For this assignment, all you have to do is to select a topic, write an introduction, formulate a research question (see examples above) and a hypothesis. Keep it simple! Then, you will also review thr

However, explanations for these differences within and across gender and race and ethnicity must continue to be explored and to that end the purpose of this research is to examine whether the well-established risk factors for victimization such as daily or routine activities and neighborhood conditions similarly influence risks for violent vic- timization among varying gender, racial, and ethnic groups. Using data from the National Crime Victimization Survey (NCVS) 12 Cities study, the authors find that risks do vary both across and within gender. While routine activities are significant predictors of females’ risks, neighborhood conditions seem to be better indicators of males’ risks. Also, routine activities and neighborhood conditions have disparate effects on males’ and females’ risks across race and ethnicity. For example, while fre- quent use of public transportation has a null effect on White females’ risks for violent victimization, it increases such for Black and Latina females. Likewise, although resi- dential stability decreased the risks of violent victimization for White and Latino males, it increased the likelihood of victimization for Black males.

Keywords African/Black Americans, Latino/Hispanic Americans, National Crime Victimization Survey (NCVS) 120, victimization, White Americans 1Department of Criminal Justice and Criminology, University of Missouri, Kansas City, MO, USA2Department of Sociology and Criminal Justice, University of Hartford, Hartford, CT, USA Corresponding Author:

Toya Z. Like-Haislip, Department of Criminal Justice, University of Missouri, 5215 Rockhill Road, Kansas City, MO 64110, USA Email: [email protected] Race and Justice 1(3) 254-276 ªThe Author(s) 2011 Reprints and permission:

sagepub.com/journalsPermissions.nav DOI: 10.1177/2153368711409059 http://raj.sagepub.com at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from The complexities of the gender, race, ethnicity, and violence relationship are evident in the victimization literature. Research has consistently demonstrated that with the exception of rape/sexual assault males are more likely than females to be victims of violent crimes while minorities (and particularly Blacks and Latinos) are more likely to be violently victimized than are Whites (Catalano, 2005, 2006; Rand, 2009). These dichotomous comparisons, however, mask the importance of intersections between gender, race, and ethnicity and their influence on individuals’ experience with vio- lence. Interestingly, recent victimization research has shown that rates of violent victimization are notably high among Black males and females relative to their White and Latino counterparts. Furthermore, the gender gap in Black rates of overall victimization is much more narrow than that found between Whites and Latinos (Lauritsen & White, 2001). For instance, Lauritsen and White (2001) report nearly identical rates of violent victimization among Black males and females (26.9 and 26.3, respectively). The disparities, however, are larger for the other groups, with rates for White males (23.2 per 1000) exceeding that of White females (15.5 per 1000) and similarly Latino males (31.3 per 1000) possess higher rates than their female coun- terpart (18.9 per 1000; Lauritsen & White, 2001).While this race/ethnicity and gender pattern has clearly been demonstrated in victimization research, explanations for these differences remain unclear. Scholars have routinely considered males and females experiences with violence separately.

Traditional criminology has focused almost exclusively on the plight of males (and minority males in particular) and explanations for their criminal behavior (e.g., Anderson, 1999; Cohen & Felson, 1979; Messerschmidt, 1993; Sampson & Laub, 1993; Sullivan, 1989). Feminist criminology, on the other hand, has focused primarily on specific forms of violence against women such as intimate partner violence and rape and sexual assault—to the detriment of a comprehensive understanding of females’ risks for violence in general (Heimer & Kruttshcnitt, 2006, p. 2). More scarce are the extant literatures on gender, race, and ethnic variations in victimization risk and causes for these disparities (but see Lauritsen & White, 2001). It is important to examine whether the intersection of these characteristics condition risks for violent victimization. Although some suggest that demographic characteristics are indicators of structural (and possibly cultural) factors that increase risks for violent victimiza- tion, few have systematically studied this possibility. It remains unclear whether well-established risk factors for victimization such as daily or routine activities and neighborhood conditions similarly influence risks for violent victimization among varying gender, racial, and ethnic groups. To that end, the goal of the present study is to explore whether ‘‘known’’ risks factors for violent victimization—indicators of individual lifestyle and community characteristics—are common across gender, race, and ethnicity. In assessing these relationships, we contribute broadly to the study of victimization and specifically to the body of work on gender, race, and ethnic variations in violent victimization. As Lauritsen and Carbone-Lopez (2011) note, studies along these lines present important theoretical implications and essentially help to determine whether general approaches in the study of violence are warranted or whether the development of ‘‘specialized Like-Haislip and Miofsky 255 at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from theories’’ that are gender- and/or race and ethnic-specific are necessary (p. 1). Furthermore, in our examination of the proximate causes of victimization, we also consider both within and across gender differences insuch. Conventional wisdom and empirical research lead us to believe that there are both similarities and differences in males’ and females’ experiences with violence; how ever, we also posit that there are within gender differences (especially across race and ethnicity) in violent victimization.

In doing so, we assess common and unique feat ures of victimization risks within and across gender.

Violent Victimization at the Intersection of Gender, Race, and Ethnicity At the forefront of the study of victimization and its relation to demographic char- acteristics such as gender, race, and ethnicity is the lifestyle model (Hindelang, Gottfredson, & Garafalo, 1978; also see Garofalo, 1987) and routine activities theory (Cohen & Felson, 1979). The lifestyle model posits that our lifestyles, which consist of daily activities centered on vocation and leisure, are largely predicted by individual characteristics and structural constraints based on these characteristics. The lifestyle pattern (or daily activities), in turn, influences the amount of exposure to places and individuals that present victimization risks (Hindelang et al., 1978; also see Garofalo, 1987). In a similar vein, routine activities theory suggests that daily or recurrent activities related to work, family, and leisure are important. The structure of these activities can impact personal victimization as well as the overall crime rate by increasing the likelihood of convergence in time and space between motivated offenders and suitable targets in the absence of capable guardians (Cohen & Felson, 1979). Overall, these theories propose that differences in victimization risks are explained by variations in lifestyles and routine activities. These theories account for gender and racial/ethnic differences in victimization using this premise. Considering gender differences, lifestyle, and routine activities approaches suggest that lifestyle differences between males and females account for disparities in their victimization risks. In other words, once routine and daily activities are considered gender is no longer an explanatory factor (Woodward & Fergusson, 2000; but see Mustaine, 1997). Females’ lower risks for violent victimization relative to males were attributed to their fewer interactions away from home and thus their diminished exposure to dangerous places such as night clubs and bars, for example, where assaults are prevalent. These differences in male/female interactions away from home might also explain contextual differences in victimization risk across gender. Males are commonly victimized by strangers or those whom they had not previously had contact with. This is not the case for females, however, who are far more likely to be victi- mized by persons they know such as their spouses, intimate partners, acquaintances, and friends (Rand, 2008; Rennison & Welchans, 2000). Feminist scholars have long critiqued traditional lifestyle/routine activities approaches for their inattention to the violence females experience in their homes or familiar settings (Heimer & Kruttshcnitt, 2006, p. 2). For example, in 2008 females were nearly four times more 256 Race and Justice 1(3) at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from likely to be violently victimized by an intimate partner than were males, with females’ rates totaling 4.3 per 1,000 compared to a rate of 0.8 per 1,000 for males (Catalano, Smith, Snyder, & Rand, 2009).Despite these trends, the gap in male and female interactions away from home may have narrowed in recent decades, especially following World War II when female involvement in the work force increased noticeably. In 1960, 97 %of males in the United States were involved in the labor force compared to only 42.9 %of females.

However, female participation skyrocketed to 75.3 %by 2005 while the rate for males dropped to 90 %(Mosisa & Hipple, 2006). Undoubtedly, female participation in the workforce has increased the amount of time that they spend away from home and consequently may have impacted the aforementioned victimization trends in notable ways. In their analysis of gender differences in violent victimization from 1973 to 2004, Lauritsen and Heimer (2008) find that the gender gap in simple and aggravated assault has closed dramatically especially due to the substantial drops for males yet relatively slower declines for females. They postulate that female movement into the public sphere may have lead to fewer acts of interpersonal violence in public settings for which males were at greater risks. But this shift may have also inadvertently led to greater opportunities for female victimization as female interactions in public settings increased and thus their greater likelihood of exposure to motivated offenders increased (Lauritsen & Heimer, 2008). In addition to lifestyle or daily activities such as workforce participation, structural constraints may also influence risks for victimization. Garofalo (1987) argues that these constraints are of particular importance because they can have a direct effect on exposures and associations conducive to victimization via place of residence. Simply put, the contextual features of communities not only determine individual and group adaptations (and thus the lifestyles they adopt) but also influences victimization risks ‘‘by sheer proximity—and hence exposure—to potential offenders’’ (Garofalo, 1987, p. 38). From this perspective, race and ethnicity are not directly connected to victi- mization but rather are indicative of macrostructural factors that shape life, including the conditions under which people live. Though ignored relative to demographic characteristics, research on lifestyle/routine activities theory that considers neigh- borhood conditions have indeed found that neighborhood disadvantage is a significant predictor of victimization risk (Mustaine & Tewksbury, 1998; Sampson, 1987). That being said, while lifestyle/routine activities theory notes the importance of structural conditions (see Garofalo, 1987, p. 38), neighborhood theorists have long argued the significance of community context and its impact on individuals’ experience with violence (Bursik & Grasmick, 1993a; Sampson, Raudenbush, & Earls, 1997; Shaw & McKay, 1942). Importantly, research in these areas suggests that racial and ethnic differences in victimization risks subside once community disadvantage is considered (Krivo & Peterson, 1996; Lauritsen, 2003; Lauritsen & White, 2001; McNulty & Bellair, 2003; Peterson & Krivo, 1993). The disproportionate rates of victimization among Blacks and Latinos compared to Whites is not surprising then given that they are less likely to live in ecological equality with Whites (Massey & Denton, 1993; Sampson & Wilson, 1995). Sampson and Wilson (1995) in their study of the largest Like-Haislip and Miofsky 257 at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from cities in the United States were unable to find one city in which Whites and Blacks live in ecological equality. Similarly, Massey and Denton (1993) document the historical context of these trends in residential segregation equating it to a system of apartheid that cannot be simply explained by economic differences between these groups but instead is rooted in deep-seated racism and prejudice in America 1(also see Fischer, Gretchen, Jon, & Michael, 2004; Lewis Mumford Center for Comparative Urban and Regional Research, 2001; Logan, Stults, & Farley, 2004). Consequently, Blacks in particular are more likely to be concentrated in neighborhoods suffering from extreme levels of social and economic disadvantage that are characterized by extremely high levels of disorder and crime (Massey & Denton, 1993; Peterson, Krivo, & Browning, 2006; Skogan, 1990; Wilson, 1987). As Garofalo (1987) had proposed a decade ear- lier, Sampson and Wilson (1995) theorize that these structural disadvantages make residents (and in this case Blacks) particularly vulnerable to violence since these struc- tural inequalities inadvertently curtail mainstream goals and values thereby exacerbat- ing risks for violent offending and victimization in their communities. Taken together, the extant research on violence—and particularly that on violent victimization—has emphasized the importance of both situational and contextual factors including individuals’ lifestyles as well as the environments in which they live.

While scholars agree that these factors predict victimization risks, it remains unclear whether they are similarly related to victimization risks across gender- and race/ethnic-specific groups. The problem is that past works have considered ethnicity, race, and gender independently, largely disregarding their interaction and likely complex effect on risks for nonfatal forms of violent victimization (see DeCoster & Heimer, 2006; Simpson & Gibbs, 2006 for full discussion on the complexity of inter- sectionalities). Feminist scholars, in particular, have critiqued criminological research and theory for ignoring the importance of gender (and its intersection with race, eth- nicity, class, etc.) and ‘‘assuming that theories designed to explain male behavior are equally applicable to females’’ (Heimer & Kruttshcnitt, 2006, p. 2). Furthermore, Lauritsen and Carbone-Lopez (2011) point out, relatively few works have considered the extent to which gender conditions the impact of ‘‘known’’ correlates of victimiza- tion (p. 1). In consideration of these assessments, we further assert that it is important to examine whether gender and race/ethnicity moderates the relationship between victimization risks and theoretical variables consistently linked to victimization. We agree with feminist works that primacy must be given to gender and its intersection with other demographic characteristics to explain variations in victimization risks. However, we also critique feminist works in that they have focused almost exclusively on those forms of violence particular to females such as domestic violence and sexual assault, ignoring how these intersections are important to male and females’ risks alike. These factions in the study of violence have limited our understanding of violence and the development of a comprehensive theoretical explanation of variations in victimization risks. As aforementioned, routine activities/lifestyle theories are commonly used to explain gender differences while neighborhood conditions are often purported to explain racial/ethnic differences in victimization risks. Yet, it remains unclear how these theoretical variables impact victimization risks across intersections of gender, 258 Race and Justice 1(3) at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from race, and ethnicity. Therefore, we examine the importance of these factors and explore whether they present unique or common effects on victimization risks among non-Latino White males and females, non-Latino Black males and females, and Latino males and females.

Method Data The data for the present study are derived from the National Crime Victimization Survey (NCVS) 12 Cities study. The Bureau of Justice Statistics (BJS) and the Office of Community-Oriented Policing Services (COPS) collaborated to collect data on vio- lent and property victimizations, perceptions of local policing and community safety across 12 cities utilizing community-oriented policing strategies. The sampled cities are Chicago, Illinois; Kansas City, Missouri; Knoxville, Tennessee; Los Angeles, California; Madison, Wisconsin; New York, New York; San Diego, California; Savannah, Georgia; Spokane, Washington; Springfield, Massachusetts; Tucson, Ari- zona; and Washington, District of Columbia. A random sample of households within each city was identified by the Demographic Statistical Methods Division (DSMD) using the GENESYS Random-Digit Dialing (RDD) Sampling System to gather house- hold telephone numbers which corresponded with city zip codes. 2It is important to note this sampling strategy differs from the multistage, multiclustered sampling tech- nique used for the traditional NCVS. Data collection for the NCVS 12 Cities study occurred over a 4-month period, starting in February 1998. Interviews were conducted via telephone using computer assisted telephone interviewing (CATI). The CATI method, used by the NCVS between 1992 and 2007, was implemented to reduce pos- sible errors by interviewers and to improve the quality of the data collected. 3 Sample The NCVS 12 Cities survey includes measures of individuals’ demographic charac- teristics, routine activities, and perceived neighborhood conditions in addition to measures of violent victimization. As noted above, non-Latino Whites and Blacks and Latinos are the focus of this research. These groups constitute the majority (or 95 %)of the 13,918 original participants in the NCVS 12 Cities study. This classification of race, which considers ethnic origin, is important because race and ethnicity are not mutually exclusive categories in any NCVS data including the NCVS 12 Cities data. 4 Latinos can be of any racial background with approximately 40 %of those in the present study self-identifying as White, while only 7 %report their race as Black. This distinction of ethnic and racial (or ethnoracial) background is especially critical in assessing risks for victimization since ‘‘‘White’ versus ‘Black’ comparisons result in an overestimation of risks among Whites because ‘Hispanics’ [Latinos] are included with Whites, whereas ‘Hispanic’ versus ‘non-Hispanic’ comparisons under- estimate group differences because Blacks and Whites are combined in the ‘non- Hispanic’ category’’ (Lauritsen & White, 2001, p. 43). Therefore, the present study Like-Haislip and Miofsky 259 at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from employs a designation of race that takes into account individuals’ ethnic origin also.

While consideration of other ethnoracial groups is needed, such comparisons present an analytical challenge due to their small sample size; therefore, these groups are not considered in the present study. 5 The sample of non-Latino Whites, non-Latino Blacks, and Latinos was reduced for two essential reasons. First, one of the key variables (perceived disorder) was asked only of respondents aged 16 and older so the sample is restricted to those fitting this age criteria. 6Second, missing data on other key variables (indicators of routine activ- ities) led to further reductions in the sample size. It is important to point out, however, the percentage missing for each routine activity measure is 2 %or less. Subsequently, the total sample of non-Latino Whites, non-Latino Blacks, and Latinos aged 16 and older comprised of 11,971 was further reduced to 11,512 due to missing values on the routine activities measures. Because the intersection between ethnicity, race, and gen- der as it relates to risks of nonfatal violent victimization is of importance, the sample is disaggregated across these dimensions and is a comparison of the following ethnic/ race-specific gender groups: non-Latino White and Black males and females, and Latinos and Latinas. 7 Dependent Variable The dependent variable is nonfatal violent victimization. 8Each respondent was asked to report whether they were a victim of an attempted or completed rape/sexual assault, robbery, or simple or aggravated assault in the past 12 months (0 ¼no and 1 ¼yes ).

A scale of violent victimization was created in which a value of ‘‘1’’ was assigned to those who reported experiencing one or more of these victimizations in the past year.

A summary indicator of violent victimization is used as opposed to separate analyses for each victimization type since certain incidents of violence are rare. For example, less than 1 %of the respondents from each race/ethnic-specific gender group reported being a victim of rape or sexual assault. Independent Variables Routine activities. Involvement in the workforce is believed to be an important pre- dictor of victimization, especially given the recent shifts for females, and so we included a measure of employment history which considers whether or not the participants worked a job in the past year. The NCVS 12 Cities participants were also asked three questions that serve as additional indicators of routine activities: (a) How often do you spend the evening away from home? (b) How often are you gone shopping? and (c) How often do you ride public transportation? In the survey, participants were given the option to answer almost every night or day (coded 1), at least once a week (coded 2), at lease once a month (coded 3), less often (coded 4), or never (coded 5). These codes were reverse-ordered to account for an increase in the value for these items representing greater frequency or involvement in the respective activities. The results of principal component analyses reveal little commonality between these items. 9Supplemental tests 260 Race and Justice 1(3) at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from also suggest the same. For example, the reliability coefficient or Cronbach’safor the three items is very low (.15). Therefore, these survey items are not combined but con- sidered separately in the analyses and are labeled Evening Away,Shopping ,andPublic Transit in the descriptive tables. Though some scholars have noted the lack of speci- ficity in using vague measures like frequen cy at which individuals spend the evening away from home as an indicator of a routine activity that places one at risks for vic- timization (Mustaine & Tewksbury, 1998), it is a common measure and directly assesses the theoretical claims of the rou tine activities approach (Cohen & Felson, 1979). The other measures, ShoppingandPublic Transit , are indicative of specific activities one may engage in outside of ho me, hence placing them in proximity to motivated offenders. Neighborhood factors. The length of years the individual has lived at his/her address is used as an indicator of residential stability and is considered here given that previous studies have associated residential stability with violent victimization (i.e., Lauritsen, 2003). Although the NCVS 12 Cities survey does not include direct measures of neighborhood conditions, it does provide questions on perceptions of neighborhood conditions. As noted above, those 16 years of age and older were asked to report whether physical and/or social disorder exists in their neighborhood. 10 Principal com- ponents analyses using a varimax rotation were performed to determine the extent of commonality among the 14 survey questions measuring signs of physical and social disorder in the participants’ neighborhoods. 11 Two components were retained— Disorder and Homeless/Transient—and composite scales were created using the aver- age of the z-scores of the items included in each component. The Disorder Scale consists of the following items: ‘‘abandoned buildings/cars,’’ ‘‘rundown/neglected buildings,’’ ‘‘public drinking/drug use,’’ ‘‘public drug sales,’’ ‘‘loitering/hanging out,’’ and/or ‘‘truancy/youth skipping school’’ in the neighborhood. ‘‘Panhandling/begging’’ in the neighborhood and ‘‘transient/homeless populations sleeping on the streets of the neighborhood’’ are included in the Homeless/Transients Scale. The reliability coeffi- cients (Cronbach’s a) for these scales are .82 and .71, respectively.

Finally, controls for demographic characteristics associated with violent victimi- zation are included in the study. Victimization surveys have consistently linked age (Klaus & Rennison, 2002) and marital status (Catalano, 2005) to violent victimization.

Age ranges from 16 to 90 across the sample. Marital status is divided into the fol- lowing categories: married (reference group), divorced/separated, widowed, and never married individuals. Though annual household income is also a correlate of violent victimization (Catalano, 2005), it is not included in the final analyses because of the extent of missing data for this measure. 12 Findings Bivariate Results Descriptive statistics across the groups are provided in Tables 1 (males) and 2 (females). As shown in Table 1, there are both similarities and differences across Like-Haislip and Miofsky 261 at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from Table 1.Descriptive Statistics on the Restricted NCVS 12 Cities Sample, 1998 a(Males) Non-Latino White Non-Latino Black Latinos Mean Median Dev. % Mean Median Dev. % Mean Median Dev. % Age 45.1 42.0 18.3 43.6 38.0 18.8 33.7 29.0 13.3 Income b 11.0 12.0 2.9 9.6 10.0 3.410.1 11.0 3.5 Current address (yrs) 11.2 6.0 12.6 9.4 4.0 10.66.4 3.0 8.0 Disorder .2 0.0 .3 .3 0.0 .3.3 0.2 .3 Homeless/transient .2 0.0 .3 .2 0.0 .3.2 0.0 .4 Shopping 4.1 4.0 .6 3.9 4.0 .7 4.1 4.0 .8 Evening away 3.8 4.0 1.0 3.5 4.0 1.4 3.8 4.0 1.1 Public transportation 1.7 1.0 1.2 2.0 1.0 1.42.0 1.0 1.5 Employed in past year 74.367.674.8 Never married 34.737.344.0 Violence victims 6.76.7 7.1 Note. NCVS 12 Cities study (ICPSR 2743).aThe descriptive statistics are based on the unweighted samples of non-Latino White males ( n¼ 3,938), non-Latino Black males ( n¼ 748), and Latinos ( n¼ 557).bBased on 14 unequal categories of income: 1 ¼<$5,000; 2 ¼$5,000–7,499; 3 ¼$7,500–9,999; 4 ¼$10,000–12,499; 5 ¼$12,500–14,999; 6 ¼$15,000–17,499; 7 ¼ $17,500–19,999; 8 ¼$20,000–24,999; 9 ¼$25,000–29,999; 10 ¼$30,000–34,999; 11 ¼$35,000–39,999; 12 ¼$40,000–49,999; 13 ¼$50,000–75,000; 14 ¼$75,000 or more. Due to the extent of missing cases for this variable, it is not included in the final analytic models. 262 at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from Table 2.Descriptive Statistics on the Restricted NCVS 12 Cities Sample, 1998 a(Females) Non-Latina White Non-Latina Black Latina Mean Median Dev. % Mean Median Dev. % Mean Median Dev. % Age 45.9 44.0 17.9 47.1 44.0 18.735.0 33.0 12.6 Income b 10.9 12.0 3.2 8.1 8.0 4.27.7 9.0 4.3 Current address (yrs) 12.8 7.0 13.1 11.9 8.0 11.66.7 4.0 7.2 Disorder .2 0.0 .3 .3 0.2 .3.3 0.4 .3 Homeless/transient .1 0.0 .3 .2 0.0 .3.2 0.0 .3 Shopping 4.2 4.0 .7 3.9 4.0 .74.0 4.0 .7 Evening away 3.6 4.0 1.0 3.3 4.0 1.4 3.6 4.0 1.3 Public transportation 1.7 1.0 1.2 2.4 2.0 1.62.4 2.0 1.6 Employed in past year 63.062.058.0 Never married 25.243.337.9 Violence victims c 4.3 5.18.0 Note. NCVS 12 Cities study (ICPSR 2743).aDescriptive statistics are based on the unweighted samples of non-Latino White females ( n¼ 4496), non-Latino Black females ( n¼ 1164), and Latinas ( n¼ 609).bBased on 14 unequal categories of income: 1 ¼<$5,000; 2 ¼$5,000–7,499; 3 ¼$7,500–9,999; 4 ¼$10,000–12,499; 5 ¼$12,500–14,999; 6 ¼$15,000–17,499; 7 ¼ $17,500–19,999; 8 ¼$20,000–24,999; 9 ¼$25,000–29,999; 10 ¼$30,000–34,999; 11 ¼$35,000–39,999; 12 ¼$40,000–49,999; 13 ¼$50,000–75,000; 14 ¼$75,000 or more. Due to the extent of missing cases for this variable, it is not included in the final analytic models. 263 at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from males in the study. Males in each racial and ethnic group report similar levels of homeless and transient populations in their neighborhoods and frequency in shopping, spending evenings away from home, and riding public transportation. While they report the exact same level of homeless/transient populations in their communities, White males and Latinos, on average, spend slightly more time shopping and out in the evenings than do Black males. Black males and Latinos are slightly more likely to ride public transportation than are White males. Also, the percentage of those who experience violent victimization are comparable across race and ethnicity among the males, with the percentage for Latinos (7.1%) being slightly higher than that for White and Black males (6.7 %). The differences, however, are more notable among the sampled males in terms of their age, marital status, income levels, perceptions of neighborhood disorder, and residential stability. The average age among White males is 45.9 years and is higher than the average age among Black males (43.6 years) and Latinos (33.7 years). Likewise, White males report notably higher annual household income levels than did males in the other racial and ethnic categories. Their mean income range between $35,000 and $39,999, while the average income among Black males and Latinos range between $25,000 and $29,999 and $30,000 and $34,999, respectively. Latinos and Whites also fare better in terms of employment over the past year with their rates nearly equal at 74 %compared to 67 %for Black males. The proportion never married is higher among Black males (37.3 %) and Latinos (44 %) than White males (34.7 %). Black males and Latinos were slightly more likely to report disorder in their communities than were White males, while White males, on average, were more likely to have lived at their current address (11.2 years) longer than Black males (9.4 years) and Latinos (6.4 years). There are more marked differences than similarities among the female participants.

Considering their commonalities, White and Black females and Latinas report roughly equal levels of time spent shopping with the average for White females (4.2) being minimally higher than Black females and Latinas (3.9 and 4.0, respectively). The mean scores for evenings spent away from home are also similar as they equal 3.6 for White females and Latinas, while the mean is only slightly lower at 3.3 for Black females. Though the difference is small, Black females and Latinas are more likely to report disorder and homeless/transient populations in their neighborhoods than are White females. In all other respects, the sampled females vary considerably. The average age is higher for Black females (47.1 years) than it is for White females (45.9 years) and Latinas (35 years). There is also a noticeable gap between the average annual household income of White females and minority females considered in this study. White females, whose household incomes are between $30,000 and $34,999, make considerably more than Latinas (between $17,500 and $19,999). The income level among Black females is above that of Latinas—ranging between $20,000 and $24,999—but still less than that of White females. These income disparities are likely tied to differences in the women’s work histories. White and Latina females are more likely to be employed (63 %and 62 %, respectively) than are Black females (58 %).

Black females and Latinas are more likely to ride public transportation and to have never been married than are White females. White females, on the other hand, are 264 Race and Justice 1(3) at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from more likely to have lived at their current address (12.8 years) longer than are Black females (11.9 years) and Latinas (7.7 years). Lastly, the percentage violently victi- mized among Latinas is nearly double that of White females (8%vs. 4.3 %, respec- tively), while the percentage among Black females (5.1 %) lies between that of Latinas and White females.

Multivariate Results Logit models are used to explore the relationship between routine activities, neigh- borhood conditions, and risks for violent victimization among non-Latino White and Black males and females and Latinos and Latinas. These analyses were performed using Stata software because of the clustered sample design of the NCVS 12 Cities data. As previously stated, a random sample of households for each city was obtained for the data to consequently cluster across the 12 cities. Stata is able to calculate robust estimates of the standard error based on this sampling strategy (StataCorp, 2005). Fur- ther, logistic regression analyses are especially appropriate when the independent and/ or control variables range in type (i.e., categorical or continuous) yet, the dependent variable is dichotomous (Mertler & Vannatta, 2002). With this analytic technique, it is not necessary to assume the independent or control variables are ‘‘normally distribu- ted, linearly related, or have equal variances within each group’’ (Mertler & Vannatta, 2002, p. 314). 13 Table 3 presents the results of the nonfatal violent victimization regression model for males, while Table 4 presents the results for females. As shown in Table 3, indicators of routine activities did not have a significant impact on White or Black males’ risks for violent victimization after controlling for age and marital status. And only one indicator is related to Latinos’ risks for violent victimization at significant levels—time spent shopping ( b¼ 0.839). Specifically, Latinos who spent more time out shopping are 2.31 times more likely to be victims of violent crime than those who do not. Results show evenings spent away from home, time spent riding public transportation, and employment are not significant predictors of victimization for any of the male groups. Results also show neighborhood conditions affect minority males’ risk for violent victimization dissimilarly from White males. Neighborhood conditions, when mea- sured as residential stability and perceived disorder, are significant predictors of violent victimization for Black males and Latinos. However, residential stability decreases risks for violent victimization for Latinos ( b¼ 0.051), but increases the risk for Black males ( b¼ 0.032). It is important to point out that perceived disorder is the greatest predictor of violent victimization for Black males (b ¼2.15) and Latinos ( b ¼ 1.69); indicating that for each unit increase in perceived disorder, the odds of violent victimization increase by 8.67 times for Black males and by 5.47 times for Latinos. Perceived disorder influences Black males and Latinos risk for victimization in the expected direction—disorder increases the risk for violent victimization among Black males and Latinos. While the relationships are not statistically significant for any group of males, it is interesting to note the presence of homeless/transient persons Like-Haislip and Miofsky 265 at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from Table 3.Logistic Regression Models Predicting Risk for Nonfatal Violent Victimization Across Race and Ethnicity (Males) Non-Latino White Non-Latino Black LatinosbSEbSEbSE Demographic characteristics Age 0.019 .014 0.006 .017 0.001 .018 Never married 0.351*** .090 0.033 .429 0.393 .382 Lifestyle/routine activities Worked past year 0.085 .134 0.661 .374 0.465 .315 Time spent shopping 0.177 .167 0.168 .474 0.839*** .164 Evenings spent away from home 0.046 .126 0.162 .347 0.081 .161 Time spent riding public transportation 0.021 .098 0.051 .143 0.146 .094 Neighborhood conditions Residential stability 0.027 .017 0.032** .011 0.051* .028 Disorder 0.597 .411 2.159*** .649 1.699* .783 Homeless/transients 0.342 .267 0.243 .839 0.773 .492 Pseudo R 2 0.063 0.1020.116 *p < .05.

** p< .01.

*** p< .001.

Table 4. Logistic Regression Models Predicting Risk for Nonfatal Violent Victimization Across Race and Ethnicity (Females) Non-Latina White Non-Latina Black LatinasbSE bSEbSE Demographic characteristics Age 0.033** .017 0.059*** .013 0.065*** .019 Never married 0.223 .249 0.224 .486 0.441 .384 Lifestyle/routine activities Worked past year 0.544 .230 0.004 .150 0.616 .589 Time spent shopping 0.694** .168 0.342** .125 0.307 .342 Evenings spent away from home 0.230 .370 0.145* .091 0.012 .300 Time spent riding public transportation 0.169 .117 0.376* .163 0.226*** .038 Neighborhood conditions Residential stability 0.004 .035 0.0595*** .009 0.012 .032 Disorder 1.153* .608 0.272 .297 0.316 1.054 Homeless/transients 0.0715 .366 0.324 .355 0.539* .308 Pseudo R 2 0.091 0.158 0.088 *p < .05.

** p< .01.

*** p< .001.

266 Race and Justice 1(3) at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from in the neighborhood have a negative effect on Black and Latino males violent victimization but is positively related to White males violent victimization. And finally, none of the neighborhood conditions have a significant effect on White males’ risk for violent victimization.While observing the results among females, as shown in Table 4, predicting risk for nonfatal violent victimization across race and ethnicity are disparate. Overall, indi- cators of routine activities have a significant impact on Black females’ risks for violent victimization after controlling for age and marital status. However, the find- ings for White females and Latinas vary. Time spent shopping has a significant impact for White and Black females’ risks for violent victimization; however, time spent shopping significantly increases White females’ risk ( b¼ 0.694), while decreasing the risk among Black females ( b¼ 0.342). ‘‘Evenings spent away from home’’ is only a significant predictor of violent victimization for Black females. Specifically, Black females who spend evenings away from home are more likely to be victims of violent crime. Riding public transportation is associated with a significant increase in risk for violent victimization among Black females ( b¼ 0.376) and Latinas ( b¼ 0.226).

Minority females who ride public transportation are more likely to experience violent victimization than are minority females who did not use public transportation. And lastly, employment is not significantly related to violent victimization for females of any racial or ethnic background. Neighborhood factors also had a dissimilar impact on females’ risks across race and ethnicity. Specifically, residential stability exerts a significant positive effect on Black females’ risks for violent victimization. While the relationships are not statis- tically significant for White females and Latinas, it is interesting to note that resi- dential stability has a negative effect on their risk for violent victimization but a positive association with Black females’ r isk. Perceived disorder is positively related to White females’ risks for violen t victimization after demographic char- acteristics and routine activ ities are considered. It is important to note that perceived disorder is the greatest predictor of violent victimization for White females ( b¼ 1.153); indicating that for each unit increase in perceived disorder, the odds of violent victimization incre ase by 3.17 times for White fe males. Finally, perception of homeless/transient persons in the neighborhood is only significantly related to Latinas’ risks for violent victimization. In particular, the presence of homeless/ transients in their neighborhood increases Latinas’ risk for victimization and this is the greatest predictor of their risk ( b¼ 0.539).

Summary Using the NCVS 12 Cities study, the findings demonstrate there are both withinand across gender differences among these racial and ethnic groups. Considering the former, there are variations in violent victimization between females and between males. In general, measures of routine activities and neighborhood conditions dif- ferentially impact females’ risks for violent victimization. Time spent shopping is significantly related to violent victimization for White and Black females but not Like-Haislip and Miofsky 267 at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from Latinas. However, this indicator influences White and Black females’ victimization in opposing directions; the relationship is positive for White females, but negative for Black females. Conversely, riding public transportation increases minority females’ risks for violent victimization but no significant relationship appears for White females. Furthermore, evenings spent away from home increase the likelihood of violent victimization for Black females but not for White females or Latinas. And finally, employment did not significantly affect any of the female groups.The data also indicate that when examining neighborhood factors, incongruent results occur within the female population’s risk for violent victimization. Residential stability increases the likelihood of violent victimization for Black females but not White females or Latinas. In contrast, the presence of homeless/transient populations in the neighborhood significantly increases Latinas’ risks but not White or Black females’ risks. Lastly, perceived disorder only has a significant influence on White females’ risk for victimization. In fact, perceived disorder increases the odds of violent victimization by 3.17 times for White females. There is only one notable difference within the male groups with respect to mea- sures of routine activities. Time spent shopping significantly increases the risk for violent victimization among Latinos but is not statistically significant for White and Black males. Yet, regardless of race/ethnicity, male’s risk for violent victimization is not influenced by employment, evenings spent away from home, or time spent riding public transportation. Overall, the results indicate neighborhood conditions influence minority males’ risk for violent victimization varyingly from White males. Specifically, residential stability is a significant predictor of Black males’ and Latinos victimization, but in contradictory directions; the relationship is positive for Black males, but negative for Latinos. Additionally, perceived disorder has a significant influence on Black males and Latino’s risk for victimization. In fact, perceived disorder increases the odds of violent victimization by 8.67 times for Black males and 5.47 times for Latinos. In contrast, the presence of homeless/transient populations in the neighborhood is not a significant predictor of violent victimization for males regardless of the racial/ethnic group considered.

There are also differences in victimization risks across gender. Overall, measures of routine activities are significant predictors of females’ risks for violent victimization but not males’. Specifically, none of the routine activities measures produce similar sig- nificant effects on violent victimization for males and females of the same racial/ethnic background. Neighborhood conditions also present dissimilar results across gender. In fact, only one indicator of neighborhood conditions is a significant predictor of male and females’ risk for violent victimization within the same race/ethnic group; residential stability increases Black males’ and females’ risk for violent victimization.

Discussion Recent research on violent victimization has underscored the need for data to examine how the intersections between gender, race, and ethnicity influence an individual’s 268 Race and Justice 1(3) at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from experience with violence. It is sometimes difficult to disentangle concepts embedded in the intersections of gender, race, and ethnicity; and while few studies can capture the complexities of these factors, we believe the NCVS 12 Cities data can be used to construct a reliable picture of the disparities of gender, race, and ethnic variations in risk for violent victimization.The goal of this article has been to explore whether risks for violent victimization are common across gender, race, and ethnicity. The findings we discovered may be regarded as the next step in the evolution of intersectional approaches toward a better understanding of well-established routine activities and neighborhood conditions that influence risks for violent victimization among varying gender and racial/ethnic groups. An intersectional approach to studying variations in violent victimization is a natural progression for the extant literature through acknowledging gender, race, and ethnicity as dynamic relationships which simultaneously succeed at both microstruc- tural and macrostructural levels. These findings are imperative because they not only contribute broadly to the study of victimization but specifically to gender and racial/ ethnic variations in victimization. The findings also suggest criminologists must recognize the importance of developing integrated criminological theories—lifestyle and neighborhood conditions that frame inequalities of victimization, gender, and race/ethnicity—as the guide for future research.

Our results showed that common criminological risk factors measured by routine activities and neighborhood conditions affect White, Black, and Latin males and females inconsistently. Beginning with routine activities, generally our findings suggested that routine activities were better predictors of females’ victimization risks than they were of males’ risks. These predictions, however, varied across race and ethnicity. Only one indicator of routine activities influenced males’ risks for violent victimization. Latinos who spent more time shopping were more likely to be victims of violent crime. Neither White nor Black males’ victimization risk was significantly impacted by measures of routine activities. A possible explanation for this complex finding is that the structure of daily activities differentially influenced victimization risk across race and ethnicity through the amount of exposure to motivated offenders who are unknown to the victim. Lauritsen and White (2001), for instance, found that Latinos were more likely than White and Black males to be victimized by strangers. It is plausible then that activities such as shopping are more often associated with stranger victimizations, which may be a more common occurrence among Latinos compared to White and Black males. The relationship between routine activities and violent victimization was also disparate throughout the female composition of the current sample. Black females’ risk for violent victimization was significantly related to three of the four measures of routine activities. Black females who frequently spent evenings away from home and frequently rode public transportation were at an increased risk for violent victimization. Latinas who frequently rode public trans- portation were also more likely to be victims of violent crimes. However, this was the only congruent finding among the female populations for the routine activities mea- sures. Time spent shopping was significantly related to White females’ risk for violent victimization, but notice this was contrary to the finding for Black females. White Like-Haislip and Miofsky 269 at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from females who frequently shopped were at an increased risk but such risk was reduced for Black females who reported frequent shopping. We believe the differences found among females are the product of lifestyle differences rooted in structural inequalities across race, ethnicity, and class. For example, our finding that time spent riding public transportation significantly increased minority females’ risks for violent victimization but not White females’ risk may be tied to variations in microstructural and macro- structural constraints. Economic and residential inequalities, in particular, are central.

Black females and Latinas in this study were more likely than White females to report using public transportation and their reliance on such may be linked to disparities in their reported income levels. Moreover, given the disproportionate concentration of Black females and Latinas in disadvantaged communities (Lauritsen & Rennison, 2006), the areas in which they are utilizing public transportation may be distinct and thus present greater opportunities for exposure to motivated offenders. Over the years, the lifestyle model/routine activities approach has gained significant popularity in explaining crime rates across gender. It may be that the explanatory power of this notion differs across race and ethnicity within the female population. Our results suggested that variations in females’ interactions in public settings provide important insight into racial and ethnic variations in risks for victimization.Furthermore, our findings suggested neighborhood conditions generally produced dissimilar affects on violent victimization across race, ethnicity, and gender. Our analyses indicated that these conditions significantly influenced risks among the minority but not White male population. Specifically, Latino and Black males who reported more disorder in their communities were at an increased risk for violent victimization. Residential stability, however, was differentially related to violent victimization across these groups of males. Black males who lived in their commu- nities longer were more likely to be victims of violent crimes; conversely, residential stability decreased risks for violent victimization for Latinos. None of the neighbor- hood conditions considered was significantly related to White males’ violent victi- mization risk. Moreover, our results proposed no consistent pattern for the relationship between neighborhood conditions and victimization risk among the female popula- tion. The three measures of neighborhood conditions—residential stability, disorder, and homeless/transients—impacted White and Black females and Latinas in dis- concert. Specifically, residential stability significantly increased Black females’ risk for violent victimization but not White females or Latinas. Disorder significantly increased White females’ risk for violent victimization but not Black females or Latinas. And, the presence of homeless/transients in the neighborhood only affected Latinas’ risk for violent victimization. Again, these intriguing findings are likely grounded in the complexities of intersecting inequalities across race, ethnicity, gen- der, and class. Our finding that neighborhood conditions are better predictors of Latino and Black males’ victimization risk is not surprising given the structural conditions often faced by minority communities. Minority, and especially pre- dominantly Black, neighborhoods are often plagued by various forms of extreme disadvantage including notably higher rates of residential instability, poverty, unemployment, and family disruption which can increase the odds of criminal 270 Race and Justice 1(3) at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from behavior and victimization in these areas (Anderson, 1999; Bursik & Grasmick, 1993b; Krivo & Peterson, 1996; Peterson et al.,2006; Sampson, 1987; Sampson & Wilson, 1995; Wilson, 1987). Black communities mor e often suffer from these inequalities than do Latino communities (Massey & Denton, 1993; Velez, 2006). This potentially explains why residential stability significan tly increased Blacks’ (males and females) risk for violent victimization as well as the disparate findings across Blacks and Latinos/Latinas. The incongruent findi ngs among females may also be tied to these inequalities in neighborhood structure. It is possible that Black females’ reports of disorder in their communities had no significant bearing on their victimization risks once residential stability was con sidered given their greater exposure to disadvantaged communities that may be characterized by various types of disorder.

However, we found that these neighborhood in dicators—perceptions of disorder and homeless/transient populations in th e neighborhood—mattered more to White females’ and Latinas’ risks, respectively. Future research to account for gender and race/ethnicity moderating the relation- ship between routine activities/lifestyle, neighborhood conditions, and victimization risk face considerable obstacles because the findings shown here were complex. Some of the difficulties relate to the limitations of the present study. In particular, the data for the present study derive from only 12 cities; to demonstrate the generalizability of the findings, future studies should be replicated in different settings and with related data. Furthermore, the NCVS 12 Cities study lacked precise measures of suggested theoretical mechanisms that would permit direct testing of various hypotheses. For example, both the routine activities and lifestyle perspective hold that exposure to motivated offenders predict victimization risks. We have only considered a limited range of activities that might be relevant without directly testing other components of the theory such as proximity to motivated offenders as the current dataset does not allow for such an examination. Moreover, a need for more measures of specific routine activities and lifestyle perspective are desired especially since the NCVS 12 Cities data were collected in 1998 and may not be as reflective of contemporary daily activities and lifestyles that place individuals at risk for violent victimization. Lastly, we relied on perceptional measures of neighborhood conditions since the NCVS 12 Cities data were collected at the city level and, therefore, preclude examination of direct measures of neighborhood characteristics (i.e., poverty) that are also associated with victimization risks. Subsequent studies then would benefit from further examination of neighborhood conditions and more specification of lifestyle/routine activity measures. Despite these limitations, our analyses revealed the importance of intersections between gender, race, and ethnicity and their influence on individuals’ experience with violence. By examining routine activities/lifestyle and neighborhood conditions on victimization risks among White, Black, and Latino males and females, we pro- vided evidence that past works have considered these factors exclusively, largely disregarding their interactional and complex effects on risks for nonfatal forms of violent victimization. We anticipate the current results will develop further under- standing of the complexities of the gender, race/ethnicity, and violence relationship by promoting researchers to investigate more intensely the patterns of victimization. Like-Haislip and Miofsky 271 at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The authors received no financial support for the research, authorship, and/or publication of this article.

Notes 1. Massey and Denton (1993) note that Blacks are far more likely to be segregated fromWhites compared to other racial/ethnic groups except Puerto Ricans. They propose that their integration into White communities relative to other Latino groups may be limited simply because of their darker skin tone.

2. See Smith, Steadman, Minton, and Townsend (1998) for a complete description of the NCVS 12 Cities study methodology.

3. See Cantor and Lynch (2000) for a full discussion of the effects of CATI on NCVS data collection. Because of budgetary concerns, the BJS discontinued the use of the CATI in 2007 (see Rand, 2008).

4. This classification of race which takes into account ethnic origin is important because race and ethnicity are not mutually exclusive categories and are not considered as such in any NCVS data including the NCVS 12 Cities data. The NCVS 12 Cities study uses the U.S. Census Bureau’s classification of race and ethnicity. Race is comprised of six categories: ‘‘White,’’ ‘‘Black,’’ ‘‘American Indian,’’ ‘‘Eskimo,’’ ‘‘Asian or Pacific Islander,’’ and ‘‘Other.’’ Ethnicity is comprised of two categories: ‘‘non-Hispanic’’ and ‘‘Hispanic.’’ Consequently, Hispanics or Latinos can be of any racial background. In the NCVS 12 Cities study, nearly 50 %of this group reported their race as ‘‘White,’’ 40 %reported being ‘‘Other,’’ 7 %reported being ‘‘Black,’’ and the remaining 3 %reported their race as ‘‘American Indian,’’ or ‘‘Asian or Pacific Islander’’ (also see Lauritsen, 2003; Lauritsen & White, 2001 for similar results).

5. Observation of other ethnic and racial groups is important but difficult using the NCVS 12 Cities data. About 3 %of the original sample (435 of 13,918) is non-Latino Asian, while the remaining group, non-Latino Others, only constitute about 2 %of the original sample (262 of 13,918). Note that these figures do not reflect possible further reductions in these groups’ sample size due to missing data on key variables (e.g., perceptions of neighborhood disorder).

6. Like the traditional NCVS, the NCVS 12 Cities study includes all household members aged 12 and older. However, the questions related to neighborhood conditions are only asked to those 16 and older.

7. Hereafter, non-Latino White and non-Latino Black are referred to as White and Black, respectively.

8. Hereafter, nonfatal or nonlethal violent victimization is referred to as violent victimization.

9. The results yielded two components (both with an eigenvalue slightly above 1). The third component had an eigenvalue close to 1 (0.82). Therefore, all two-way combinations of these three survey items were considered and the results were similar; the first component had an eigenvalue slightly above 1, while the eigenvalue for the second component neared a value of 1. The second component eigenvalue equaled 0.83 for the ‘‘evening away’’ and 272 Race and Justice 1(3) at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from ‘‘shopping’’ combination, 0.99 for the ‘‘shopping’’ and ‘‘public transit’’ combination, and 0.95 for the ‘‘evening away’’ and ‘‘public transit’’ combination.

10. These are dichotomous measures which were coded 0 for no responses and 1 for yes responses.

11. Despite numerous analyses, six of the disorder items did not load well with the others and therefore were omitted. These items were poor lighting, overgrown shrubs/trees, trash, empty lots, vandalism/graffiti, and prostitution.

12. The sample size reduces from 11,512 to 9,771 when income is included in the analyses. Note, however, the findings are largely unchanged when income is considered. The same lifestyle/routine activities and neighborhood variables are significant predictors of victimi- zation for Black males and Latinos with or without the income measure in the analytical models. And these variables are unrelated to White males’ risks. The only caveat is that one indicator of lifestyle/routine activity—‘‘worked past year’’—that is not significantly related to males’ risk when income is not included is indeed a significant predictor of their risk once income is considered. Likewise, there is consistency in the predictors for violent victimization among the sampled females regardless of the inclusion of income in the ana- lytical models, with one exception. For Black females, the number of evenings spent away from home is not a significant predictor of their risk for violent victimization once income is considered. For White females an additional measure of routine activities—‘‘time spent riding public transportation’’—is a significant predictor of their victimization risk once income is considered. The predictors are the same for Latinas across models with and with- out the inclusion of income.

13. Note that there are also critiques of using traditional logit models when both the occurrence of the event of the dependent variable (e.g., being a victim of a nonfatal violent crime) is rare and the sample size is small as this can result in extremely biased estimates of the odds ratio (King & Zeng, 2001a, 2001b). In simulations, King and Zeng (2001a, 2001b) demonstrate that this bias is especially pronounced in studies where the event is very rare (e.g., less than 1 %) and the sample size is small (e.g., n< 1,000). They suggest the use of an ‘‘approximate Bayesian’’ method over the traditional logit model in these cases (King & Zeng, 2001a, p. 709). However, the present study is less subjected to such bias since it utilizes a sizable sample ( n> 10,000), of which nearly 5 %have been victims of a nonfatal violent crime. For example, in their demonstrations where the sample size is 10,000 and the event occurred for approximately 5 %of the sample, the percentage difference in the odds ratio derived from a traditional logit mode l versus their alternative method was less than 5 %. References Anderson, E. (1999). Code of the street: Decency, violence and the moral life of the inner city.

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Bios Toya Z. Like-Haislip is an assistant professor of Criminal Justice and Criminology at the University of Missouri, Kansas City. Her current research interests include mul- tilevel assessments of risks for violent victimization, racial and ethnic variations in victimization, and the intersection between gender, race, and class as it relates to victimization risks.

Karin Tusinski Miofsky is an assistant professor of Sociology and Criminal Justice at the University of Hartford. Her research is concerned primarily with juvenile delin- quency, particularly with patterns of bullying and victimizations within schools. 276 Race and Justice 1(3) at FLORIDA STATE UNIV LIBRARY on September 4, 2016 raj.sagepub.com Downloaded from