Race-Specific Gender Equality and Rape: A Further Test of Feminist Hypotheses

RACE-SPECIFIC GENDER EQUALITY AND RAPE:

A FURTHER TEST OF FEMINIST HYPOTHESES

SARAH ESCHHOLZCentral Washington University

LYNNE M. VIERAITISUniversity of Alabama at Birmingham

Abstract. Feminists have long argued that structural inequality between men and wo-men influences the prevalence of rape. The patriarchal maintenance hypothesis predicts

that gender inequality increases rape, while gender equality ameliorates rape (Whaleyand Messner 2002). Alternatively, the backlash hypothesis predicts that gender equalityexacerbates the rape problem (Russell 1975; Williams and Holmes 1981). To date, no

study has explored this relationship with respect to race. In the present study, we use across-sectional design with racially disaggregated census and crime data in order toassess the differences among White and Black women in terms of their status along

educational, employment, income, and occupational dimensions, and their risk of vic-timization. The findings indicate that the relationship between equality and rape ismasked in the model that includes all women, but becomes apparent in the race specificmodels.

Rape is often conceptualized not only as a crime against individualwomen, but as a means by which men maintain power over women as aclass through both force and fear (Brownmiller 1975). Although theintroduction of feminist theory into mainstream criminology in the1960s highlighted the importance of examining the structural position ofwomen in society and their risk of violent victimization by men, mostrape research still focuses on individual level explanations (Randall andMcNickle Rose 1984; Johnson and Lee 2000). Early studies thatexamined structural theories of rape focused on general incomeinequality and racial inequality as precursors to environments condu-cive to violence (Blau and Blau 1982; Schwendinger and Schwendinger1983; Baron and Straus 1987). These studies did not, however, focus onthe gendered nature of rape by exploring inequality between men andwomen.

While most criminological theories agree that general incomeinequality and racial inequality should produce higher rape rates, there

Critical Criminology 12: 195–219, 2004.

� 2004 Kluwer Law International. Printed in the Netherlands. 195

is no consensus among theories as to the direction of the effect forgender inequality and rape rates. According to feminist theory, greaterlevels of gender inequality may lead to elevated rape rates by placingwomen at a structural disadvantage relative to men (Griffin 1971;Brownmiller 1975; Davis 1975) and equality should ameliorate rapelevels (Whaley and Messner 2002); however, greater levels of genderequality may also increase women’s victimization by generating a‘‘backlash’’ effect (Russell 1975; William and Holmes 1981). In addition,although the inequality-crime literature has highlighted the importanceof racial inequality for crime, very few studies have explored the race-specific nature of gender inequality and violence against women withinspecific racial groups. Considering that rape is primarily an intra-racialcrime, especially in single offender – single victim cases (U.S. Depart-ment of Justice 2001), that Black women are victimized at a rate dis-proportionate to their representation in the population, and that therape rate for Black women is approximately five times that of whitewomen (see Table 2), it is important to examine the dynamic betweenrace, gender, and rape.

The present study offers insight into this dynamic by exploring racialdifferences in the link between gender equality and rates of rape in largecities. Cross-sectional data from the largest 148 cities in 1990 are disag-gregated based on gender and race to assess the degree towhichWhite andBlack women’s absolute status and their status relative to White andBlack men, respectively, impact rape rates. Women’s status is opera-tionalized using economic, educational, and occupational measures.

Theoretical Background

Both absolute and relative deprivation have long been cornerstonesof various theories predicting crime. Marxist theory (Bonger 1916),social disorganization theory (Shaw and McKay 1942), anomie the-ory (Merton 1938), macrostructural theory (Blau and Blau 1982), androutine activity theory (Maume 1989) all posit a positive relationshipbetween income inequality, poverty, and crime (Fowles and Merva1996). Poor economic conditions, whether increasing frustration,generating strain, inhibiting social control mechanisms, or increasingcriminal opportunities, impact the rates of both offending and vic-timization (making women more vulnerable through both proximityto violent individuals and inadequate resources to protect oneself)(Bailey 1999).

SARAH ESCHHOLZ AND LYNNE M. VIERAITIS196

While it has been hypothesized that impoverished conditions canalone produce the frustration that leads to a heightened level of vio-lence, including rape (Schwendinger and Schwendinger 1983), theseconditions may be exacerbated by the presence of those much better offeconomically (Merton 1938). As Schwendinger and Schwendinger(1983: 221) argue: ‘‘it is time to recognize that rape is distributed in oursocial structure in predictable ways and that sexual assault as well asother violent crime is influenced by political, economic, and ideologicalconditions.’’ Relative deprivation is particularly frustrating when entiregroups of people see opportunities to success blocked by race, class,and/or sex (Blau and Blau 1982; Blau and Schwartz 1984; Blau andGolden 1986).

The recognition that groups vary in their access to opportunities forsuccess provided the impetus for race-specific macro-level research onthe relationship between inequality and crime. Additionally, many havequestioned the racial invariance issue, arguing that Whites and Blacksmay instead react differently to structural constraints (Ousey 1999). Forexample, recent research has explored the impact of race on the rela-tionships among income inequality, poverty, and homicide rates (Harerand Steffensmeir 1992; Ousey 1999; Parker and McCall 1999; Petersonand Krivo 1993). Only one published study has combined this workwith feminist arguments concerning gender inequality by testing theinterplay of race and gender and homicide rates (Vieraitis and Williams2002). Recognizing that both race and gender are important factors inestablishing structural positions in society, as well as factors inresponding to social structures researchers need to consider this inter-section in studies of crime, particularly rape, which may serve as amethod of maintaining structural divisions in society.

Gender Inequality and Violent Crime

While structural theories do much to focus attention on the crimino-genic influence of poor economic conditions, and class and race divi-sions on society, they fail to recognize the fundamental inequality facedby women within classes and within race-ethnic groups. Feminist the-ory, in its variety of forms, highlights the importance of status differ-ences between men and women in a number of spheres, including legal,economic, political, social, and the patriarchal family unit. Genderinequality is particularly relevant to discussions of rape and domesticassault given that the overwhelming majority of victims are female andoffenders are male (U.S. Department of Justice 2001).

RACE-SPECIFIC GENDER EQUALITY 197

Past research has focused primarily on two feminist hypothesesconcerning the impact of gender inequality on rape rates. The tradi-tional feminist hypothesis suggests that rape is a method of patriarchalmaintenance and that gender equality has an ameliorative effect onrape. Occupying the bottom-rung of the social, economic, legal, politicaland familial ladder, women are socialized to serve the needs of men, andmen are socialized to view women as their property (Griffin 1971; Davis1975; Ellis and Beattie 1983). Rape is ‘‘a conscious process of intimi-dation by which all men keep all women in a state of fear’’ (Brownmiller1975: 13). Consequently, when women are in disadvantaged positionsrelative to their male counterparts the rape rate will be higher (Griffin1971; Brownmiller 1975; Sanday 1981), and as women become moreequal rape rates should decline (Whaley and Messner 2002).

Although the traditional patriarchal maintenance argument predictsa positive relationship between gender inequality and rape rates, acounter argument has arisen utilizing a similar rationale. Russell (1975;see also Faludi 1991) contends that rape rates will increase as genderequality increases because men will try to recapture their lost powerthrough force. Rape is one way that men may react to structuralchanges they perceive as disadvantageous or threatening (Brownmiller1975; Riger and Gordon 1981; Sanday 1981). Therefore, gender equalitymay result in a ‘‘backlash’’ and increase violence against women.Advocates of this position generally agree that after an unspecifiedperiod of resistance by men to women’s gains, the overall rape rateshould decrease as men become more comfortable with equality andrealize the benefits that equality offers them; at this point one shouldonce again find support for the traditional feminist hypothesis.

In 1999, Bailey introduced a third alternative hypothesis that predictsthe absolute status of women is more important than gender inequality.Women who have more resources may be better able to protect them-selves from rape, particularly stranger rape because they can afford asafer living environment, likewise women who have fewer resources aremore vulnerable to rape (Bailey 1999). This hypothesis focuses on thebehaviors of women as predictors of rape rather than the behaviors ofmen.

Race-Specific Gender Inequality

Although the inequality-crime literature has long included a discussionof the importance of measuring racial inequality, only one study hasexplored the race-specific nature of gender inequality and violence


against women of specific race groups and this study focused onhomicide (Vieraitis and Williams 2002). Treating women as a homog-enous group by aggregating the data may distort race-specific patternsof offending and victimization. For example, several studies have foundthat the effect of both poverty and inequality on homicide is race-spe-cific (Harer and Steffensmeier 1992; Peterson and Krivo 1993; Ousey1999). We predict that gender inequality and rape may operate in asimilar fashion.

Recent feminist scholarship has also noted the importance ofexploring the intersection of race and gender (Williams and Holmes1981; Huey and Lynch 1996; Daly and Tonry 1997). Sex and genderroles are culturally contingent and racial-ethnic group differences couldhave a large impact on the incidence of rape within these groups(Messerschmidt 1993, 1997). Williams and Holmes (1981: 259) predict‘‘that the risk of being raped, attitudes toward rape, and the impact ofthe rape experience upon victims, will differ between Whites, Blacks,and Mexican-Americans.’’

Recent trends suggest that minorities, particularly African Ameri-cans, have more gender equality than their White counterparts (seeTable 2), For minority men, this may be particularly frustrating becausenot only are their economic opportunities limited in comparisons toWhites, but minority women are making economic and educationalgains at a faster pace. Alternatively, since Black women have been in thepaid workforce in larger numbers for a prolonged period of time, Blackwomen may currently be experiencing less ‘‘backlash’’ than their Whitecounterparts. The degree to which these factors impact rape rates needsto be investigated and may provide clues as to the viability of thepatriarchal maintenance, ‘‘backlash,’’ and vulnerability hypotheses.

Literature Review

Research testing the various theoretical propositions delineated above islimited. Table 1 summarizes the 8 studies that tested the genderinequality-rape hypotheses. Since these studies employed differentmeasures of gender inequality and different samples, there are 60 modelsreported in the table. The following discussion focuses on the findings ofstudies that use measures of inequality in income, education, occupa-tions, and employment.1

Gender inequality in income was included in 12 models. Sevenreported a negative relationship, only one of which was statistically


Table

1.Summary

offindingsforstudiesofgender

inequality

andrape

Authors

Sample

Data

source

Findings*

Controlvariables

Ellisand

Beattie

(1983)

25SMSAs(1970)

UCR

1975

)Income

)Education

)Employment

+Occupation

)Judges

&Lawyers

)Police/detectives

PopulationSize;

Pct.Black;

MeanFamilyIncome;

Poverty;Pct.

FamilyHeadsEmployed;Pct.

Professional&

Managerial;

AgeRiskAdjustment;Marital

StatusRiskAdjustment

26Cities(1970)

UCR

1975

)Income

)Education

)Employment

+Occupation

NCVS

1975–1976

+Income

+Education

+Employment

+Occupation

BaronandStrauss

(1984)

50States(1980)

UCR

1979

+Statusofwomen

index

1

Sex

Mag.CirculationIndex;Pct.

CityPop.residingin

SMSAs;Pct.Black;

Pct.Poor;Pct.Age18–24;Pct.Male

Pop.15–24

Baronand

Strauss

(1987)

50States(1980)

UCR

1980–1982

)Gender

equality

index

2

Sex

Mag.Index;Legit.Violence

Index;Soc.

DisorganizationIndex;Pct.Citypop.residingin

SMSAs;Pct.Black;Pct.Age18–24;Pct.Males

Age15–24;GiniIndex;Pct.Single

MalesAge15andolder;Pct.Unem

ployed


Table

1.Continued

Authors

Sample

Data

source

Findings*

Controlvariables

Maume(1989)

284SMSAs(1980)

UCR

1980–1982

Income3

Pct.Black;Pop.Size;

Pct.Age15–34;

South;Gini;RacialInequality;General

OpportunityIndex;RacialDifferences

inLifestyles

Petersonand

Bailey

(1992)

263SMSAs(1980)

UCR

1980

+Income

+Education

+Occupation5

Divorcerate;Pct.YoungMales;Pct.

Black;PopulationSize

Linskyet

al.(1995)

50States(1980)

UCR

1980–1982

+Gender

Equality

Index

Pct.Metro;Poverty;Sex

Magazine

CirculationIndex;Legitim

ate

Violence

Index;SocialDisorganizationIndex

Bailey

(1999)

192Cities(1980)

UCR

1980

Absolute

status

ofwomen:

)Education

)Occupation

)Income

Pop.Size;

Pct.Black;Pct.Married

Women;Pct.Divorced;Poverty;

GiniIndex

Relative

status

ofwomen:

)Education

)Occupation

)Income

192Cities(1990)

UCR

1990

Absolute

status

ofwomen:

)Education


Table

1.Continued

Authors

Sample

Data

source

Findings*

Controlvariables

)Occupation

)Income

Relativestatusof

women:

)Education

)Occupation

)Income

192Cities(C

hange1980–1990)

Relative

statusofwomen:

)Education

)Occupation

+Income

Whaley(2001)

109Cities(1970)

UCR

1970

Relative

statusofwomen:

)Income

)Employment

)Education

)Legal

)%

Male

Employment

LogPopulation,

%age15–24,

Sex

ratio,Family

Poverty,%

Moved,

Ethnic

Heterogeneity,%

Divorced

)%

Male

Executives

109Cities(1980)

UCR

1980

Relative

statusofwomen:

)Income

)Employment

)Education


Table

1.Continued

Authors

Sample

Data

source

Findings*

Controlvariables

)Legal

)%

Male

Employment

)%

Male

Executives

109Cities(1990)

UCR

1990

Relative

statusofwomen:

)Income

)Employment

)Education

)Legal

)%

Male

Employment

)%

Male

Executives

109Cities(C

hange1970–1980)

Relative

statusofwomen:

+Education

109Cities(C

hange1980–1990)

Relative

statusofwomen:

+Income

+Education

+Legal

+%

Male

Executives


Table

1.Continued

Authors

Sample

Data

source

Findings*

Controlvariables

109Cities(C

hange1970–1990)

Relative

statusofwomen:

+Income

+Education

*Capitalizationmeansthatthecoeffi

cientisstatisticallysignificant.

1TheStatusofWomen

Index

(YlloandStraus1981)is

composedof22indicators

ofsexualequality,alongeconomic,educational,political,andlegal

dim

ensions.

2TheGender

Equality

Index

(Sugarm

anandStraus,1998)iscomposedofseven

indicators

ofeconomic

status,fourindicators

ofpoliticalstatus,and13

indicators

ofthelegalstatusofwomen.

3Directionofeff

ectnotreported.

4Modelsthatincluded

measuresofgender

inequality

inincomeandeducationare

baseddata

for147SMSAs.

5PetersonandBailey

(1992)also

regressed

raperatesagainst

fiveadditionaloccupationalmeasures.

Theresultsindicate

thatthecoeffi

cients

forthe

percentageoffemalesin

healthdiagnostic

occupationsandthepercentageoffemale

elem

entary

andsecondary

teachersare

negativeandstatistically

significant.


significant (Ellis and Beattie 1983)2 and five indicated a positive andsignificant relationship to rape (Ellis and Beattie 1983; Peterson andBailey 1992; Bailey 1999; Whaley 2001).3 Educational inequality wasincluded in 13 models (Ellis and Beattie 1983; Peterson and Bailey 1992;Bailey 1999; Whaley 2001). Eight models were in the negative direction,however, only two models were statistically significant and five modelswere positive, three of which achieved statistical significance.

Measures of occupational inequality, most commonly measured asinequality in employment in executive, managerial, and administrativepositions, were included in seven models (Bailey 1999; Ellis and Beattie1983; Peterson and Bailey 1992). Of these seven models, four were po-sitive, three were negative, and only one was significant (negative),Gender inequality in employment was included in six models. Fivemodels were negative (two of which were significant) and one waspositive and nonsignificant.

Three studies use an index of gender inequality to predict rape. Baronand Straus (1987) found a negative and significant relationship betweenthe Gender Equality Index and rape; however, using the same sample,Linsky et al. (1995) reported negative but statistically insignificant re-sults. In an earlier study, Baron and Straus (1984) reported positive andsignificant results for the Status of Women Index on rape, indicatingthat as women’s status increases, so to do rape rates.

The findings of these studies were inconclusive at best. Althoughstudies found both positive and negative relationships between measuresof gender inequality and rape, the majority of studies found no rela-tionship. Of the 60 models reported in Table 1, statistically significantfindings were limited to the following: (1) six models of incomeinequality (one negative and five positive); (2) five models of educationalinequality (two negative and three positive); (3) one model of occupa-tional inequality (negative); (4) two models of employment inequality(negative); (5) the Status of Women Index (positive direction) and (6)the Gender Equality Index (negative direction). Overall, the statisticallysignificant findings indicate limited support for both the patriarchalmaintenance (nine models) and ‘‘backlash’’ hypotheses (seven models).

The present study measures the impact of race-specific genderequality, along economic, educational, and occupational dimensions, onestimated race-specific rape rates using a cross-sectional design withcity-level data for 1990.We disaggregate our results to test the followinghypotheses for White women as a group and for Black women as agroup: Hypothesis 1 (Patriarchal Maintenance/Ameliorative): Cities inwhich gender equality is low will have higher rape rates than in cities


where gender equality is high. Hypothesis 2 (Backlash): Conversely, incities where gender equality is high (i.e., women are more equal to men),rape rates will be higher than in cities where women are less equal tomen, Hypothesis 3 (Vulnerability): Cities in which the absolute status ofwomen is low will have higher rape rates than cities in which theabsolute status of women is high.

Data and Methods

The present study used data collected for U.S. cities that had a popu-lation of 100,000 or more in 1990 and for which all relevant crime andgender data were available. Cities were selected as the units of analysissince they are more suitable for studies of rape and structural conditionsthan larger aggregations such as states (Peterson and Bailey 1992; Bailey1999) and SMSAs (Bailey 1999). As Bailey (1999) has noted, cities aremore ‘‘theoretically homogenous’’ and exhibit greater variation in rapeand sociodemographic patterns. Moreover, cities provide for a largersample size than states. In this study, the sample was restricted to citiesthat had a minimum Black population of 2000 persons (Parker andMcCall 1999). Based on these criteria, the sample was 148 cities.4

Dependent Variables: Estimated Rape Victimization Rates

Data used to construct the rape rates were drawn from the UniformCrime Reports (Federal Bureau of Investigation, 1990–1992).5 The rapevictimization rate was the average number of rapes reported to thepolice in 1989, 1990, and 1991 divided by the female population andmultiplied by 100,000. To estimate race-specific rape rates, the followingprocedure was employed: for the White females, the ratio of the totalnumber of White males arrested for rape in 1989 to the total number ofarrests for rape was multiplied by the total number of rapes reported tothe UCR in 1989.6 This procedure was repeated for 1990 and 1991.Next, the resulting figures for each year were added together and di-vided by three in order to compute the three-year average. This numberwas then divided by the White female population and multiplied by100,000 to produce an estimated White female rape victimization rate.The same procedure was followed for the estimated Black female vic-timization rate.7 The mean rape rate in our sample was 86.01 and 486.86for Whites and Blacks, respectively. The estimated race-specific rapevictimization rates were transformed into natural logs to stabilize the


variance of the error terms and induce a normal distribution of thedependent variables.

Although some readers may be uncomfortable with the use of UCRdata for estimating race-specific rape victimization rates, it is the onlydataset available for testing the structural arguments proposed byfeminist theories for a large sample of cities. We realize that all officialrape data suffers from underreporting, however, several studies com-paring UCR and National Crime Victimization Survey data suggestthat the seriousness of the crime, indicated by factors such as the useof force, the extent of injury to the victim, and the offender being astranger, is a key determinant of whether the crime is reported to thepolice (Gottfredson and Hindelang 1979; Gove et al. 1985; Lizotte1985).Thus while UCR data cannot provide a measure of a city’s‘‘true’’ rape rate, they are probably a relatively accurate indicator ofrapes involving strangers, additional violence and bodily harm beyondthe rape itself, and where the legal evidence is clear (Gove et al. 1985;Lizotte 1985; Maume 1989). In addition, we recognize that the use ofarrest data in the above procedure also poses several problems sincenot all reported rapes result in arrests, however, recent studies haveconcluded that there is substantial similarity between UCR arreststatistics and the NCVS on offenders’ characteristics (LaFree 1998).When assessing the effects of structural factors on the variation in cityrape rates, underestimation is not a serious problem since cities withhigh UCR rape rates would likely have high actual rape rates (Whaley2001). While UCR data provide a reasonable indicator of the relativeincidence of rape across cities, the results should be interpreted withcaution since they may underestimate ‘‘the trade-off’’ between genderequality and rape (Hindelang 1974; Gove et al. 1985; Peterson andBailey 1992).

We also recognize that our measures of race-specific victimizationrates may raise questions among readers, since our calculation proce-dures assume white men rape white women and black men rape blackwomen, i.e., rape is an intraracial crime. Although not all rapes areintraracial, data from the National Crime Victimization Survey (NCVS,1996–2002) and the National Incident Based Reporting System (1993)suggest that in the majority of rape incidents, the offender and victimare of the same race. According to the NCVS data from 1996 to 2002,83 percent of white victims reported ‘‘White’’ as the perceived race ofthe offender, while 80 percent of black victims reported ‘‘Black’’ as theperceived race of the offender (data for 1996 to 2002 are available athttp://www.ojp.usdoj.gov/bjs/abstract/cvus/race752.htm). In addition,


the Bureau of Justice Statistics reports that 88 percent of rape victimswere victimized by an offender of the same race (BJS 1993).

Gender Equality Measures

Data for the economic, educational and occupational variables werecollected from the 1990 Census of Population: Social and EconomicCharacteristics (US Bureau of the Census, 1993). Measures of theabsolute status of women include: (1) percentage of females 25 yearsand older who have completed a bachelor’s degree; (2) percentage offemales 15 years, and over employed full-time year-round; (3) medianincome for females 15 years and over employed full-time; and (4)percentage of females 16 years and older employed in executive,managerial, and administrative positions. These measures were col-lected for all females, White females and Black females. The measuresof the relative status of women are the ratios (females to males) of theabove variables.

Control Variables

Based on their theoretical and empirical links to violent crime asreported in previous research (Land et al. 1990; Fowles and Merva1996; Kovandzic et al. 1998; Ousey 1999; Parker and McCall 1999), thefollowing were included as control variables: (1) Gini index of incomeinequality; (2) percentage of population below poverty; (3) unemploy-ment rate; (4) population change from 1980 to 1990; (5) populationdensity; (6) percent of the population aged 15–34 (percent young); and(7) rate of divorce and separations.8

Results

Inspection of the bivariate correlation matrices for the White femalemodel and Black female model revealed three correlations that exceeded0.70 However, examination of collinearity diagnostics developed byBelsley et al. ‘‘(1980)’’ revealed no serious collinearity problems amongthe principal variables of interest. The Breusch–Pagan test indicatedheteroscedasticity. To eliminate this problem, we weighted the regres-sions by the square root of the city population (Greene 1993).

Descriptive statistics for all independent and dependent variables arepresented in Table 2. The ratio variables measuring gender equality may


Table 2. Descriptive statistics for gender equality and rape rate variables

Variable Minimum Maximum Mean SD

Measures of white women’s absolute status

White women w/B.A. (%) 4.48 32.49 14.97 5.99

White women employed (%) 22.3 55.2 35.42 5.29

White female median income 15642 34325 21192.77 3485.59

White women execs. (%) 3.88 29.14 13.28 3.39

Measures of White gender equality

Ratio of White women–White men

with B.A.

0.68 1.21 0.91 0.11

Ratio of White women–White men

Employed

0.53 0.80 0.66 0.05

Ratio of White female–White male

median income

0.54 0.92 0.70 0.06

Ratio of White women–White men Execs. 0.49 1.36 0 80 0.12

Measures of Black women’s absolute status

Black women w/B.A. (%) 2.85 25.13 9.02 4.68

Black women employed (%) 23.0 591 36.38 7.64

Black female median income 12338 28487 18846.94 3493.30

Black women execs. (%) 1.65 23.12 8.93 3.88

Measures of Black gender equality

Ratio of Black women–Black men

with B.A.

0.25 2.17 1.16 0.38

Ratio of Black women–Black men

Employed

0.57 1.07 0.78 0.09

Ratio of Black female–Black male

median income

0.60 1.06 0 81 0.07

Ratio of Black women–Black men execs. 0.19 2.22 1.17 0.34

Control variables

Divorce Rate 125.23 1997.40 527.67 209.78

Unemployment rate 2.3 16.7 6.77 2.35

Gini Index 0.289 0.583 0.41 0.05

Poverty (%) 2.8 32.4 16.35 6.20

Population change 80–90 (%) )23.2 101.2 17.20 26.22

Percent Young 17.9 48.0 31.89 3.92

Population density 145 23,671 4374.18 3381.36

Dependent Variables

White rape rate 13.06 294.32 86.01 49.70

Black rape rate 102.02 2814.36 486.86 357.96

White rape rate (natural log) 2.64 5.69 4.31 0.57

Black rape rate (natural log) 4.63 7.94 6.00 0.59


be interpreted as follows: values equal to 1.00 indicate equality andvalues less than 1.00 indicate male advantage. An initial examination ofthe mean values for the absolute status and gender equality measuresshowed that White women fared better than their Black counterparts(see Table 2). Although Black women were employed at a slightlyhigher rate than White women, White women were more likely to haveearned a bachelor’s degree, earned more money, and to be employed inexecutive, managerial, and administrative positions. While Whitewomen’s absolute status was higher, the gap between White women andWhite men was greater than the gap between Black women and Blackmen. In fact, Black women outpaced Black men in two of the fourmeasures of relative status (bachelor’s degrees and executives), andachieved near equality for employment and median income. Addition-ally, the estimated rape victimization rates (natural logs) differed dra-matically between White women and Black women (4.31 and 6.00,respectively).

Weighted least squares regression analysis of the model for allwomen provided little support for the three feminist hypotheses,delineated above (see Table 3). Only two principal variables of interest –percentage of women with a bachelor’s degree and the ratio of female tomale executives – were significant at the 0.05 level. Both were in thepositive direction, meaning that rape rates were higher in cities where agreater number of women had bachelor’s degrees and where occupa-tional equality was greater. The absolute status measure of bachelor’sdegrees also is counter to what is expected in the vulnerabilityhypothesis, where greater resources (including education) were expectedto be related to lower rape rates. Two control variables also achievedstatistical significance. The rate of divorce and the unemployment ratewere both in the positive direction. To explore the possible race-specificnature of gender inequality on rape the sample was disaggregated byrace.

Results of the weighted least squares regression analysis revealed thatone of the absolute measures of White women’s status – employment –and three of the four gender equality measures – education, employmentand medium income – produced statistically significant results in theestimated White rape models (see Table 4). The percentage of Whitewomen employed was negatively associated with the estimated raperate. Both the ratio of White women to White men employed full-timeand the income ratio were positive, meaning that in cities where Whitewomen were more equal to White men in terms of employment andincome rape rates were higher than in cities with less equality. The ratio


of White women to White men with bachelor’s degree, however, was inthe negative direction, indicating that as women gain educational paritywith men the rape rate declines. Three control variables – populationdensity, divorce rate and unemployment – were significant and in thepositive direction. Therefore, estimated rape rates for White womenwere higher in cities in which divorce rates were higher and totalunemployment was higher. The White rape model may show mixedresults supporting all three feminist hypothesis depending on the par-ticular variable. The absolute measure of employment showed thatemployment gains were related to declines in the rape rate, which isconsistent with the vulnerability hypothesis. Alternatively, the negativerelationship between gender inequality for bachelor’s degrees supportsthe ameliorative hypothesis and some support was also found for the‘‘backlash’’ hypothesis since rape rates were higher in cities where whitewomen had narrowed the gender gap in employment and income.

Table 3. Rape rates regressed against gender equality measures*

Variable b SE Beta t Ratio

Measures of women’s absolute status

Women with B.A. degree (%) 0.038 0.017 0.392 2.190

Women employed (%) )0.017 0.015 )0.179 )1.113Female median income )0.000 0.000 )0.125 )0.477Women executive (%) )0.047 0.038 )0.275 )1.256Measures of gender equality

Ratio of women–men w/B.A. )0.730 0.473 )0.197 )1.243Ratio of women–men employed 2.808 1.493 0.308 1.881

Ratio of female–male med. Inc. )0.035 1.049 )0.005 )0.033Ratio of women–men executive 0.981 0.478 0.267 2.053

Control variables

Population density )0.000 0.000 )0.145 )1.328Divorce rate 0.001 0.000 0.214 2.224

Unemployed(%) 0.058 0.023 0.282 2.549

Gini Index 1.523 1.196 0.152 1.273

Poverty (%) 0.013 0.015 0.170 0.879

Population change 80–90 )0.000 )0.002 )0.024 )0.255Young (%) )0.001 0.012 )0.010 )0.106Degrees of freedom 146

Adjusted R2 0.352

*Coefficients in boldface are significant at the 0.05 level.


Results of the Black women model show some support for feministhypotheses, which predict that gender equality is related to rape rates(see Table 5 ). The following variables were statistically significant: (1)percent Black females employed full-time (negative direction); (2) ratioof Black women to Black men with a bachelor’s degree (negative); and(3) ratio of Black women to Black men employed full-time (positive).Estimated rape victimization rates were lower in cities where the per-centage of Black women employed was higher and where Black womenwere more equal to Black men in education, However, Black women’sestimated risk of rape was higher in cities in which they were more equalto men in terms of employment. One control variable, populationdensity, achieved statistical significance and was in the negative direc-tion. This pattern of relationships, especially relative to absolute statusmeasures and gender equality measures was similar to the results foundfor Whites – mixed support of all three hypotheses.

Table 4. White rape rates regressed against White gender equality measures*


Measures of white women’s absolute status

White women with B.A. degree (%) )1.83 0.016 0.197 1.116

White women employed (%) )0.054 0.016 )0.489 )3.285White female median income )0.000 )0.000 )0.110 )0.636White women executive (%) )0.024 0.029 )0.142 )0.828Measures of white gender equality

Ratio of White women–white men w/B.A. )1.354 0.577 )0.266 )2.346Ratio of White women–white men employed 5.404 1.315 0.494 4.109

Ratio of White female–white male med. Inc. 2.982 1.134 0.320 2.629

Ratio of White women–white men executive )0.533 0.432 )0.109 )1.233Control variables

Population density )0.000 0.000 )0.257 )2.214Divorce rate 0.001 0.000 0.221 2.217

Unemployed(%) 0.122 0.028 0.498 4.307

Gini Index )1.334 1.481 )0.112 )0.900Poverty (%) )0.011 0.014 )0.125 )0.791Population change 80–90 0.002 0.002 0.089 0.856

Young (%) )0.014 0.014 )0.095 )0.996Degrees of freedom 146

Adjusted R2 0.314



Discussion and Conclusion

Feminists have long argued that structural inequality between men andwomen influences the prevalence of rape. Three hypotheses about therelationship between structural inequality and rape have emergedincluding: (1) the patriarchal maintenance hypothesis which predictsthat gender inequality increases rape, while gender equality amelioratesrape (Whaley and Messner 2002); (2) the backlash hypothesis whichpredicts that gender equality exacerbates the rape problem (Russell1975; William and Holmes 1981); and more recently, the vulnerabilityhypothesis which predicts that an increase in women’s absolute statusreduces the risk of rape (Bailey 1999). In the present study, we explorethis relationship with respect to race in order to assess the differencesamong White and Black women’s estimated risk of victimization.

Table 5. Black rape rates regressed against Black gender equality measures*


Measures of Black women’s absolute status

Black women with B.A. degree (%) 0.025 0.016 0.179 1.601

Black women employed (%) )0.050 0.010 )0.593 )5.047Black female median income )0.000 0.000 )0.030 )0.122Black women executive (%) )0.001 0.019 0.005 0.046

Measures of Black gender equality

Ratio of Black women–Black men w/B.A. )0.918 0.159 )0.551 )5.776Ratio of Black women–Black men employed 1.585 0.555 0.228 2.853

Ratio of Black female–Black male med. inc. 1.075 0.668 0.124 1.608

Ratio of Black women–Black men executive 0.005 0.166 0.003 0.031

Control variables

Population density )0.000 0.000 )0.276 )2.709Divorce rate )0.000 0.000 0.083 1.002

Unemployed(%) )0.001 0.026 )0.003 )0.032Gini Index )1.334 1.134 )0.109 )1.177Poverty (%) )0.004 0.012 )0.039 )0.314Population change 80–90 0.000 0.002 0.018 0.183

Young (%) 0.008 0.011 0.051 0.692

Degrees of Freedom 147

Adjusted R2 0.444



Our original model, which contained all women, appeared to furthercomplicate the results of past feminist theoretical tests of genderinequality on rape rates. The results indicated limited support for thebacklash hypothesis; only the ratio of female to male executives wassignificant. This finding contradicts past research which has found nosignificant relationship between these two variables (Ellis and Beattie1983; Peterson and Bailey 1992; Bailey 1999). (The one exception wasBailey’s (1999) study in which occupational equality had an ameliora-tive effect on rape rates, but only in the sample of 192 cities using 1980data). The remainder of our relative inequality measures produces nosignificant relationships with rape. This is consistent with the majorityof studies reviewed in the literature. Our finding of a positive relation-ship between women’s absolute status in education and rape has notbeen found in past studies, and unlike Bailey (1999) we found norelationship between women’s absolute income and rape. Althoughthese contradictory results seem to add confusion to an already unclearpicture, these inconsistencies may suggest that the relationship betweengender equality and rape rates is race specific, or mediated by someother variable. According to our analyses, it appears that some race-specific relationships are masked in the non-disaggregated model.

The results for the race-specific models differed from the results of thenon-disaggregated models indicating that race was mediating the rela-tionship between gender equality and rape. Only one measure providedsupport for the patriarchal maintenance/ameliorative hypothesis amongthe Black and White models – the ratio of women to men with abachelor’s degree for both White women (B ¼ )0.266) and Black wo-men (B ¼ )0.551). The results suggest that estimated rape rates for bothWhite and Black women are lower in cities with greater educationalequality. It is interesting that of the three gender equality measures withsignificant results (education, employment, and income) educationalequality is the measure where White women near equality to White men(0.91) and where Black women exceed Black men (1.16). It is possiblethat as education nears parity that both males and females are exposedto more negative attitudes toward rape in the classroom and within theirsocial circles that may serve to both protect women and liberate menfrom traditional notions of masculinity.

In support of the backlash hypothesis, the greater equality inemployment between White women and White men (B ¼ 0.494) andBlack women and Black men (B ¼ 0.228), the higher the White victim-ization rate andBlack victimization rate, respectively. In addition, greaterequality in income between White women and men also resulted in a


higher rape rate (B ¼ 0.320) but this measure just failed to achieve sta-tistical significance in the Black models (B ¼ 0.124, p ¼ 0.11). While it ispossible that greater equality betweenwomen andmen increases women’smotivation to report victimization to the police, it is difficult to explainwhy equality in educationwould have the opposite effect. Considering thecoefficients for equality in employment (b ¼ 5.404 for Whites; b ¼ 1.585for Blacks) and income (b ¼ 2.982; b ¼ 1.075) are greater than the coef-ficients for educational equality (b ¼ )1.354; b ¼ )0.918) within bothmodels, it may be that women’s advances in employment and income areperceived to be particularly threatening to the status quo. Although notassessed in the present study, it is possible that equality in education hasmoved beyond a ‘‘backlash’’ effect, while women are in the midst of a‘‘backlash’’ as the relative gains in employment and income are less (seeBailey 1999; Whaley 2001).

The finding that the greater percentage of women employed full-time,the lower the rape rates for both White women (B ¼ )0.489) and Blackwomen (B ¼ )0.593) provided some support for Bailey’s (1999) vul-nerability hypothesis. The race-specific tests of these three hypothesisshow that the relationships for Whites and Blacks are very similar whencomparing the two races, but also that they are race specific. Because ofthis finding it is impossible to compare race-specific tests with paststudies that have aggregated these two groups.

This confluence of results is somewhat confusing theoretically,because none of the three hypotheses were completely supported orrefuted. Further work is needed both theoretically and empirically toexplore the complexity of the relationship between measures of equalityand rape rates. The conclusions offered in this study are admittedlyspeculative and more work is needed to fully explain this pattern offindings. The present study does suggest the importance of exploring thestatus of women within separate racial categories in order to capture thedifferent experiences of women as well as recognizing that the structuralorganization of society is influenced by race. Although not addressed inthis study, we agree with Bailey (1999) and Whaley (2001) that researchshould also look at changes in gender equality and rape rates acrosstime. The 2000 Census data should provide a unique opportunity forresearchers to examine changes over time in women’s absolute statusand their status relative to men. The past four decades have witnesseddramatic changes with respect to women’s advances along educational,employment, income, and occupational dimensions and exploring thesetrends may provide additional insight into feminist hypotheses aboutthe violence directed toward women.


Notes

1. Ellis and Beattie (1983) also used the percentage of women who are judges andlawyers and the percentage of women employed as police officers and detectives intheir SMSA model.

2. The finding of Ellis and Beattie (1983) is based on UCR data.

3. The finding of Ellis and Beattie (1983) is based on NCVS data.4. New York City was removed from the total female model and White model because

analysis of influence statistics (i.e. DFBetas) revealed the city to be an influential

observation; therefore, the analyses of total women and White women is based on asample of 147 cities.

5. The UCR definition of rape is ‘‘the carnal knowledge of a female forcibly and against

her will.’’6. The race of the offender serves as a proxy for the race of the victim since violent

crime, including rape, is primarily intraracial (U.S. Department of Justice, 2001).

7. To illustrate, the following steps were used to compute the Black female victimiza-tion rate for the City of Atlanta: (1). the number of Black males arrested in 1989(275) was divided by the total number of arrests in 1989 (284) and then multiplied bythe total number of rapes reported in 1989 (691). This was repeated for 1990 and

1991. (2). The resulting figures 669, 673, and 610, respectively were added togetherand then divided by three to produce a three year average (651). (3) This number(651) was divided by the total Black female population (142,976) and multiplied by

100,000 to produce the estimated Black female rape victimization rate.8. Income inequality is measured as the Gini index of family income concentration

(Bureau of the Census, 1990). Data for poverty were drawn from the County and City

Data Book (U.S. Bureau of the Census, 1994) and data for the measure of unem-ployment were extracted from the 1990 Census of Population: Social and EconomicCharacteristics (U.S. Bureau of the Census, 1993). Data for percent Black, popula-tion change, and population density were drawn from the County and city Data Book

for 1990 (U.S. Bureu of the Census, 1994). The variable, percent young, was basedon data from 1990 Census of Population: Social and Economic Characteristics (U.S.Bureu of the Census, 1993). Data for the divorce and seperation rate were collected

from the Supplements to the Monthly Vital Statistics Report: Advanced Reports, 1988(U.S. Department of Health and Human Services, 1990).

References

Bailey, William C. (1999). The socioeconomic status of women and patterns of forciblerape for major U.S. cities. Sociological Focus 32, 43–63.

Baron, Larry S. and Straus, Murray A. (1984). Sexual stratification, pornography,

and rape in the United States. In Neil M. Malamuth and E. Donnerstein (eds.),Pornography and Sexual Aggression San Diego: Academic Press, pp. 185–209.

Baron, Larry S. and Straus, Murray A. (1987). Four theories of rape: A macrosocio-

logical analysis. Social Problems 34, 467–489.Belsley, David A., Kuh, Edwin and Welsch, Roy E. (1980). Regression Diagnostics:

Identifying Influential Data and Sources of Collinearity. New York: Wiley.


Blau, Judith and Blau, Peter (1982). The cost of inequality: Metropolitan structure and

violent crime. American Sociological Review 47, 114–129.Blau, Peter and Golden, Reid (1986), Metropolitan structure and criminal violence. The

Sociological Quarterly 27, 15–26.Blau, Peter and Schwartz, Joseph (1984). Crosscutting Social Circles: Testing a Mac-

rostructural Theory of Inter Group Relations. Orlando, FL: Academic Press.Bonger, Willem (1916). Criminality and Economic Conditions. Boston: Little, Brown, &

Company.

Brownmiller, Susan (1975). Against Our Will: Men, Women and Rape. New York:Simon & Schuster.

Bureau of the Census (1994). 1990 Census of Population: Social and Economic Char-

acteristics. Washington, D.C.: U.S. Government Printing Office.Bureau of the Census (1993) County and City Data Book—1990. Washington, D.C.:

U.S. Government Printing Office.Daly, Kathleen and Tonry, Michael (1997). Gender, race, and sentencing. Crime and

Justice 22, 210–252.Davis, Angela (1975). JoAnn Little: The Dialectics of Rape. Ms. 3, 106–108.Ellis, Lee and Beattie (1983). The feminist explanation for rape: An empirical test.

The Journal of Sex Research 19, 74–93.Faludi, Susan (1991). Backlash: The, Undeclared War Against American Women.

New York: Crown.

Federal Bureau of Investigation (1990). Crime in the United States—1989. Washington,D.C.: U.S. Government Printing Office.

Federal Bureau of Investigation (1991). Crime in the United States—1990. Washington,

D.C.: U.S. Government Printing Office.Federal Bureau of Investigation (1992). Crime in the United States—1991. Washington,

D.C.: U.S. Government Printing Office.Fowles, Richard and Merva, Mary (1996). Wage inequality and criminal activity:

An extreme bounds analysis for the United States, 1975–1990. Criminology 34,l63–182.

Gottfredson, Michael and Michael J. Hindelang (1979). A study of the behavior of law.

American Sociological Review 44, 3–18.Gove, Walter R., Michael Hughes and Michael Geerken (1985). Are uniform crime

reports a valid indicator of the index crimes? An affirmative answer with minor

qualifications. Criminology 23, 451–491.Greene, W.H. (1993). Econometric Analysis. New York: MacMillan.Griffin, Susan (1971). Rape, the all-American crime. Ramparts 10, 26–35.Harer, Miles D. and Steffensmeir Darrell (1992). The differing effects of economic

inequality on black and white rates of violence. Social Forces 70, 1035–1054.Hindelang, Michael J. (1974). The uniform crime reports revisited. Journal of Criminal

Justice 2, 1–17.

Huey, Jacklyn and Lynch, Michael, J. (1996). The image of black women in criminol-ogy: Historical stereotypes as theoretical foundation. In Michael J. Lynch andE. Britt Patterson (eds.), Justice Without Prejudice: Race and Criminal Justice in

America. Guilderland, NY: Harrow and Heston, pp. 72–88.Johnson, Kim and Lee, Mi Young (2000). Effects of clothing and behavior on per-

ceptions concerning an alleged date rape. Family and Consumer Sciences Research

Journal 28, 331–356.


Kovandzic, Tomislav V., Lynne M. Vieraitis and Mark R. Yeisley. (1998). The struc-

tural covariates of urban homicide: Reassessing the impact of income inequality andpoverty in the post-Reagan era. Criminology 36, 569–599.

LaFree, Gary ( 1998). Losing Legitimacy. Boulder, CO: Westview.Land, Kenneth C., McCall, Patricia L., and Cohen, Lawrence E. (1990). Structural

covariates of homicide rates: Are there any invariances across time and social space?American Journal of Sociology 95, 922–963.

Linsky, Arnold, Bachman, Ronet and Straus, Murray (1995). Stress, Culture &

Aggression. Yale University Press: New Haven & London.Lizotte, Alan (1985). The uniqueness of rape: Reporting assaultive behavior to the

police Crime and Delinquency 31, 169–190.

Maume, David (1989). Inequality and metropolitan rape rates: A routine activityapproach. Justice Quarterly 6, 513–527.

Merton, Robert K. (1938). Social Theory and Spcial Structure. New York: FreePress.

Messerschmidt, James (1997). Crime as Structured Action: Gender, Race, Class andCrime in the Making. Thousand Oaks, California: Sage Publications.

Messerschmidt, James (1993).Masculinities and Crime: Critique and Reconceptualization

of Theory. Lanham, Maryland: Rowan & Littlefield Publishers.Ousey, Graham C. (1999). Homicide structural factors and the racial invariance

assumption. Criminology 37, 405–426.

Parker, Karen F. and McCall, Patricia L. (1999). Structural conditions and racialhomicide patterns: A look at the multiple disadvantages in urban areas. Criminology37, 447–478.

Peterson, Ruth D. and Bailey, William C. (1992). Rape and dimensions of gendersocioeconomic inequality in U.S. metropolitan areas. Journal of Research in Crimeand Delinquency 29, l62–177.

Peterson, Ruth D. and Krivo, Lauren J. (1993) Racial segregation and black urban

homicide. Social Forces 71, l001–1026.Randall, Susan and Rose, Vicki McNickle (1984). Forcible rape. In Robert Meier (ed.),

Major Forms of Crime, Vol. 21. Beverly Hills: Sage Publications, pp. 47–72.

Riger, Stephanie and Gordon, Margaret (1981). The fear of rape: A study in socialcontrol. Journal of Social Issues 37, 71–92.

Russell, Dianna (1975). The Politics of Rape, the Victim’s Perspective. New York: Stein

& Day.Sanday, Peggy Reeves (1981). The socio-cultural context of rape: A cross-cultural study.

Journal of Social Issues 37, 5–27.Schwendinger, Julia and Schwendinger, Herman (1983). Rape and Inequality. Sage

Publications: Beverly Hills.Shaw, Clifford and McKay, Henry (1942). Juvenile Delinquency and Urban Areas.

Chicago: University of Chicago Press.

U.S. Department of Justice (2000). Criminal Victimization in United States, 1999 Sta-tistical Tables. National Crime Victimization Survey, NCJ 184938.

U.S. Department of Justice (2000). Violent Victimization and Race 1993–1998. National

Crime Victimization Survey, NCJ 176354.U.S. Department of Health and Human Services (1988). Supplements to the monthly

vital statistics report: Advanced reports, 1988.


Vieraitis, Lynne M. and Williams, Marian R. (2002). Assessing the impact of gender

inequality on female homicide victimization across U.S. cities: A racially disaggre-gated analysis. Violence Against Women 8, 35–63.

Whaley, Rachel Bridges (2001). The paradoxical relationship between gender inequalityand rape: Toward a refined theory. Gender & Society 15, 531–555.

Whaley, Rachel Bridges and Steven F. Messner (2002). Gender equality and genderedhomicides. Homicide Studies 6, 188–210.

Williams, J.E. and Holmes, K.A. (1981). The Second Assault: Rape and Public Attitudes.

Westport, CT: Greenwood.


Race-Specific Gender Equality and Rape: A Further Test of Feminist Hypotheses

Documents

Transcript of Race-Specific Gender Equality and Rape: A Further Test of Feminist Hypotheses