The Gender Gap in Fear: Assessing the Interactive Effects of Gender and Perceived Risk on Fear of Crime

Abstract

In this research we explore the interaction between gender and perceived risk of victimization on levels of fear of crime. Much of the previous research on the effects of gender on fear of crime assumes that crimes are not gendered and that the effects of gender would operate the same regardless of type of crime. Challenging this assumption, we examine crimes that disproportionately victimize women or men. We find that there is greater nuance in both fear of crime and perception of risk when explored in this way. In fact, men's fear of crime actually surpasses women's fear at high levels of perceived risk for those crimes in which men are more likely to be victimized. We offer explanations for this finding, concluding that gendered perceptions of crime and victimization may drive these differences. In sum, our study indicates that future research on fear of crime must be even further attuned to the gender gap in fear.

We thank J. Timmons Roberts and Heather Monro Hilliard for assistance with the original data collection and analysis. We also thank Eric Stewart and Charles Gallagher for feedback on this manuscript.

Notes

¹Not all women accept this “stereotypography” of fear. Some have the capacity to resist the dominant woman as victim ideology (Farrall et al., 2000).

²Clearly those who are in their 50's are part of the working age population, not the elderly population. However, some of our analyses are limited in this regard because the original survey instrument measured age categorically with a top code of “over 50.”

³Of the entire sample, 60 percent were White, 31 percent Black, 4 percent Hispanic, 3 percent Asian, and 2 percent other.

⁴In 1995, New Orleans had an exceptionally high homicide rate of 74.5 per 100,000.

*p<.05 (two-tailed)

+Compared to the middle category.

⁵This finding is complicated by our operationalization of age. Previous research focuses on the relationship between fear and the elderly. The majority of our highest age category is composed of individuals who are far from elderly.

⁶Although we are presenting the results of regression equations modeled using OLS, we also modeled the same equations using ordered logit regression. The results of the two sets of analyses did not differ in either statistical or substantive effects therefore we chose to present our OLS results because the coefficients can be interpreted and discussed more succinctly. The ordered logit results are available from the authors.

⁷Despite concerns about the presence of multicollinearity, none of the independent variables exhibit problematic collinearity. With the exception of product terms in later models, correlations among the independent variables are all less than +/−0.4, all of the Variance Inflation Indices are less than 1.3, and all of the tolerances are greater than 0.7.

⁸In calculating these predicted values we set the value of all other explanatory variables to zero.

⁹Given the methodological approach of this study, however, this explanation of the greater effect of perceived risk on men's fear of crime is unlikely. Those who are most likely to engage in high-risk behavior are also those who are least likely to be included in a sampling frame of phone number listings. The demographic group most likely to be at the greatest risk of criminal victimization is young men who engage in criminal behavior themselves. In our study this group is likely underrepresented, documented by the slight overrepresentation of women in our sample.