residing in a common ecological area are not equally subject to relationship factors that help control criminal behavior. Women tend to be affected more strongly by such factors than men are.