Gender Inequality and Levels of Female Homicide in Cities: Examining the Influence of
Race, Poverty Context, and Family Structure for Levels of Female Homicide
Victimization and Offending
DISSERTATION
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy
in the Graduate School of The Ohio State University
By
Meghan Elizabeth Myers, M.A.
Graduate Program in Sociology
The Ohio State University
2013
Dissertation Committee:
Dr. Ruth D. Peterson, Advisor
Dr. Elizabeth G. Menaghan
Dr. Dana L. Haynie
Copyrighted by
Meghan Elizabeth Myers
2013
ABSTRACT
In the United States, Black women are at an increased risk of homicide
victimization and offending when compared to White women. What accounts for these
differences in homicide involvement for Black and White females? Spanning the last
thirty years, feminist theory has called attention to the importance of examining how
structures relating to gender contribute to killings by and of females. Empirical work in
this area has highlighted that relative differences in men and women’s social and
economic positioning in the United States, known as socioeconomic gender inequality,
are important for city levels of female homicide victimization and offending. Few of
these studies, however, have considered other structural factors that may be contributing
to homicide by and of females. As a result, we know little about how race influences the
relationship between socioeconomic gender inequality and female homicide involvement
for the 2000 period. We also have limited information on how city poverty contexts or
family structure contribute to female homicide victimization and offending for women of
different racial groups. As such, our knowledge regarding the differential structural
causes of Black women’s increased risk of homicide victimization and offending when
compared to White women’s is incomplete.
Drawing on feminist theories of homicide, this dissertation attempts to contribute
to our current understanding of how structures of gender inequality contribute to killings
iii
by and of women from different walks of life. Toward this end, I utilize data from the
Federal Bureau of Investigation’s Supplementary Homicide Reports, a voluntary
reporting database that includes city level information on the sex, age, and race of
homicide victims and known offenders. Social and demographic information is drawn
from the United States Bureau of the Census for 2000. These data are used to answer the
following questions. First, is socioeconomic gender inequality related to killings by and
of both Black and White females for the 2000 period? Based on previous research,
socioeconomic gender inequality should be related to White female homicide
victimization and offending but not necessarily to Black women’s levels of killing or
being killed. This idea is tested using negative binomial regression. The results
demonstrate that socioeconomic gender inequality does indeed influence city levels of
homicide, but only for White females and with regards to victimization. In particular,
higher levels of socioeconomic gender inequality are significantly related to lower levels
of White female homicide victimization. No relationship is found between White female
homicide offending and socioeconomic gender inequality. And, paralleling prior
research, socioeconomic gender inequality is unrelated to city level killings by and of
Black females. Rather, women’s absolute status in the most important gender related
variable for levels of Black female homicide victimization and offending.
This study also examines how city poverty contexts influence the gender
inequality-homicide relationship. Some feminist scholars have long asserted that high
levels of poverty make women more vulnerable to violence stemming from
socioeconomic gender inequality. Accordingly, the relationship between gender
iv
inequality and homicide may be expected to be stronger in high poverty city contexts for
both Black and White females. Alternatively, socioeconomic gender inequality matters
less in low poverty city contexts. The results from the negative binomial regression are
contrary to some feminist arguments. With regards to high poverty city contexts, no
relationship is observed between levels of socioeconomic gender inequality and rates of
homicide victimization or offending for Black or White females. In low poverty city
contexts, socioeconomic gender inequality only exhibits a relationship to city levels of
White female homicide victimization. No relationship is observed between these factors
for Black females in low poverty city contexts.
In a final set of exploratory analyses, I examine the effects of four familial related
variables, along with socioeconomic gender inequality, on levels of killings by and of
Black and White females. I do so in response to arguments presented by scholars of
female homicide that family structure potentially captures aspects reflecting gender
inequality that are not reflected in traditional measures used in feminist research of
homicide. I ask: Are variables argued to represent women’s greater independence from
men and more familial equality between the sexes, (for example, non-traditional family
structures such as higher rates of cohabitation, single father households, and female
divorce and separation rates) related to lower rates of female homicide as suggested by
Vickie Jensen (2001)? Or, as suggested by other scholars of female homicide, are more
extensive levels of non-traditional family arrangements associated with higher levels of
female homicide, as might be expected if these factors reflect aspects of general social
instability? The results for family variables indicates that, by and large, non-traditional
v
family arrangements are related to higher levels of killings by and of White females, but
are unrelated to Black female homicide involvement.
Overall, this dissertation shows that socioeconomic gender inequality influences
Black and White female homicide differently. The findings also reveal that city poverty
contexts, in addition to race, matter for female homicide victimization, although not in
the way anticipated. Rather than demonstrating that gender inequality exerts a stronger
effect on levels of female homicide in high poverty city contexts, the results indicate that
socioeconomic gender inequality is only important for White females in low poverty city
contexts. When high poverty contexts are taken into account, the relationship between
socioeconomic gender inequality and White female homicide victimization no longer
holds. In this regard, the findings for White females in high poverty contexts parallel
those of Black females that women’s absolute status is related to levels of homicide
victimization. Family structure also emerges as an important factor for levels of White,
but not Black, female homicide. In contrast to arguments that greater levels of
cohabitation, single father households, and divorce and separation rates reduce homicide,
in general higher levels of non-traditional family structures seem to contribute to more
homicides by and of White females.
Certainly, the structures contributing to killings by and of females are
multifaceted and merit further investigation. By evaluating the multiple ways in which
gender inequality may potentially be related to city levels of female homicide
victimization and offending, this dissertation advances research on female homicide in
several ways. First, the findings highlight that women are not situated similarly with
vi
regards to their multiple statuses, and this fact may shape the relationship between gender
inequality and city levels of female homicide. Second, the results call attention to the
potential role of family structure for influencing city levels of homicide victimization and
offending, and point to multiple indicators specific to women that have implications for
analyses of female homicide.
Third, this dissertation calls into question extant theories on the relationship
between socioeconomic gender inequality, poverty, and homicide by demonstrating that
the role of socioeconomic gender inequality is variable depending upon poverty context,
as well as women’s racial background. In total, this study accentuates the need for
empirical work to identify and examine additional status differences among women that
may help to illuminate the structural causes of female homicide and, in turn, point to
solutions that could benefit those most at risk for high levels of homicide victimization or
offending.
vii
ACKNOWLEDGEMENTS
Many people have helped me on my path to completing this dissertation. I would
first like to express thanks to my advisor, Dr. Ruth Peterson, who guided me through the
process of learning how to do academic research. Without her dedication to my success
and the time and energy she spent coaching me, I would not have been able to complete
this dissertation. I thank her for her support, guidance, and her continued commitment to
helping students to conduct interesting and important sociological research. I would also
like to express my gratitude to. Dr. Elizabeth Menaghan for her helpful comments
relating to issues of the family and for always listening and providing useful information
throughout the process of my tenure as a graduate student. I am thankful to Dr. Dana
Haynie for the time and energy she spent serving as a committee member, as well as her
insightful comments. In addition, I would like to express thanks to Dr. Lauren Krivo for
imparting her excellent knowledge of statistics and her numerous consultations regarding
this project.
I never would have made it this far without my fellow cohorts and friends Heather
Washington, Anna McCreary, Khayyam Qidwai, and John Vaughn. Thank you for all
your encouragement, long talks, fun times, and heartfelt support. I’d also like to express
gratitude for your help and advice on courses, research, and teaching. You are wonderful
people and I am lucky to have met you.
viii
To my family. First, thanks for encouraging me to push myself and work hard,
and for giving me the wisdom and life skills necessary to do so. To Mom and Dad; thanks
for always being there to listen, for your encouragement, for help with editing (Mom), for
giving me travel money whenever I came home (Dad), and for always being great role
models. I love you. Brandon, thanks for always being there to talk and for your helpful
advice. You are a smart cookie. Also, thank you for imparting your wisdom on statistics,
academics, and life. To my grandma, thanks for your love and support. To grandpa, I
know you would have been proud for me to reach this day. I wish you could be here to
see it. Finally, thanks to Jake, for helping me with formatting my dissertation and editing.
More than anything thanks for putting up with me while writing this and for being there
every step along the way. This moment would not have been possible without all of the
hard work, support, sacrifices, and most importantly, love from my family.
ix
VITA
2002................................................................John Adams High School
2006................................................................B.A. Sociology/Spanish, Indiana University
2009................................................................M.A. Sociology, Ohio State University
2006-2009 .....................................................Graduate Teaching Associate, Department
of Sociology The Ohio State University
2006-2012 ......................................................Independent Instructor, Department of
Sociology, The Ohio State University
PUBLICATIONS
Lundman, Richard J. and Meghan E. Myers. 2011. “Explanations of Homicide
Clearances: Do Results Vary Dependent Upon Operationalization and Initial
(Time 1) and Updated (Time 2) Data?” Homicide Studies. 16(1):23-40.
FIELDS OF STUDY
Major Field: Sociology
x
TABLE OF CONTENTS
ABSTRACT ................................................................................................................. iii
ACKNOWLEDGEMENTS ....................................................................................... viii
VITA ..............................................................................................................................x
.
PUBLICATIONS ...........................................................................................................x
FIELDS OF STUDY......................................................................................................x
LIST OF TABLES ..................................................................................................... xiii
CHAPTER 1: INTRODUCTION ..................................................................................1
CHAPTER 2: FEMINIST THEORY, GENDER INEQUALITY, AND RACIAL
DIFFERENCES IN FEMALE HOMICIDE VICTIMIZATION
AND OFFENDING .....................................................................................................18
Perspectives on Female Homicide ..........................................................................23
Gender Inequality, Family Structure, and Female Homicide .................................36
Other Factors Associated with City Levels of Homicide .......................................43
CHAPTER 3: DATA AND METHODS .....................................................................44
Data .........................................................................................................................45
Measures .................................................................................................................46
Analytic Strategy ....................................................................................................51
CHAPTER 4: DESCRPTIVE STATISTICS AND MULTIVARIATE RESULTS
FOR THE RELATIONSHIP BETWEEN SOCIOECNOMIC GENDER
INEQUALITY AND FEMALE HOMICIDE .............................................................53
The Distribution of Female Homicide, Independent, and Control Variables .........54
Socioeconomic Gender Inequality and Homicide Victimization and Offending ...64
Poverty Contexts, Race, and the Relationship Between Socioeconomic Gender
Inequality and Female Homicide Victimization and Offending .............................71
CHAPTER 5: AN EXPLORATORY ANALYSIS OF FAMILIAL INEQUALITY
AND FEMALE HOMICIDE VICTIMIZATION AND OFFENDING ......................78
Multivariate Results for the Relationship Between Familial Variables and Female
xi
Homicide Victimization………………………………………………………….80
Multivariate Results for the Relationship Between Familial Variables and Female
Homicide Offending ...............................................................................................84
Familial Variables, Poverty Contexts, and White Female Homicide
Victimization and Offending ..................................................................................88
CHAPTER 6: CONCLUSION ....................................................................................97
REFERENCES ..........................................................................................................113
APPENDIX A: CITIES WITH POPULATIONS OVER 100,000 EXCLUDED
FROM THE ANALYSES .........................................................................................123
APPENDIX B: OPERATIONALIZATIONS OF ALL VARIABLES INCLUDED 6
IN THE EMPIRICAL CHAPTERS ..........................................................................124
APPENDIX C: DESCRIPTIVE STATISTICS FOR LOW AND HIGH CITY
POVERTY CONTEXTS ...........................................................................................126
APPENDIX D: CORRELATION MATRICES OF ALL VARIABLES FOR
TOTAL, BLACK, AND WHITE FEMALES ...........................................................130
xii
LIST OF TABLES
Table 1: Means and Standard Deviations for Female Homicide Victimization and
Offending, Socioeconomic Gender Inequality, Familial Aspects, and Control
Variables………………………………………………………………………………....55
Table 2: Multivariate Results for Female Homicide Victimization, Socioeconomic
Gender Inequality, and Control Variables by Race .......................................................... 66
Table 3: Multivariate Results for Female Homicide Offending, Socioeconomic Gender
Inequality, and Control Variables by Race ....................................................................... 70
Table 4: Multivariate Results for White and Black Female Homicide Victimization and
Offending, Socioeconomic Gender Inequality, and Control Variables in Low Poverty
City Contexts .................................................................................................................... 74
Table 5: Multivariate Results for Female Homicide Victimization and Offending,
Socioeconomic Gender Inequality, and Control Variables in High Poverty City
Contexts ............................................................................................................................ 77
Table 6: Multivariate Results for White Female Homicide Victimization, Socioeconomic
Gender Inequality, and the Independent Effects of the Familial Variables ...................... 82
Table 7: Multivariate Results for Black Female Homicide Victimization, Socioeconomic
Gender Inequality, and the Independent Effects of the Familial Variables ...................... 83
Table 8: Multivariate Results for White Female Homicide Offending, Socioeconomic
Gender Inequality, and the Independent Effects of the Familial Variables ...................... 85
Table 9: Multivariate Results for Black Female Homicide Offending, Socioeconomic
Gender Inequality, and the Independent Effects of the Familial Variables ...................... 87
Table 10: Multivariate Results for White Female Homicide Victimization, Familial
Variables and Socioeconomic Gender Inequality in Low Poverty City Contexts ............ 89
xiii
Table 11: Multivariate Results for White Female Homicide Victimization, Familial and
Socioeconomic Gender Inequality, and High Poverty City Contexts............................... 91
Table 12: Multivariate Results for White Female Homicide Offending, Familial and
Socioeconomic Gender Inequality, and Low Poverty City Contexts ............................... 92
Table 13: Multivariate Results for White Female Homicide Offending, Familial and
Socioecnomic Gender Inequality, and High Poverty City Contexts................................. 93
Table 14: Means and Standard Deviations for Female Homicide Victimization and
Offending, Socioeconomic Gender Inequality, Familial Aspects, and Control
Variables for Low Poverty City Contexts………………………………………………126
Table 15: Means and Standard Deviations for Female Homicide Victimization and
Offending, Socioeconomic Gender Inequality, Familial Aspects, and Control
Variables for High Poverty City Contexts……………………………………………..128
xiv
CHAPTER 1: INTRODUCTION
In the United States, there are significant racial disparities in patterns of violent
crime between different groups of women. This is reflected in rates of homicide
victimization and offending, where Black females are one and half times more likely to
be killed and nearly three times more likely to kill than White females (Federal Bureau of
Investigation 2000). As such, Black women have a higher risk of premature death,
incarceration for engaging in killing, and other consequences that flow from homicide
involvement when compared to their White female counterparts (Center for Disease
Control 2009; Greenfeld and Snell 2007). How do we account for these varying patterns
of homicide victimization and offending for women of different racial backgrounds?
Examinations of women’s involvement in homicide have drawn mainly on
feminist theories to suggest that gender inequality, defined as the relative difference in
socioeconomic status between women and men, is important in understanding women’s
levels of killing and being killed (Brewer and Smith 1995, DeWees and Parker 2003,
Gartner et. al 1990, Gauthier and Bankston 1997, Stout 1992, Vieraitis and Williams
2002, Whaley and Messner 2002). From this perspective, high levels of female killings,
whether defined in terms of victimization or offending, is the price that we pay for a
system of gender stratification that devalues and subordinates women to men, and
permits diffuse male aggression and violence to be directed against women (Blau and
1
Blau 1982). That is, according to feminist scholarship, killings of and by women
are a manifestation of a social system that perpetuates the political, social, and economic
subjugation of women to the benefit of men (Brownmiller 1975; Clark and Lewis 1997;
Connell 1995; Kimmel 1996; Russell 1975; Sanday 1981). On the one hand, high levels
of women’s violent victimization, including its lethal form, is a tool that helps to (1)
maintain female subjugation and (2) prevent women from challenging their subordinate
position and achieving social and economic parity with men (Browne 1997; Browne and
Williams 1993; Brownmiller 1975; Campbell 1992; Griffin 1971; MacKinnon 1989;
Messerschmidt 1986; Millet 1970; Polk 1994). On the other hand, high levels of
homicide offending by females is posited to result from women responding in kind to
violence as members of this group attempt to protect themselves (and perhaps others such
as their children) from violence (Browne 1987; Fagan and Browne 1994; Ferraro 1997;
Gillespie 1989; Goetting 1988; Mann 1996; Wolfgang 1958).
In elaborating on how gender inequality works to produce female crime, scholars
have pointed to the potential for levels of gender inequality to both foster and impede
rates of female homicide. Accordingly, what is known as the “ameliorative hypothesis”
suggests that in places and times where equality between women and men is greater,
hostility and violence toward women will be diminished (Ellis 1989; Ellis and Beattie
1983; Schwendinger and Schwendinger 1983; Whaley and Messner 2002). This
amelioration of inequality will be evident in lower levels of women’s homicide
involvement. The ameliorative hypothesis has received some empirical support from
studies of women’s homicide, particularly with regards to offending (Bailey and Peterson
2
1995; Jensen 2001; Reckdenwald and Parker 2008). Alternatively, the "backlash
hypothesis" suggests that lower levels of gender inequality may increase levels of male
aggression and violence towards women (Russell 1975), and in turn, female violence as a
reaction. This would occur if greater equality between women and men is viewed by a
large portion of the population as a threat to men's privileged positions relative to women
(Ferraro 1988; Mahoney 1994, Rubin 1994; Smith 1990). In such a context, attempts to
regain lost power and control may take the form of greater violence against women
(Mahoney 1994). Consistent with the backlash viewpoint, a number of studies have
demonstrated that in areas where there is less gender inequality (more gender equality),
there are higher levels of female homicide involvement, particularly victimization
(DeWees and Parker 2003; Gartner et. a1. 1990; Gauthier and Bankston 1997, Vieraitis
and Williams 2002, Whaley and Messner 2002). Notably, there are slightly more studies
supporting the backlash thesis than the ameliorative hypothesis.
In addition to highlighting the importance of levels of socioeconomic gender
inequality for female homicide victimization and offending, studies have also suggested
that women’s absolute status may be an important factor for levels of killings by and of
women. Specifically, higher levels of social and economic achievement by women (e.g.,
education, income, employment, etc.) are believed to decrease women’s homicide
involvement, regardless of women’s relative status to men. Argument’s for the
importance of women’s absolute status mirror more traditional theories of homicide that
have been used to explain men’s or total levels of killing and being killed (e.g., Blau and
Blau 1979; Land et. al. 1990; Messner and Rosenfeld 1999; Sampson and Wilson 1995).
3
According to these perspectives, absolute status contributes to higher levels of
homicide by creating more opportunities for violence or increasing stress and frustration
that may lead to instances of homicide. As a result, women who live in less affluent cities
where their absolute socioeconomic status is comparatively worse may be more exposed
to violent crimes in general (e.g. Steffensmeier and Haynie 2000). Certainly the bulk of
research on violent crime rates would support the idea that greater disadvantage is
associated with higher levels of violence, with this being broadly true regardless of what
groups are under consideration. Notably, studies that consider gender inequality also
indicate that women’s absolute status plays a role in their rates of victimization and
offending (Bailey and Peterson 1995; Vieraitis and Williams 2002; Vieraitis et. al. 2008;
Reckdenwald and Parker 2008; Whaley and Messner 2002). Given the volume of
research showing the important role of absolute socioeconomic status in levels of street
crime and violence, the analyses below includes measures to capture the relationship
between Black and White females’ absolute social and economic status and their levels of
killing and being killed. However, these factors are treated as control rather than
explanatory variables, with the emphasis being on assessing whether above and beyond
females’ absolute socioeconomic status, gender inequality in socioeconomic and familial
status influence female homicide victimization and offending rates differently across
racial groups.
Prior studies have helped to shed light on general patterns of female homicide by
highlighting the importance of socioeconomic gender inequality for when women kill and
are killed. However, research has seldom gone beyond assessing the role of
4
socioeconomic inequality, the fundamental ameliorative or backlash hypothesis, and the
impact of absolute status (as a control variable or otherwise) for women as an aggregate
group. Most notably, very little attention has been paid to racial differences in female
homicide. Existing studies provide few insights on why female rates of killing and being
killed are so much higher for Black than White women, or how patterns of homicide for
women of different racial groups are differentially affected by unequal structural
conditions. Thus, additional scholarship is needed to identify the sources of female
killings, including the extent to which gender inequality is relevant to homicides of and
by women of different colors. The purpose of this dissertation is to address these
neglected issues in the literature on levels of female involvement in lethal violence as
victims and perpetrators. In doing so, the work goes beyond solely answering the basic
question of whether for each racial group the relationship between socioeconomic gender
inequality and homicide is one of amelioration or backlash. I also examine such
additional questions as: Do non-economic aspects of gender inequality contribute to
homicide involvement for the two groups?; and, Does the relationship between aspects of
inequality and female homicide hold for Black and White women in both high and low
poverty environments?
Why has the question of racial differences been neglected in structural analyses of
lethal violence by and against females? The answer may lie in the limitations of existing
conceptualizations of the gender inequality-female violence relationship, and/or in data
limitations that make it difficult to conduct disaggregated analyses of female crimes.
Conceptually, an underlying assumption of most gender inequality and violence
5
arguments is that they apply across the board to women from all walks of life. Flowing
from this assumption, most tests of gender inequality claims treat women as a single
group without attention to differences in levels of crime across groups, or to likely
differences in the potential impact of women’s circumstances (inequality or otherwise) by
race or other social statuses (e.g., ethnicity, age, social class) (Daly and Tonry 1997).
Empirically, females comprise a relatively small proportion of homicide victims and
offenders (24% and 12%, respectively). Consequently, most homicide studies have
focused exclusively on rates of male killings or on general rates for the total population
(Daly and Chesney-Lind 1988). Further, national homicide data with information on the
race and sex of homicide victims and offenders has only been available since 1976 when
the Federal Bureau of Investigation (FBI) made available the Supplementary Homicide
Reports (SHR) through its Uniform Crime Reporting (UCR) program. The availability of
these data makes it possible to examine more closely the structural contributors to levels
of homicide for differentially-situated females, for example with regards to women’s race
or age.
Why is it important to examine the role of gender inequality on homicide for
females from different status backgrounds? To begin, a sociological perspective suggests
that the large differences in rates of homicide victimization and offending for Black and
White females are not self-explanatory. Rather, they are driven by social processes,
including inequalities relating to gender and race, as well as women’s absolute status in
society. Therefore, empirical attention is needed to identify the factors driving differential
rates of killings by and of Black and White females. In addition to assessing the
6
structures contributing to female homicide for women of different racial backgrounds,
some claims in the literature have been neglected in prior work, have yielded
contradictory findings across studies, or have yielded findings that depart from feminist
theoretical claims. Below, I elaborate on the nature of the neglected issues.
First, feminist scholars-of-color point out that structures pertaining to the racial
organization of U.S. society may shape the distributions of homicide for Black and White
females (Collins 1990, Davis 1981, hooks 1984; Martin 1994; Richie 1994). In
particular they argue that examinations of violence should take into account the
possibility that race and gender intersect in ways that may contribute to a double
disadvantage for Black women. Black women may experience discrimination and
oppression due to their status as females, and face racial oppression stemming from their
status as members of a subordinate racial minority group, resulting in additional social
and economic disadvantages (Collins 1990, Davis 1981, hooks 1984; see also works by
Baca-Zinn and Thornton-Dill 1996, Burgess-Proctor 2006, Sokoloff and Dupont 2005
who argue that women’s behavior and resulting aggregate patterns are simultaneously
influenced by their multiple statuses). Regarding homicide, this “double whammy” of
being Black and female in U.S. society may render Black women (compared to their
White counterparts) particularly vulnerable to lethal violence stemming from a gender
unequal society (Martin 1994; Richie 1984).
Second, the arguments of the above scholars notwithstanding, two recent studies
fail to substantiate this “double whammy” argument. Specifically, Vieraitis and Williams
(2002) assessed the gender inequality-female homicide victimization relationship for
7
Black and White females for 1990. They found that although socioeconomic gender
inequality is related to city wide levels of White female homicide victimization, there is
no such relationship for homicides against Black women. Similarly, Haynie and
Armstrong (2006) demonstrated a strong association between socioeconomic gender
inequality and levels of homicide offending by White but not Black females for the same
time period. By examining the influence of gender inequality on homicides against and
by Black and White women separately, the studies by Vieraitis and Williams (2002) and
Haynie and Armstrong (2006) acknowledge the potential for race and gender to
simultaneously shape women’s homicide involvement. As such, they also offer starting
points for further consideration of how gender inequality varies in its influence on female
homicides across women of different racial backgrounds.
Third, occasional theoretical arguments draw attention to the possibility that
women in contexts of high poverty might be especially vulnerable to violence stemming
from gender inequality. For example, Messerschmidt (1986; 1993) argued that
disparities in equality between females and males matter more for violent victimization of
females in high poverty than in low poverty contexts. This is because in more affluent
contexts a relatively small proportion of the population experiences intense economic
deprivation and resulting frustration. Furthermore, women are better able to afford a
more secure living situation.
In contrast, for women in less affluent contexts, associated material and status
deprivation with its resulting frustration (especially for males) likely results in more
diffuse aggression. Further, in such places females may lack the resources necessary to
8
live free of violence (C. Williams 1995). As such, high poverty contexts are believed to
generate more violent behavior overall, and where there is greater gender inequality,
more of this violence is expected to be channeled toward women (Burgess-Proctor 2006;
Martin 1994; Messerschmidt 1986; 1993; Richie 1984; Saunders 1992; Stanko 1985).
Further, because Blacks in the United States are more likely than Whites to reside in
cities and areas of high poverty (Peterson and Krivo 2010), assessing the gender
inequality-female homicide relationship might be expected to reveal that gender
inequality matters more for Black than White females. Yet, researchers have not given
sufficient attention to this possibility to date.
Finally, some scholars have raised the possibility that certain non-economic
aspects related to structural gender inequalities may contribute to when women kill and
are killed. Jensen (2001) evaluated the role of familial inequality on female homicide
offending levels within cities. Drawing on works (e.g., Abott and Wallace 1990, Chafetz
1984, Chandler 1991) that point to traditional marriage in the United States as an
institution by which gender inequality may potentially be created and maintained, Jensen
(2001) suggests that larger numbers of women living outside of marriage within cities
(e.g. female divorce and separation rates, cohabitation, along with a greater share of
single-father households) denotes a more gender equal environment. In such settings,
women are not as restricted and may be more able to avoid abusive situations that could
escalate into homicide. Such equality, she hypothesized, will reduce women’s homicide
involvement in terms of both offending and victimization. Empirically, Jensen found that
9
factors relating to family structure, most notably the city level of cohabitating
households, are negatively related to levels of female homicide offending.
Jensen’s findings are relevant to the present effort not only because they point to
structures other than socioeconomic gender inequality that may affect female
involvement in homicide, but also because some of the measures she utilizes to indicate
equality, (e.g. divorce and separation) have traditionally been argued to contribute to
higher rather than lower female offending or victimization. This is because traditional
institutions such as marriage have also been hypothesized to contribute to greater social
stability and organization within areas which is associated with lower levels of many
types of violent crime, including homicide (see Parker and McCall 1990). With regards to
female homicide specifically, it has also been argued that marriage is protective for
women, reducing their opportunities for violent crime and sheltering them from greater
exposure to public life where they may be at greater risk for killing or being killed
(DeWees and Parker 2003; Messner and Tardiff 1984). However, the role of family
structure has yet to be evaluated thoroughly with regards to racial differences or female
homicide victimization and offending.
In brief, data are now available that allow for consideration of the structural
determinants of female homicide victimization and offending for females from different
status backgrounds. Nonetheless, researchers have only provided a limited amount of
information on racial differences in such killings. Two extant articles (Haynie and
Armstrong 2002; Vieriatis and Williams 2006) are helpful, but they leave some
fundamental questions unanswered.
10
First, in the context of the 2000s are levels of socioeconomic gender inequality
associated with levels of female homicide victimization and offending for both White and
Black women across U.S. cities? Both Haynie and Armstrong (2006) and Vieraitis and
Williams (2002) focus on the 1990 period when homicides peaked and began to decline.
Since the early 1990’s, there has been a period of continuous decline in killings (Cooper
and Smith 2011). Furthermore, patterns of gender inequality are different from those that
prevailed in 1990. For example, 2000 data indicate that both Black and White women
have made at least some gains in socioeconomic status since 1990 (England 2003). This
is evident in women’s rates of employment and occupation in professional occupations
for 2000 (Bureau of the Census 2000). Gains in women’s status relative to men’s have
been particularly notable for Black women (Bureau of the Census 2000). The changes in
women’s social and economic standing relative to men’s since 1990 makes it imperative
to ask whether the result is “backlash,” particularly for Black women and homicide
victimization? Or if current levels of gender socioeconomic inequality mean a decline of
gender inequality and lower levels of violence in favor of the ameliorative hypothesis?
Second, does the relationship between gender inequality and female homicide
hold for Black and White women in places with high- and low-levels of poverty?
Despite long held assumptions about the role of poverty for gender inequality, the
question of whether city levels of poverty influence the gender inequality-homicide
relationship has remained unaddressed in the general criminology literature. Here, I ask
the question that feminist scholars have posed of whether women situated in higher
11
poverty areas are more vulnerable to violence stemming from gender inequality than
women positioned otherwise (Messerschmidt 1983; 1996).
Third, I ask: Do non-economic aspects of gender inequality also contribute to
Black and White female homicide? Both feminist theory and empirical works have
suggested that gender inequality with respect to family structure may be relevant to
female killings as male control over domestic life and strict adherence to traditional
gender roles are a primary aspect of societies where male dominance is built into the
social organization of society (often traditionally referred to as patriarchy) (Browne 1997;
Chafetz 1984; DeWees and Parker 2003; Jensen 2001; Saunders 1992). There is limited
empirical work on this issue. However, the findings are mixed regarding the direction of
influence of familial structure on rates of female homicide. Thus, more work is needed on
how family structure contributes to levels of female killing and being killed, and
especially how this relationship works for women of different racial groups in the 2000
period.
Present Research
The goal of this dissertation is to shed light on the extent to which gender
inequality influences city-rates of Black and White female homicide involvement for the
2000 period. To answer the above questions, this dissertation utilizes the Federal Bureau
of Investigation’s Supplementary Homicide Reports as well as United States Bureau of
the Census data. Data are obtained for 199 U.S. cities with total populations of 100,000
or greater and Black populations of 2,000 or greater for the 2000 time period. Relying on
12
negative binomial regression procedures, the empirical analyses proceed in several
stages. Following the precedent set by prior research, the first stage evaluates the role
that socioeconomic-related dimensions of gender inequality play in city-level rates of
homicide victimization and offending first for total and then separately for Black and
White women. Specifically, I evaluate the impact of four aspects of gender inequality on
female homicide: male relative to female levels of income, employment, education, and
occupational status. By examining the links between these aspects of gender inequality
and Black and White female involvement in homicide, this dissertation assesses the
merits and scope of application of a long-held perspective on female crime for a
contemporary period. In the process, I also demonstrate whether the different patterns
found for Black and White women's homicide victimization (Vieraitis and Williams
2006) and offending (Haynie and Armstrong 2006) considered in 1990 have relevance
for the 2000 period, and establish whether the ameliorative or the backlash hypothesis has
greater relevance for the 2000 period and for Black versus White female killings.
Following from the basic analyses of the role of gender inequality, the second
stage of this dissertation assesses the relationship between gender inequality and female
homicide involvement for cities with varying levels of poverty. The focus on this issue
harkens back to scholarship raising the possibility that compared to women in more
affluent contexts, women in poorer contexts are at an elevated risk of homicide
victimization and offending due to diffuse aggression and violence from males mired in
environments of deprivation and frustration (Messerschmidt 1986). According to some
feminist thought, in cities characterized by greater poverty, women’s homicide
13
victimization and offending should be more heavily influenced by levels of gender
inequality. Further, attention to this issue may be particularly relevant when making
comparisons across Black and White women, who are quite differentially situated in U.S.
urban areas with respect to levels of poverty (Martin 1994; Richie 1984).
In the final stage, I look at expanded models of gender inequality that account for
inequalities in family structure for Black and White female homicide. Doing so is in
response to arguments that conceptualizations of gender inequality are incomplete and
that they ignore fundamental differences in aspects of male-female relationships that may
be especially important in explaining violent crime (DeWees and Parker 2003, Jensen
2001). Toward this end, I look at the levels of cohabitating and single father households,
as well as the ratio of men to women unmarried and female divorce and separation rates,
and their influence on homicide levels. According to Jensen (2001), higher levels of
single father and cohabitating households should represent more gender equality and
reduce female homicide involvement. On the other hand, higher levels of divorce and
separation may increase female homicide by contributing to social instability, leading to
higher levels of killings by and of females (DeWees and Parker 2003).
Contributions
By addressing the above questions, this research builds upon our knowledge of
women and crime in the following ways. In the most basic sense, this dissertation
provides tests of whether feminist arguments are relevant to explanations of levels of
homicide for women for the 2000 period and for women of different racial groups. Such
14
an analysis accounts for changes in gender inequality that have occurred in the 1990 and
2000 time period for Black and White women. In doing so, I also hope to contribute to
knowledge on why rates of homicide victimization and offending are markedly higher for
Black women and how structures of inequality contribute to racial disparities in homicide
involvement. By better understanding the economic and social mechanisms which
contribute to women's homicide with regards to race, we may better inform policy that
could intervene to stop one of the major causes of preventable death for young Black
women.
Another contribution of this dissertation evaluates whether long held feminist
assumptions regarding the role of poverty for women’s experience of gender inequality is
true with regards to levels of homicide victimization and offending. It has long been
suggested that higher poverty contexts are associated with even greater levels of violence
resulting from gender inequality and directed toward women. However, this has not been
empirically established. Furthermore, this has not been evaluated with regards to race.
Finally, this dissertation provides an exploratory examination of how the family,
one of the major sites by which gender inequality is believed to be reproduced and
maintained, contributes to female homicide levels. I do so by considering how family
related variables, specifically ratios of unmarried men to unmarried women, female
divorce and separation rates, cohabitation, and single father households influence
women's homicide involvement. Doing so contributes to a broader empirical test of the
multiple ways that structures of gender inequality relate to killings by, and of, women. By
looking at familial variables with regards to their theorized potential to both increase and
15
decrease female homicide involvement, this study also establishes if non-traditional
family structures indicate women’s greater freedom in society at large, and consequently
lower homicide rates, or less protection of females and a subsequent greater homicide
risk. Furthermore, this dissertation will be the first of its kind to contribute knowledge on
whether or not familial gender inequality has a unique influence for Black and White
women.
Chapter Organization
The following summarizes the content of the remaining chapters of this
dissertation. In chapter two, I discuss in greater depth the potential links between gender
inequality and homicide involvement and why it is important to consider including race
and additional measures of gender inequality when evaluating women's homicide
involvement. In addition, I review feminist arguments regarding the expectations of the
relationship between gender inequality and homicide involvement. Furthermore, I discuss
the importance of considering varying levels of poverty when considering when women
kill and are killed. In chapter three, I present the methodology for my analysis, describing
the data, variables, and analytic strategy for my dissertation. Chapter four provides
descriptive statistics and multi-variate analyses of the relationship between
socioeconomic gender inequality and homicide victimization; first for cities overall and
then by poverty contexts. Chapter five assesses each of the familial variables
individually, along with the control variables, for Black and White female’s homicide
victimization and offending. Chapter six interprets the results of the findings, providing a
16
discussion about the ways in which the present research fits into theory on gender
inequality and female homicide involvement. In addition, I discuss what implications
gender inequality has for Black and White women. Finally, the contributions of this
research, as well as implications for future research on gender, race, and homicide are
discussed.
17
CHAPTER 2: FEMINIST THEORY, GENDER INEQUALITY, AND RACIAL
DIFFERENCES IN FEMALE HOMICIDE VICTIMIZATION AND OFFENDING
In the United States, rates of homicide victimization and offending for Black
women are substantially higher than for White women (Bureau of Justice Statistics
2011). Specifically, Black women are one and a half times more likely to be killed and
nearly three times more likely to kill than White females (Federal Bureau of Investigation
2000). As a result, Black women are more likely to both incur the social and emotional
costs that accompany homicide offending, such as incarceration, and to die at younger
ages than their White female counterparts. For example, homicide victimization is the
second leading cause of death for Black women between the ages of 18 and 25, while for
White women it is the fourth leading cause of death for that same age group (Center for
Disease Control 2010). Despite differences between Black and White females in levels of
homicide victimization and offending, and the implications this has for women’s life
chances, the structural factors accounting for these differences are not well understood.
Research examining racial differences in levels of female homicide victimization
and offending is somewhat limited. This is largely due to the fact that women have
received a relatively small share of the attention given to investigations of homicide.
Consequently, less attention has been paid to how social structures contribute to homicide
behavior of women of different statuses (i.e., racial minorities and poor women) (Daly
and Tonry 1997). A paucity of research in this area is not surprising, given the well18
documented fact that women overall comprise a relatively small proportion of homicide
victims and offenders, around 24 percent and 12 percent respectively (Belknap 2006). In
addition to women’s lower levels of killing and being killed, data on the combination of
gender, race, and homicide has not been readily available to researchers. Thus, much of
the extant work on the structural causes of homicide has focused on total levels of
homicide involvement, without regards to status characteristics, particularly with regards
to race.
In trying to assess what factors contribute to homicide involvement,
criminologists often look to the organization of society, with particular regard to social
and economic conditions. Historically, studies of male or total homicide levels have
focused on urban areas where homicides are most likely to occur, in particular evaluating
the ways in which city level factors, such as general socioeconomic inequality, levels of
absolute deprivation, and social disorganization, are related to levels of homicide
involvement (Bursik 1989; Messner and Rosenfeld 1999; Wilson 1995; Wolfgang and
Ferracuti 1967). For example, through a variety of mechanism, such as increasing levels
of stress and frustration amongst members of society, evaluations of homicide
involvement have suggested that areas characterized by poverty are more conducive to
violent crimes such as homicide (Land, McCall and Cohen 1990; Messner and Rosenfeld
1999; Parker and McCall 1997; Sampson and Wilson 1995; Williams 1984; Williams and
Flewelling 1988, Wilson 1987, 1996). Also, Blau and Blau (1979) proposed that
homicide victimization and offending are simply an added “cost” of high levels of social
19
inequality, especially racial inequality in a society that purports to base rewards and
status on merit.
Typically, homicide studies do not examine male and female homicide behavior
independently. Although some attention has been paid to how race factors into general
socioeconomic inequality or absolute deprivation (see, Harer and Steffensmeier 1992;
Lee 2005; Peterson and Krivo 1993, 1996), little attention has been paid to the role of
race for women’s levels of homicide involvement. Race scholars who investigate women
and society, as well as feminist criminologists, however, argue that multiple structures
may be simultaneously important for providing a complete picture of how social
organization contributes to outcomes for different groups, including female crime (e.g.,
Collins 1990). Applied to the present context this means that in examining female
homicide victimization and offending it is important to consider the comparative
influence of factors for Blacks versus Whites, as well as for other groups.
Although there has been a general lack of attention to racial differences in
women’s homicide involvement, a handful of studies have attempted to identify the
social structures specific to total levels of female homicide victimization and offending.
Grounded in feminist research, such studies assert that the institution of gender is an
essential, and often overlooked, factor for understanding women’s violent behavior such
as homicide (Daly and Chesney-Lind 1988; Steffensmeier and Allen 1996). A body of
research has looked at the ways in which socioeconomic gender inequality influences
total city levels of female homicide victimization and offending (Bailey and Peterson
1995; Brewer and Smith 1995; DeWees and Parker 2003; Gartner, Baker, and Pampel
20
1990; Gauthier and Bankston 1997; Jensen 2001; Reckdenwald and Parker 2008; Whaley
and Messner 2002). Focusing primarily on establishing what types of socioeconomic
gender inequality are important for levels of homicide (i.e., education, occupation,
employment, income) and the direction of the relationship between gender inequality and
levels of homicide victimization and offending, this body of work has provided evidence
to suggest that socioeconomic gender inequality matters for female homicide. Few
investigations, however, have moved beyond fundamental tests of the relationship
between socioeconomic gender inequality and city levels of total female homicide (for
exceptions, see DeWees and Parker 2003; Haynie and Armstrong 2006; Jensen 2001;
Vieraitis and Williams 2002). As a result, there remain some gaps in the literature on the
structural causes of women’s homicide involvement at the city level.
First, little is known about how socioeconomic gender inequality influences
homicides for women of different racial groups. Rather, the assumption of most feminist
research on female homicide has been that women from different walks of life are
similarly influenced by structures relating to gender and race (Burgess-Proctor 2006;
Daly and Tonry 1997). Two studies are exceptions in demonstrating that race may be an
important factor in female homicide victimization and offending (Haynie and Armstrong
2006; Vieraitis and Williams 2002). However, as of yet no studies have provided an
examination of this relationship for time periods beyond 1990. Consequently, the
comparative role of socioeconomic gender inequality for Black and White women’s risk
of homicide involvement for the contemporary time period is not known.
21
Second, according to feminist thought, levels of poverty are an important
structural contributor to levels of women killing and being killed. In places with greater
poverty, it is argued, higher levels of gender inequality make violence by and of women
more likely through higher levels of diffuse aggression directed toward females
(Messerschmidt 1993). Whether higher levels of gender inequality in high poverty city
contexts lead to more female homicide involvement than similar levels in low poverty
city contexts has not yet been empirically established, either for the general population of
females or for females in different racial groups.
Lastly, as the bulk of research on gender inequality and homicide has limited the
conceptualization of gender inequality to socioeconomic status, other arguably important
indicators of gender inequality have been largely overlooked as contributors to women’s
involvement in homicide. Therefore, knowledge is limited with regards to the multiple
types of gender inequality women experience and which aspects of gender unequal
systems are most relevant for killings by and of Black and White females. Notably,
scholars of female homicide victimization and offending have proposed that family
structure may potentially influence rates of female homicide (DeWees and Parker 2003:
Jensen 2001). However, little empirical work has examined these potential relationships.
Furthermore, no studies have yet looked at the role of family structure and familial
inequality in killings for Black and White females.
In brief, several questions remain regarding the relationship between gender
inequality and women’s homicide victimization and offending. What is the relationship
between socioeconomic gender inequality and homicide victimization and offending for
22
Black and White women for the 2000 time period? Does socioeconomic gender
inequality influence both Black and White women in similar ways with regards to
homicide victimization and offending, and for different poverty contexts? Beyond
socioeconomic inequality what other aspects of gender organization are relevant for when
women kill and are killed? How does family structure influence levels of women’s
homicide victimization and offending within cities? In the analyses that follow, I address
these questions. In the remainder of this chapter, I set the stage for the analyses by
elaborating on current feminist perspectives on homicide and assess extant research
regarding the general relationship between socioeconomic gender inequality and
women’s homicide victimization and offending.
Perspectives on Female Homicide
According to feminist scholarship, violent behaviors carried out by and toward
women cannot be fully understood without first acknowledging the importance of the
institution of gender (Daly and Chesney-Lind 1988). One of the most commonly
referenced interpretations of the impact of gender on levels of female homicide focuses
on social systems of gender inequality (Baron and Straus 1989; Bailey and Peterson
1992; Whaley and Messner 2002; Vieraitis and Williams 2008). In particular, levels of
female homicide and victimization are believed to be driven by aspects related to
“patriarchal” societies, including relative social and economic inequalities between
women and men (to the benefit of men), the promotion of ideologies of male supremacy
23
and female subjugation, as well as the use of violence to maintain built in structures of
gender inequality (Brownmiller 1975; Clark and Lewis 1997; Connell 1995; Kimmel
1996; Russell 1975; Sanday 1981). In society, such inequalities between women and men
are believed to influence levels of homicide victimization and offending by channeling
greater amounts of male aggression and violence toward women.
Within a gender unequal society, violence (and threats of violence) toward
women serve the purpose of keeping women from challenging systems of male power
(Brownmiller 1975; Griffin 1971; MacKinnon 1989; Messerschmidt 1986; Millet 1970).
Ideologies promoting gender inequality are also believed to serve as a context by which
male violence towards women is rendered a socially acceptable, if not encouraged, course
of action (Messerschmidt 1986, 1993; Viano 1992). This applies to many types of
violence, including physical assault, rape, and homicide. For example, rape has long been
argued by feminist scholars to be a form of violence used primarily against women as an
expression of male power and control (Russell 1975). Similarly, homicide victimization
may also be viewed as an expression of male domination and attempts to control
women’s behavior.
In particular, the lethal victimization of women is one of the extreme ways that
violence can be directed toward women (e.g., Bailey and Peterson 1995; Brewer and
Smith 1995). Additionally, where general levels of violence against women are high, its
stands to reason that there are more opportunities for violence against women to turn
lethal (Campbell 1992; Daly and Wilson 1988; Dobash et. al. 1992; Dutton and Golant
1995; Polk 1994). Although the factors driving killings of females were the initial focus
24
of gendered studies of homicide, female homicide offending has also been proposed by
feminist scholars to be driven by gender inequality. In particular, levels of killing by
females are suggested to be higher in areas characterized by gender inequality as women
respond in kind to violence (or the threat of same) perpetrated against them (Browne
1997; Chimbos 1978; Daniel and Harris 1982; Fagan and Bronwe 1994; Ferraro 1997;
Mann 1996; Wolfgang 1958).
Empirical studies have established support for links between structures of gender
inequality and killings by and of females. For example, several studies have examined
socioeconomic gender inequality and its influence on levels of female homicide
involvement. Such studies have demonstrated the potential for aspects related to gender
inequality to breed homicides by and of females, although the relationship between
socioeconomic gender inequality and homicide is not entirely straightforward (Bailey and
Peterson 1995; Brewer and Smith 1995; DeWees and Parker 2003; Gartner, Baker, and
Pampel 1990; Jensen 2001; Reckdenwald and Parker; Whaley and Messner 2002). For
example, while some studies have found that higher levels of socioeconomic gender
inequality are associated with higher levels of homicide victimization and offending
(Bailey and Peterson 1995; DeWees and Parker 2003; Whaley and Messner 2002;
Reckdenwald and Parker 2008, Smith and Brewer 1995; Vieraitis and Williams 2002)
others have found the opposite to be the case (Jensen 2001; Haynie and Armstrong 2006;
Reckdenwald and Parker 2008).
When considering insights offered by feminist research, mixed findings on the
direction of the relationship between socioeconomic gender inequality and homicide are
25
not unexpected. Feminist scholars have long argued that levels of socioeconomic gender
inequality have the potential to contribute to higher or lower levels of female homicide
victimization and offending. On the one hand, women’s greater access to social and
economic resources relative to men may translate into females being viewed as more
valuable members of society, diminishing male supremacy (Ellis 1989; Ellis and Beattie
1983; Whaley and Messner 2002). As systems of male control no longer need to be
maintained through violence, the result may be lower levels of women’s homicide
involvement. In other words, female victimization would be lower where there is greater
equality between the sexes. The expectation of lower levels of gender inequality being
associated with lower levels of female homicide victimization and offending has been
coined the “ameliorative hypothesis” (Whaley and Messner 2002).
On the other hand, greater equality between women and men has also been argued
by feminist theorists to have less than entirely beneficial effects for women in terms of
their violent victimization. What is known as the "backlash hypothesis" suggests that
lower levels of gender inequality may result in higher levels of violence directed toward
women (Russell 1975). Initially applied to rape, the backlash hypothesis suggests that
homicide is also an expression of male anger and resentment toward women (Baron and
Straus 1989; Ellis and Beattie 1983; Peterson and Bailey 1992; Russell 1975). Because
severe physical violence towards women may be done with the intention of controlling
female behavior and keeping women “in their place” (Gauthier and Bankston 2004), in
contexts and times of improving equality for women, men might feel a need to reclaim
their status as dominant social members. If so, it would not be surprising to find that
26
greater gender equality would be associated with more female homicide, whether
victimization or offending. However, it is also worth noting that a general assumption
concerning the backlash theory is that higher levels of female homicide victimization and
offending are temporary, and should eventually give over to amelioration of violence
once men adapt to women’s greater equality (Russell 1975).
Gender Inequality, Poverty Contexts, and Homicide
Feminist scholars have long noted that poverty plays an important role in how
different groups of women experience gender inequality. Specifically, it has been argued
that poor women, and those in high poverty contexts, are especially vulnerable to gender
inequality with regards to violent victimization and offending (Messermschmidt 1993).
Areas characterized by high levels of poverty are argued to be conducive to high levels of
stress and frustration, especially among men. One form of adaptation to such frustration
may be violence directed toward women. Higher levels of stress and frustration
associated with conditions of poverty are argued to stem from the inability to achieve
basic material goals of society e.g., employment, and the challenge this poses to men’s
status as dominant social members and identity with regards to their roles as the material
providers for families (Vieraitis and Williams 2002) (Here, feminist scholars are drawing
on the basic premises of anomie and strain theories of crime rates; see, for example
Merton 1938; Messner and Rosenfeld 1993.)
To elaborate briefly, according to these strain-type arguments, gender
expectations of women and men in the United States have traditionally been that men are
27
singularly responsible for provide such resources for women and their family. This
“breadwinner” status is argued to be associated with power and control over the
household for men who provide material resources, as well as a central part of male
identity (Benston 1969; Haynie and Armstrong 2006; Jaggar 1993; Vieraitis and
Williams 2002). When there are institutional barriers to fulfilling this identity for large
segments of a population as would be the case in impoverished contexts, it is argued that
greater violence prevails and is directed toward women to replace the loss of power and
control experienced by men (Browne 1997; Messerschmidt 1986; 1993; Stanko 1985;
Saunders 1992). Consequently, higher levels of female homicide victimization and
offending are expected to result in areas characterized by greater amounts of poverty.
Further, where there are high levels of both gender inequality and poverty, not only is
violence more likely to be viewed as an acceptable course of action toward women, but
women may be unable to escape instances of male violence (C. Williams 1995).
Given the disparity in levels of economic wellbeing of Blacks and Whites, it may
be particularly important to account for poverty status in assessing the comparative levels
of homicide among Black and White women (Haynie and Armstrong 2006; Vieraitis and
Williams 2002). With regards to race, White men and women are typically situated in
U.S. society to experience higher levels of social and economic advantage when
compared to Blacks (Peterson and Krivo 2010). Higher levels of disadvantage among
Black men, it is argued, may increase levels of stress and frustration (Messerschmidt
1993), and set in motion the hypothesized violence noted above. Within the context of
greater gender inequality, this may result in greater amounts of violence directed toward
28
Black women. While these arguments seem logical, the ways in which impoverished
contexts influence the relationship between gender inequality and homicide for Black and
White women remains untested. This dissertation takes up the challenge of investigating
this issue in order to correct this omission in the literature.
To date, the majority of research on female homicide provides tests of the
ameliorative and backlash hypotheses to assess the overall relationship between levels of
socioeconomic gender inequality and levels of female homicide victimization or
offending. Therefore, the proceeding discussion is dedicated to assessing studies that
have considered the relationship between socioeconomic gender inequality and city levels
of female homicide victimization and offending. As well, I examine two studies that
have evaluated the gender inequality-homicide connection across racial groups.
Empirical Evidence on the Relationship between Socioeconomic Gender Inequality and
Female Homicides
Bailey and Peterson (1995) conducted the first test of female homicide
victimization. Prior to this study, evidence of the relationship between gender inequality
and female crime had come only from studies of the influence of gender socioeconomic
inequality on levels of rape (Ellis and Beattie 1983; Baron and Straus 1987, 1989;
Peterson and Bailey 1992). Bailey and Peterson questioned whether gender inequality
might also influence other forms of violence against women, such as homicide
victimization. As they noted, if rape is a crime of “hate and destruction” in a gender
unequal society, then murder, one of the most violent crimes that can be carried out
29
against women, may also be related to social and economic inequalities between women
and men (1995; p. 180).
To assess this possibility, Bailey and Peterson undertook a cross-sectional
analysis of 138 U.S. cities for the year 1980, drawing on data from the FBI’s
Supplementary Homicide Reports (SHR) and the United States Bureau of the Census.
Taking into account literature on general social stratification, racial inequality and crime,
in addition to gender inequality and rape, their analysis included four measures of gender
inequality between women and men These were male-to-female differentials in: the
percent with a college degree; the percent employed in managerial, professional, and
administrative occupations; the percent unemployed; and median yearly income in 1979.
Gender inequality was evaluated with regards to different types of homicide, including
domestic, acquaintance, and stranger related killings. Their study also included
demographic and socioeconomic controls, such as the divorce rate, population size, and
general income inequality.
Bailey and Peterson (1995) found support for feminist arguments, providing
evidence of the ameliorative hypotheses. They reported that although not all types of
victim-offender relationships are influenced by socioeconomic gender inequality,
findings pertaining to wife killings and acquaintance homicide support feminist
arguments. Specifically, the authors demonstrated that the rate of wife killings is
significantly higher in cities where the college education gap between males and females
is greater and where there are higher levels of female unemployment when compared to
men. With regards to acquaintance related homicides, the authors reported that higher
30
amounts of gender inequality in income are associated with higher levels of killings of
females. In all three cases, higher levels of gender inequality are associated with higher
levels of female homicide victimization. Or, where there is more gender equality, levels
of killings of females are lower. These findings offer support for the ameliorative
hypothesis.
Whaley and Messner (2002) provided a similar analysis to Bailey and Peterson’s
study, evaluating both homicide victimization and offending for a later time period, 1990,
and utilizing an index of gender inequality variable rather than evaluating the components
of inequality separately. To test the ameliorative and backlash hypotheses with regards to
the effect of socioeconomic gender inequality on homicide, the authors evaluate male
killings of women and men and female killings of women and men. Differing from most
other studies of female homicide, the authors assess the gender inequality-homicide
relationship according to the region where the homicides occurred, including the South,
Midwest, Western, Mid-Atlantic States, New England, and North Central States. The
authors utilize city level data from 1990- 1994 for 191 cities with populations greater
than 100,000. The authors also account for percentage poor, income inequality,
percentage Black, the percentage unemployed, and whether the city is located in a
northern or southern region. Whaley and Messner (2002) found in support of the backlash
hypothesis, but only for the South. In particular, their findings suggest that
socioeconomic gender inequality is positively associated with male killings of females.
However, the authors found that gender inequality is not significant in non-southern areas
such as the Midwest or Mid-Atlantic States.
31
In a study of types of women’s criminal offending, including homicide,
Reckdenwald and Parker (2008) report complex findings with regards to socioeconomic
gender inequality and women’s homicide offending. The authors evaluate crime levels
for 202 U.S. cities with a population of 100,000 or more in the 2000 period.
Reckdenwald and Parker (2008) assessed three components of socioeconomic gender
inequality: income, occupation, and higher education, while controlling for other factors
associated with female offending, including residential mobility, population size, and an
index of economic marginalization. The authors report that gender inequality in both
education and income are associated with levels of female killings of intimate partners.
However, these factors appear to influence homicide offending in different ways. Higher
levels of income inequality between women and men are related to lower levels of
intimate partner homicide, in favor of the backlash hypothesis. Alternatively, higher
levels of gender equality in education are associated with lower levels of female
homicide offending, in favor of the ameliorative hypothesis. The pattern for education is
consistent with Bailey and Peterson’s (1995) results for female victimization, where
greater inequality in education is associated with higher levels of female homicide
victimization.
Vieraitis and Williams (2002) also analyzed the relationship between
socioeconomic gender inequality and levels of homicide victimization within cities.
Building upon prior analyses, the authors provided the first study of the relationship
between socioeconomic gender inequality and female homicide victimization for women
of different racial groups. Utilizing SHR data for the 1990 period, the authors examined
32
the relationship between socioeconomic gender inequality, race, and homicide levels for
148 U.S cities. In addition to the criterion that city size be over 100,000 population, the
authors only included cities with Black populations of 2,000 or more in order to have
sufficient numbers by which to construct reliable variables. Similar to other studies of
female homicide, Vieriatis and Williams operationalized gender inequality in terms of
four dimensions, the ratio of male-female: median yearly income, percent employed
percent with a college degree, and percent in a professional/managerial occupation. They
also controlled for other factors associated with homicide, including a resource
deprivation index, population density, the divorce rate, and the youthful population.
In general, the authors’ findings indicate that greater levels of equality in
occupation, income, and employment are associated with higher levels of homicide
victimization for women when race is not taken into account. This finding is consistent
with the backlash hypothesis. When the authors tested gender inequality for Black and
White women separately, however, they found that while gender socioeconomic
inequality is associated with greater female homicide victimization for White women, it
is not associated with levels of homicide victimization for Black women. In particular,
the ratio of White women to White men employed full-time and the ratio of White
women to White men’s income are positively associated with levels of White female
homicide victimization. Alternatively, only absolute status is associated with levels of
Black female homicide victimization.
Haynie and Armstrong (2006) also considered the role of race in the relationship
between gender inequality and homicide for 148 cities with populations of at least
33
100,000 and Black populations of 5,000 or more. To evaluate how hypothesized
structures, most notably gender inequality, influence levels of female homicide, Haynie
and Armstrong (2006) use U.S. Bureau of the Census and SHR data for the 1990 period.
Two measures of gender inequality are utilized: female occupational opportunities
relative to male occupational opportunities; and the percentage of men in high-skilled
jobs to the percentage of women in high-skilled jobs. The authors also control for levels
of disadvantage, residential mobility, and racial equality.
Haynie and Armstrong (2006) demonstrated that socioeconomic gender
inequality is more closely associated with homicide offending for White than Black
women. In particular, they (2006) found that for White women, greater gender inequality
contributes to higher rates of intimate partner and family homicide, but this factor is not
associated with acquaintance or stranger homicide. For Black women, socioeconomic
gender inequality does not affect rates of family and intimate partner homicide, although
such inequality has a positive relationship with Black women’s rates of homicide
offending against strangers. Overall, Haynie and Armstrong’s work suggests that gender
equality is a stronger predictor of levels of White females’ homicide offending than
Black females’ homicide offending. Regarding direction of effects, their work supports
the ameliorative hypothesis but to a greater extent for White than Black women’s
offending.
In sum, evidence has been found that both socioeconomic gender inequality and
race are important factors for understanding city levels of killings by and of women. With
regards to the direction of the relationship between homicide and socioeconomic gender
34
inequality, two studies have found support for both the ameliorative and backlash
hypotheses, one study has found support only for the backlash hypothesis, and one has
found support only for the ameliorative hypothesis. Thus, research guiding the expected
relationship between gender inequality and levels of homicide victimization and
offending is mixed. Furthermore, given that homicide “backlash” is hypothesized to be a
short lived theory (Russell 1975), findings supporting the backlash hypothesis for 1980,
1990, and 2000 seem somewhat contrary to feminist arguments.
Contradictory findings among studies of female homicide may be due to a variety
of factors. For example, studies evaluating female homicide often use different measures
of socioeconomic gender inequality. Studies vary in the dependent variable under
consideration. Some consider overall patterns of female homicide victimization, others
study general levels of female homicide offending, and still others examine various
subtypes of homicide victimization or offending (e.g., intimate partner, stranger, etc.).
Along different lines, Bailey and Peterson (1995) and Vieraitis and Williams (2002)
operationalized gender inequality as four separate measures of income, occupation,
employment, and education, while Whaley and Messner (2002) utilized an index of
gender inequality variables. As a final example, the above studies examine different time
periods, with analyses spanning three different decades. Thus, differences in outcomes
could reflect differences in real world relationships across the three periods.
In short, prior research on homicide involvement has examined different
outcomes and utilized different measures of gender inequality for different time periods.
As such, it is difficult to draw firm conclusions about the relationship between gender
35
inequality and female homicide involvement. And most investigations do not speak to the
issue of race differences in the patterns and determinants of female killings.
Findings from the two studies that evaluate race differences provide promising
evidence that structures of race, in addition to gender, contribute to when women kill and
are killed. For example, Vieraitis and Williams (2002) found that socioeconomic gender
inequality is associated with levels of homicide victimization and offending, but only for
White women. This is in support of the backlash hypothesis. In terms of homicide
offending, socioeconomic gender inequality is associated with an increase in rates of
homicide, in favor of the ameliorative hypothesis, but more so for White women than
Black women (Haynie and Armstrong 2006). Consequently, it appears that when
disaggregated by race, gender inequality operates in the opposite direction for homicide
victimization and offending. Of note too, both the Vieraitis and Williams (2002) and
Haynie and Armstrong (2006) studies pertain to the 1990 time period. One question that
still has to be addressed is whether these patterns hold for earlier or later periods. I now
turn to a discussion of other factors that are arguably important to the study at hand.
Gender Inequality, Family Structure, and Female Homicide
In addition to race, extant research on gender inequality and homicide has also
begun to build upon fundamental tests of the ameliorative and backlash hypotheses by
examining multiple types of gender inequality. Some feminist scholars have argued that
concepts of gender unequal systems are complex and arguably should include multiple
aspects of inequalities between women and men. These include, but are not limited to,
36
inequalities in material resources, power to make decisions, and differing behavioral and
role expectations for women and men (Dunn, Almquist, and Chafetz 1993). Although the
bulk of research has represented gender inequality using indicators of social and
economic resources, some scholars have also evaluated the potential for other types of
gender inequalities, mainly inequality in family structure, to influence when women kill
and are killed (DeWees and Parker 2003; Jensen 2001).
Family structure is believed to be important to the study of aggregate levels of
female homicide as the majority of killings by and of women occur within the family
context (Belknap 2006). Furthermore, feminist scholars have argued that the family is a
primary institution by which gender inequalities are produced and maintained (Bell and
Newby 1976). Arguments by such scholars often center on the restriction of women to
domestic work, including unpaid child-care and housework, which is believed to
contribute to women’s dependence on men and to perpetuation of an imbalance of power
between the sexes (Ellis 1989; MacKinnon 1989; Millett 1970; Schechter 1982; Schlegel
1977; Schwendinger and Schwendinger 1983). Such dependence arguably translates into
men’s greater ability to maintain power and control over women. In areas where women
are more dependent on men within the family setting, higher levels of violence toward
women may be expected. Feminist scholars argue that domesticity may play a substantial
role in perpetuating gender inequality. In particular, traditional gender roles often result
in women engaging in work that has little monetary value (Blumberg 1979).
Additionally, residing in the domestic sphere may cut women off from the public domain,
consequently reducing their ability to form expanded social networks, which might
37
provide social, emotional, and economic resources (Peterson 1990). Marriage and family
structures may also be considered gender unequal as men typically receive greater
benefits from the emotional and household support provided by women. The unequal
division of benefits further holds up and contributes to men’s superior status, adding to
the lowered social status of women (Blumberg 1979).
Drawing on these themes, some feminist scholars have argued that certain familial
arrangements may indicate greater equality between women and men in society. For
example, lower levels of entry by women into marriage may indicate women’s lessening
dependence on men and lower levels of male control and domination (DeWees and
Parker 2003). The proportionate rise in cohabitating households over the last 15 years
may indicate greater flexibility in family structure (Fry and Cohn 2011), as well as a
broadening of viable alternatives to traditional marriage roles for women and men
(Jensen 2001). Similarly, a larger component of women who never marry may indicate
women’s greater independence from men, and consequently, declining control of females
by males.
As a final example, and in light of the presumed association between female
subjugation and women singularly caring for children, contexts where a greater share of
men have full responsibility for child care may indicate lower levels of gender inequality
(Jensen 2001). That is, similar to levels of cohabitation, the share of single father
households with children may reflect the degree of flexibility in family structure for the
setting (e.g., Fox and Allen 1987). Additionally, where men take on child-care
responsibilities, women may be less dependent on them for material resources.
38
Jensen (2001) perhaps provides the most comprehensive analysis of how familial
inequalities relate to levels of female homicide offending in her book, Why Women Kill.
In particular, she argues that homicide offenses are not just a product of a system of
gender stratification that economically marginalizes women. Rather, killings also result
from the social oppression that women face with regards to their expectations within the
family. For example, she stresses that traditionally female tasks, such as child rearing and
caretaking, are typically unpaid and underappreciated and that women, more so than men,
are expected to conform to expectations for marriage and domesticity. Jensen
hypothesizes that cities characterized by greater amounts of such familial “inequalities”,
in combination with socioeconomic inequality, are likely to have higher rates of female
homicide offending.
For Jensen (2001) rates of cohabitation, single father households, and unmarried
women (including divorced and separated), along with socioeconomic inequality between
the sexes, signal the extent to which society is characterized by gender inequality. She
argues that in areas where there are higher levels of cohabitation and unmarried females,
there is greater gender equality, greater flexibility in relationships, and more
opportunities for women to live outside of traditional marriage arrangements. Similarly,
higher levels of single father households may denote lower levels of inequality between
the sexes. In contrast, she proposes that greater proportions of unmarried women and
lower levels of cohabitation and fathers with primary responsibility for children may be
indicative of an imbalance of power between females and males where women are
39
expected to engage in traditional family arrangements, and in general “take a back seat to
men.”
To examine her ideas, Jensen tested models of female homicide offending that
included measures of inequalities between women and men in education, occupation,
income, and employment, as well as familial variables such as: cohabitation represented
by the percent of unmarried heterosexual and homosexual households; the divorce and
separation rate to capture social environments where women are freer to live outside of
marriage; and the percent of single male headed households with children as a measure of
the level of men engaged in primary child care.
Jensen (2001) found that some familial measures matter for women’s overall
homicide offending rates in ways that support the ameliorative hypothesis. Specifically,
higher cohabitation rates are associated with lower rates of female homicide offending.
However, she did not find support for her hypothesis that single father headed households
predict killings by females. And, contrary to Jensen’s expectations, the female divorce
and separation rate had a positive rather than negative relationship with women’s
homicide offending. While not supportive of Jensen’s familial inequality arguments, this
last point is consistent with the general findings of an array of studies showing that higher
levels of divorce contribute to higher levels of Violent (and property) crime. Indeed,
many scholars conceptualize divorce as representing the type of general instability in
society that would lead to higher general homicide rates within cities.
DeWees and Parker (2003) provide the most direct test of this idea as it pertains
to female killings. Specifically, they evaluate the relationship between socioeconomic
40
gender inequality and homicide for 168 U.S. cities for the year 1990. In addition to
socioeconomic gender inequality, the authors evaluate the role of family structure,
assessing whether the ratio of “unattached” (or unmarried women to men affects
homicide rates (in an upward direction) by contributing to social instability (Messner and
Tardiff 1985). While DeWees and Parker found support for gender inequality arguments
in that greater gender inequality in educational attainment contributes to significantly
lower female homicide victimization rates, their analyses did not demonstrate that the
ratio of unmarried women to unmarried men is associated with levels of female homicide
victimization. Thus, more women relative to men living outside the presumed protective
institution of marriage apparently does not translate into increased levels of female
homicide involvement.
In sum, research on family structure has provided some support for the claim that
family organization is important for determining women’s levels of killing and being
killed. In particular, levels of cohabitation and female divorce and separation rates appear
to play roles in influencing levels of female homicide offending. However, the
implications of these findings are not straightforward. Though levels of cohabitation are
associated with lower levels of female homicide (in support of Jensen’s hypothesis), the
divorce and separation rate exhibit a positive effect on female offending. This finding
would suggest that rather than capturing women’s liberation from men, divorce and
separation may be representing instability in family structure that contributes to higher,
rather than lower, rates of female homicide. This finding would be in line with the
arguments suggested by DeWees and Parker (2003) that higher rates of women outside of
41
marriage would be associated with more killings of females within cities. However, their
claim about marriage and homicide is not empirically supported.
Consequently, there remain some issues to be explored regarding the relationship
between family structure and female homicide. As Jensen (2001) did not examine killings
of females, it is unknown whether the variables she argues to be important for the gender
inequality homicide relationship are relevant to women’s homicide victimization. Nor has
it been established whether DeWees’ and Parker’s hypothesis might apply to killings by,
rather than of, females. As no studies to date have looked closely at family related
variables with regards to race, the impact of gender inequality on levels of female
homicide victimization for Black and White females remains unknown.
In light of the findings presented above, it is not necessarily clear what is to be
expected with regards to measures of familial inequality and women’s homicide
victimization and offending. Are inequalities related to family structure related to killings
by and of females, whereby greater amounts of non-traditional family arrangements are
associated with lower homicide rates? Or do higher levels of non-traditional family
arrangements indicate greater social instability, thereby increasing female homicide
involvement? The analyses that follow explore the questions above with regards to both
Black and White female victimization and offending in the 2000 time period.
42
Other Factors Associated with City Levels of Homicide
In addition to the factors of central concern here, several other variables are
included in this dissertation to account for other structural causes of homicide. Scholars
of female homicide point out that women’s absolute status, in addition to females’
relative inequality to males’, may also matter for city levels of killings by and of women.
The better of women are economically and socially, the more power women have to
protect themselves from violence, for example by exiting abusive relationships or
choosing to live in crime free areas (Steffensmeier 1980; Steffensmeier and Haynie
2002).Taking this into account, this study includes a control for females’ absolute
socioeconomic status.
Additionally, there exist several other factors that also contribute to levels of
homicide. The control variables region, age composition, residential mobility, and
divorce are designed to account for the structural characteristics associated with
socioeconomic inequality and previous findings that such inequality is related to higher
levels of homicides within cities (Krivo and Peterson 2000; Liska and Chamlin 1984;
Messner and Golden 1992; Ousey 1999; Parker and McCall 1997; Phillips 1997).
43
CHAPTER 3: DATA AND METHODS
To examine the relationship between gender inequality and women’s homicide
involvement, this analysis utilizes a cross-sectional sample of 199 U.S. cities for the 2000
period. Cities are used, rather than other government recognized areas such as states and
Standard Metropolitan Statistical Areas (SMSA’s), because cities are where homicides
are most concentrated. Evaluating cities reduces problems of aggregation bias, which
may occur when indicators of structural factors such as socioeconomic inequality are
measured beyond the limits of where the homicides actually take place (Bailey 1984,
Bailey and Peterson 1995; Smith and Brewer 1995). U.S. cities were selected into the
sample based upon the following criteria, that: (1) they have a population size that equals
or exceeds 100,000; (2) homicide victim and offender data were available for that city for
1999 through 2001; and (3) the Black population of the city is greater than 2,0001. Of the
238 cities with populations of 100,000 or more in 2000, sixteen were dropped due to
missing homicide data and another twenty-three were excluded because of a Black
population that was statistically too small to construct reliable measures of
socioeconomic gender inequality, familial, and control variables (N=199). (For the list of
1
Because Blacks comprise a smaller percentage of the population than Whites (12% and 75%, respectively
in 2000) (United States Bureau of the Census 2000), a minimum Black population ensures a sufficient
number to evaluate racial differences (Parker and McCall 1999).
44
large cities that are excluded because of missing homicide data or insufficient Black
population see Appendix A).
Data
Data for the dependent variables, female homicide victimization and offending,
are drawn from the Federal Bureau of Investigation’s (FBI) Supplementary Homicide
Reports (SHR), a database that collects monthly homicide information from city police
agencies. This dataset is provided yearly (since 1976) and includes information on the
race, sex, and age of homicide victims and known homicide offenders. However,
reporting is voluntary and not all police departments report data to the FBI for this
purpose. Sixteen cities that did not report homicide data to the SHR were dropped from
the analysis. Despite the lack of information for these sixteen cities, the Supplementary
Homicide Reports is the largest and most nationally representative data set containing
information on incidents of homicide by demographic characteristics of victims and
perpetrators for cities in the United States. It is the most widely used homicide database
in macro-level research on gender inequality and homicide (Gove, Hughes, and Geerken
1985; Steffensmeier 1993).
Data from the 2000 U.S. Census are drawn on to construct the independent and
control variables. Socioeconomic gender inequality and familial variables are drawn from
the United States Bureau of the Census, Summary Tape File 3 (STF3) and Summary
Tape File 4 (STF4). The United States Bureau of the Census Summary Form 3 provides
45
demographic information on income, occupation, education, employment, marital status,
cohabitation, and single father households. Tape 4 provides information for the above
variables further broken down by racial groups. The information for most of the control
variables are from STF3.
Measures
Dependent Variables
Detailed operationalizations of the dependent and independent variables can be
found in Appendix B. Female homicide victimization and offending rates are rounded
counts of the average number of female homicide victimizations and offenses per
100,000 women in each city for the years 1999, 2000, 2001. Three year averages are
used to minimize the impact of annual fluctuations for relatively rare events. Three
measures of female homicide victimization and offending are used in the study. Total
female homicide victimization is operationalized as the three year average count of female
homicide victims reported to the police in the 199 cities per 100,000 women.
Analogously, Black female homicide victimization and White female homicide
victimization are defined as the average count of Black and White female homicide
victims per 100,000 women, respectively. Total female homicide offending is
operationalized as the three year average count of female homicide offenders reported to
the police in the 199 cities per 100,000 women. Similarly, Black female homicide
offending and White female homicide offending are defined as the average count of Black
or White female homicide offenders per 100,000 women, respectively. For ease of
46
interpretation in Chapter 4, I present rates of total, Black, or White female victimization
and offending per 100,000, total, Black, or White females, respectively. Substantively, I
am interested in explaining rates of female homicide involvement and do so by
presenting negative binominal modeling (see discussion of analytic strategy below).
Independent Variables
Consistent with prior research, measures capturing socioeconomic gender
inequality are computed in four areas: median yearly income, employment, college
completion, and managerial, executive, and professional occupational status.
Socioeconomic gender inequality variables are computed for women as a total group,
Black women alone, and White women alone. Income inequality is operationalized as the
ratio of men’s to women’s median yearly earnings in 1999. Employment inequality is
measured as the ratio of the percentages of men to women sixteen years and older in the
civilian labor force who are employed. Educational inequality is the ratio of the
percentages of men to women twenty-five years and older with at least a four year
college degree. Occupational inequality is composed of the ratio of the percentages of
men to women sixteen years and older in the civilian population who are employed in
managerial, professional, and executive professions. Following some prior work (Whaley
and Messner; Veriatis et al. 2008) and because of high correlations among the factors
making up the four measures of socioeconomic gender inequality, male to female ratios
of socioeconomic gender inequality are combined into an index (average z-scores) called
socioeconomic gender inequality. However, to be sure that the pattern of findings holds
47
for the individual indicators, subsidiary analyses using the individual ratio components
were also conducted.
Four variables are included to account for aspects of familial structure that are
argued to be related to inequalities between women and men, and consequently levels of
female homicide. The variable ratio unmarried is operationalized as the ratio of the
percent of males to females that are divorced, separated, or unmarried in the 2000 period.
The female divorce and separation rate is the percentage of the total population of
females (or Black or White females) fifteen years of age and older who are divorced or
separated. Cohabitation is measured as the percent of cohabitating households in the city
out of the total number of partner (married and cohabitating) households. Finally, single
father households is operationalized as the percent of single male headed households with
children out of single and married parent households with children. The familial
inequality variables are computed and used as appropriate for females as a total group
and for Black females alone and White females alone.
High and Low Poverty Contexts
In order to examine the relationship between gender inequality and female
homicide victimization and offending with regards to poverty contexts (presented in the
second half of the proceeding empirical chapter), the 199 cities in the data are grouped
into either “high” or “low” poverty groups. This grouping is based upon the mean of the
percentage of individuals within a city with incomes at or below the poverty line in 1999.
Cities with the percentages of individuals living at or below the poverty line equal to or
48
above the mean (15.6 percent) are considered “high poverty city contexts” and cities
below the mean are considered as “low poverty city contexts”. Descriptive statistics for
the dependent and independent variables, as well as controls for the high and low poverty
city contexts can be found in Appendix C.
Control Variables
Consistent with previous research, women’s absolute status is measured along
four socioeconomic dimensions including: income, employment, education and
occupation. Women’s absolute income is measured as the median yearly income of
females in 1999. Women’s absolute employment is the percentage of females sixteen
years and older in the civilian labor force who are employed. Women’s absolute
educational status is measured as the percentage of females twenty-five years and older
who have completed a four year college degree or higher. Women’s absolute
occupational status is operationalized as the percentage of females sixteen years and
older in the civilian labor force who are employed in managerial, professional, and
executive occupations. All absolute status variables are computed for women as a total
group, Black women alone, and White women alone. Similar to gender inequality, in the
models that follow measures of women’s absolute status are combined into an index 2,3.
2
Indicators for women’s absolute status tend to be highly correlated (see Vieraitis, Kovandzic, and Britto
2008). Assessment of the correlation matrix indicated substantial correlation amongst the four measures
of socioeconomic absolute status used to construct the gender inequality variables. For example,
women’s employment in professional occupations and level of college completion were extremely
correlated (r=.96). A factor analysis was performed on the combination of the absolutes status variables
income, employment, educational, and occupational status. All four absolute status variables loading
scores were above .5, with an Eigen value of 2.8, which is over the conventional threshold of 1 (Kim and
49
The following control variables are designed to account for other structural
characteristics associated with socioeconomic inequality and its impact on overall levels
of homicide (Blau and Blau 1982). In particular, region, age composition, residential
mobility, and divorce are all arguably important for levels of homicide victimization and
offending (Krivo and Peterson 2000; Liska and Chamlin 1984; Messner and Golden
1992; Ousey 1999; Parker and McCall 1997; Phillips 1997). The region variable is
conceptualized as a dummy variable distinguishing southern from non-southern locations
(South = 1, non-South = 0) is. Young male population captures what is considered to be
the crime-prone population and is measured as the percentage of the population that is
male and between the ages of 15-34. Residential mobility is designed to capture the
stability of the residential population. This factor is measured as the percentage of the
city population that lived in a different residence in 1995 than in the year 2000. Percent
divorced is operationalized as the f the total adult population over fifteen years of age
who are divorced.
Mueller 1978). The result is the creation of the socioeconomic gender inequality and female absolute
status indices discussed in the previous section.
3
Further examination of the correlation matrix did not raise any concerns regarding the other variables in
the analysis. However, to ensure that collinearity was not problematic for other variables besides those
relating to women’s social and economic statuses, Variance Inflation Factor tests were performed on the
models for total, Black, and White females. As none of the VIF values exceeded the threshold of 10, it was
determined that none of the other variables included in the analysis posed a problem with
multicollinearity (Fox and Monette 1992). (For information regarding the bivariate relationships of all the
variables, see the correlation matrices for the samples with total, Black, and White women located in
Appendix D).
50
Analytic Strategy
This analysis proceeds in several stages. First, I present descriptive statistics for
all of the dependent and independent variables. Second, I provide a model that replicates
prior research regarding the relationship between gender inequality and female homicide.
In this model, I consider the influence of the index of four measures of socioeconomic
gender inequality-income, employment, education, and occupation- on female homicide
victimization and offending rates for total, Black, and White women. Next, to evaluate
the role of socioeconomic gender inequality within different poverty contexts, I model
the influence of social and economic gender inequality on Black and White women’s
homicide involvement, broken down by high or low city poverty contexts. The final
component of the analysis is the exploration of the effects of various measures of familial
inequality (including the ratio of unmarried men to women, rates of female divorce and
separation, and levels of cohabitating and single father households) on killings by and of
Black and White females.
This dissertation fits the above models using Poisson based regression techniques.
As female homicide victimization and offending are rare events, Ordinary Least Squares
regression is likely to result in biased results (Long 1997). Poisson modeling accounts for
the fact that incidences of homicide victimization and offending are rare events, and thus
have relatively low counts (Gardner, Mulvey, and Shaw 1995: Osgood 2002).
Consequently, this dissertation implements negative binomial regression in order to
analyze the relationship between gender inequality and female homicide victimization
51
and offending. The respective female population is included as an exposure variable in
the negative binomial regressions. Doing so allows the analysis to be one of rates, rather
than of counts, of female homicide victimization and offending. The negative binomial
coefficients can be interpreted in terms of percentage change in the rate of homicide per
unit change in the independent variable when transformed (using the formula [(eb 1)*100]).
In sum, this dissertation utilizes negative binomial regression to assess the
relationship between gender inequality and levels of total, Black and White female
homicide victimization and offending. Following prior research and due to collinearity
between variables capturing women’s social and economic absolute status, indices of
absolute female status and gender socioeconomic inequality are used in the analyses,
rather than evaluating these factors independently. This dissertation proceeds by
assessing the influence of socioeconomic gender inequality on Black and White female
homicide, then looking at this relationship with regards to poverty contexts, and finally
exploring the influence of various family related variables argued to be important to
gender inequality and involvement in violent behaviors by and toward females. The next
chapter presents the descriptive statistics of the variables introduced above, as well as the
multivariate analyses of socioeconomic gender inequality and female homicide
victimization and offending for females overall and by race and, finally, by poverty
context.
52
CHAPTER 4: DESCRPTIVE STATISTICS AND MULTIVARIATE RESULTS FOR
THE RELATIONSHIP BETWEEN SOCIOECNOMIC GENDER INEQUALITY AND
FEMALE HOMICIDE
Is socioeconomic gender inequality related to women’s levels of killing and being
killed? And how does race influence this relationship? In this chapter, I present the
results from the analyses of the relationship between socioeconomic gender inequality
and homicide involvement for Black and White females. However, before discussing the
multivariate findings, I describe the patterns of female homicide victimization and
offending, socioeconomic gender inequality, familial variables and other factors
associated with city-level rates of homicide.
I next present multivariate analyses assessing the role of socioeconomic gender
inequality on homicide victimization and offending for females overall and for Black and
White females, respectively. Doing so replicates prior research on gender inequality and
female homicide, and establishes whether socioeconomic gender inequality is important
for overall rates of female homicide for the 2000 period. Furthermore, it establishes
whether gender inequality similarly influences Black and White female killings in the
contemporary period in ways suggested by studies focused on the 1990’s. Finally, I
evaluate the relationship between homicide victimization and offending and
53
socioeconomic gender inequality with regards to low and high poverty city contexts for
Black and White females.
The Distribution of Female Homicide, Independent, and Control Variables
Female Homicide Victimization and Offending Rates
Table 1 displays the means and standard deviations (located in parentheses below
the means) for rates of female homicide victimization and offending, socioeconomic
gender inequality factors, familial variables, as well as the controls. Means and standard
deviations are displayed for total, White, and Black females. The ranges for the variables
are not presented in the table. However, some of these are referenced in the text. Looking
first at the descriptive statistics for females overall, mean rates4 of homicide victimization
are 9.81 per 100,000 females in the city population with a range of 0.00 to 53.52. The
average rate of homicide offending for females overall is 3.10 per 100,000 females,
ranging from 0.00 to 14.19 per 100,000 women and girls in the city. Clearly, instances of
female homicide victimization and offending are relatively uncommon and rates of
female homicide victimization are about three times that of female homicide offending.
These findings are consistent with the general literature on women and homicide
involvement (Belknap 2006; Gauthier and Bankston 1994)5.
4
Although the analysis utilizes counts of female homicide victimization and offending, rates are reported in
this section as they provide a more meaningful picture of female homicide involvement.
5
Females generally have lower rates of homicide victimization and offending when compared to males. For
victimization, females comprise around 24% of homicide victims while males comprise the other 76%.
Female offenders make up around 11% of homicide offenders, while males constitute the other 89%
(Belknap 2006).
54
Turning to the racial breakdowns, as expected Table 1 indicates that Black
females have higher rates of homicide victimization and offending when compared to
White females. First, the mean for the White female homicide victimization rate is 7.58
and ranges from 0.00 to 47.41 homicide victimizations per 100,000 White females. The
White female average homicide offending rate is 1.54 per 100,000 White females, with a
range of 0.00 to 9.41 homicide offenses per 100,000 White females. Black female rates of
homicide victimization are substantially higher than those of White females, with an
average of about 19.14 victimizations per 100,000 Black females. The range is from 0.00
to 101.35 killings per 100,000 Black females. In terms of offending, the mean for Black
females is 8.54, with a range of 0.00 to 114.42 homicide offenses per 100,000 Black
females. Similar to rates for overall females’ homicide involvement, rates of homicide
victimization are higher than offending for both Black and White females. At the same
time, the figures indicate that Black females in large U.S. cities are at a much greater risk
of killing or being killed than their White counterparts.
Table 1: Means and Standard Deviations for Female Homicide Victimization and
Offending, Socioeconomic Gender Inequality, Familial Aspects, and Control Variables
Dependent Variables
Female Homicide Victimization Rate
Female Homicide Offending Rate
Independent Variables
55
Total
White
Black
9.81
(7.96)
3.10
(3.00)
7.58
(7.17)
1.54
(1.96)
19.14
(18.92)
8.54
(15.63)
Socioeconomic Gender Inequality Index
.00
(.67)
1.42
(.16)
1.00
(.01)
1.14)
(.10)
.86
(.11)
1.07
(.05)
15.45
(2.12)
12.09
(3.91)
7.03
(1.35)
Income Inequality
Employment Inequality
Educational Inequality
Occupational Inequality
Ratio Unmarried
Female Divorce and Separation Rate
Cohabitation
Single Father Household
Control Variables
Female Absolute Status Index
.00
(.83)
19,438.13
(3,871.67)
92.76
(2.75)
Median Yearly Income
Percent Employed
.00
(.62)
1.31
(.11)
1.00
(.01)
1.19
(.10)
.89
(.10)
1.11
(.06)
15.08
(2.08)
13.53
(4.83)
6.64
(1.63)
.00
(.83)
29,875.73
(5,402.21)
94.42
(2.36)
.00
(.51)
1.19
(.12)
.98
(.03)
.98
(.23)
.72
(.15)
.95
(.07)
20.29
(2.52)
18.94
(6.07)
8.56
(2.68)
.00
(.86)
26,478.86
(5,298.00)
89.46
(3.68)
Table Continues
Table 1, Continued
Total
Control Variables, continued
Percent with College Degree
23.85
(10.00)
35.71
(7.18)
52.46
(6.01)
15.87
(2.34)
.32
(.47)
Percent in Professional Occupations
Residential Mobility
Percent Males 15-34
South =1
56
White
Black
27.31
(12.61)
39.82
(8.75)
52.46
(6.01)
15.31
(2.70)
.32
(.47)
16.88
(7.54)
30.91
(7.53)
52.46
(6.01)
15.38
(2.80)
.32
(.47)
Percent Divorced
10.88
(2.01)
11.48
(2.00)
12.89
(2.49)
N=199
Note: Standard deviations are below means in parentheses for all variables
Socioeconomic Gender Inequality
As explained in Chapter 3 (Data and Methods), the four socioeconomic gender
inequality variables that have been consistently used in research on females and homicide
(ratios6 of men to women’s status in: income, employment, educational, and occupational
status) are combined into an index. The descriptive statistics for the socioeconomic
gender inequality indices computed for total, Black, and White women are presented in
Table 1. To gain a more concrete sense of the distribution of the socioeconomic gender
inequality variables, Table 1 also displays the means and standard deviations for the four
variables used to construct the socioeconomic gender inequality index.
Beginning with women overall, the socioeconomic gender inequality index has a
mean of approximately 0.00, which is common for indices. The index for total female
socioeconomic gender inequality ranges from -2.44 to 1.65 (ranges are not shown in the
table). The variable income inequality signifies that, on average, men’s median yearly
earnings were about 42 percent higher than that of women for the 2000 period. For
example, in the 2000 time period, men overall made an average of around $27,507
compared to a mean of about $19,438 for women, a difference of about of $8,067 (or
6
Ratios are computed by first determining women and men’s: median yearly income, percent employed,
percent with a college degree or higher, and percent in professional occupations. Percentages for men are
then divided by percentages for women to produce a ratio of male to female values for SES inequality
along four dimensions.
57
around 42 percent of women’s income). Men and women were equally likely to be
employed in 2000, with a mean ratio of 1.00. Table 1 also reveals that, on average, men
were about 14 percent more likely to have obtained a college or graduate degree than
women. At the same time, in terms of type of occupation, the mean ratio of .86 indicates
that women were about 14% more likely to be employed in professional occupations than
their male counterparts7,8. For the most part, within this data set men are typically better
off socially and economically when compared to women, although their levels of
employment is about equal. Employment in professional occupations appears to be the
only area in which women’s status exceeds men’s.
Descriptive statistics for socioeconomic gender inequality broken down by race
demonstrate that patterns of socioeconomic gender inequality for White men and women
generally parallel the findings for overall gender inequality. Beginning with the
socioeconomic gender inequality index variable, Table 1 displays a mean of 0.00, with a
range of -2.12 to 2.18. In 2000, White men’s earnings were, on average, around 31
percent higher than White women’s earnings. White women and men appear to be about
equal in their employment status, with a mean ratio of 1.00. The mean ratio of 1.19
illustrates that White men were, on average, about 19 percent more likely to have earned
a bachelor or graduate degree when compared to White women for the year 2000. In
terms of occupational status type, on average White women were 11 percent more likely
7
Although women are more likely to be employed in executive and managerial professions than men,
women have greater representation in typically lower paid professional service industries such as teaching
and health care (United States Bureau of the Census 2000).
8
Because occupational status was the one variable in which women appeared to exceed men, models were
run without occupational status included. Similar results were obtained with and without the inclusion of
occupational status.
58
to be employed in executive, professional, and managerial occupations than White men
for the same time period. Similar to women overall, employment in professional
occupations is the one socioeconomic dimension in which White women appear to be
better off relative to White men.
The socioeconomic gender inequality index for Black men and women has a
mean of zero and ranges from -1.43 to 1.57. As with Whites, the earnings ratio favors
Black men over Black women. In particular, Black men’s earnings were about 19 percent
higher than Black women’s earnings in 2000. However, for employment and education,
Black men and women are more on an even par, with a slight difference favoring Black
women. Black women, on average, were slightly (about 2 percent) more likely to be
employed and to hold a bachelor or graduate degree in 2000. On average, the ratio (.72)
for professional occupational status favors Black women over Black men to an even
greater degree than is true for the ratio for Whites. Black women were 28 percent more
likely to be employed in executive, professional, and managerial occupations when
compared to Black men. In general, Black women relative to Black men appear to have
been slightly better off than White women relative to White men in the 2000 period.
Black women achieved near equality in both education and income, and exceeded men in
employment in professional occupations by a somewhat greater margin than White
women exceeded White men. Similar to White women and men, Black men earned more
money than Black women in the 2000 period.
59
Familial Variables
A goal of this dissertation is to move beyond the consideration of traditional
socioeconomic gender inequality in assessing how various factors related to gender affect
levels of female homicide victimization and offending. In line with this goal, the analyses
also include four measures of familial factors, which have been suggested to potentially
affect female homicide victimization and offending (DeWees and Parker 2003; Jensen
2001). The descriptive statistics for these variables are also located in Table 1. Beginning
with overall family variables, the average of the variable “Ratio Unmarried” indicates
that men were about 7 percent more likely to be never married, divorced, or separated
than women in the year 2000. The mean for the variable capturing females’ divorce and
separation signifies that around 15 percent of women over the age of 15 were divorced or
separated in 2000. On average, around 12 percent of coupled households in large U.S.
cities were comprised of unmarried heterosexual and homosexual couples for that same
time period. According to the mean for single father households, around 7 percent of all
households with children were headed by single fathers in 2000.
Statistics on marriage are similar for Whites. On average, White men were about
11 percent more likely to be unmarried in 2000 than White women and nearly 15 percent
of White women over the age of 15 were divorced or separated in 2000. Around 14
percent of White households in large U.S. cities involved cohabitating couples in 2000
according to the mean for the variable “Cohabitation” and, on average, nearly 7 percent
of households with children were single father households. Contrary to the patterns for
Whites, the descriptive statistics indicate that Black women were less likely to be
60
unmarried in 2000 than Black men by an average of around 5 percent. The mean for
Black females’ divorce and separation illustrates that Black women were more likely to
be divorced or separated than overall or White females, with a little over 20 percent of
Black women divorced or separated in the 2000 time period. Percent households
cohabiting was slightly more for Blacks than that of women overall and White women.
On average, 19 percent of Black households were composed of unmarried heterosexual
and homosexual couples in 2000. The mean of single father households for the Black
population indicates that Black single fathers accounted for around 9 percent of
households with children, slightly more than the average for Whites.
In brief, White women more closely match the statistics for women overall than
Black women. In particular, White women are less likely to be unmarried relative to
White men, while the opposite appears to be true for Black women. In terms of
cohabiting and single father households, Blacks, when compared to Whites, have
somewhat higher percentages of both types of these family arrangements. Finally,
divorce and separation rates are higher amongst Black women than White females. Thus,
these descriptive statistics indicate that in general Black women are more likely to be
engaged in “non-traditional” family structures, such as cohabitation, while White females
appear to be somewhat less likely to partake in non-traditional family arrangements.
Control Variables
The analyses presented next include controls for city level variables associated
with levels of homicide and other serious crime. First, it is important to control for
61
females’ absolute socioeconomic status, which also has been theoretically suggested and
empirically demonstrated to be an important contributor to female homicide (e.g. Adler
and Adler 1975; Box and Hale 1984; Steffensmeier and Haynie 2002; Steffensmeier
1980; Veriatis 2008). Women’s absolute status is an index that combines four dimensions
of socioeconomic status: women’s median yearly income, the percentage of women that
are employed, the percentage of women who have college degrees, and the percentage of
women who have professional jobs. To avoid issues of multicollinearity the components
of women’s absolute status are combined into an index (see Chapter 3: Data and
Methods). As is common with indices, women’s absolute status index has a mean of 0.00
and a standard deviation of just over .8 for all the groups under consideration: the total
female population, White females, and Black females.
Descriptive statistics for each of the variables used to construct the female
absolute status index are located in Table 1. The average yearly median income in 2000
for women overall was $19,438.13. Around 93 percent of women sixteen years and older
in the civilian labor force were employed and nearly 24 percent had obtained a college
degree or higher for that same time period. The mean of women in professional
occupations was around 36 percent in 2000. White women had higher median yearly
incomes than women overall in 2000, with an average of $29, 875.73. White women
were similar to women overall with regards to the other absolute status variables. On
average, 94 percent of White women were employed, 27 percent had a college degree or
higher, and nearly 40 percent were employed professional jobs for the same time period.
In 2000, the average median income for Black females was $26,478.86. As expected, the
62
other absolute status variables for Black women were somewhat lower than for overall or
White females. Around 89 percent of Black women were employed, an average of about
17 percent had college degrees or higher, and around 31 percent of Black women had
professional occupations in the 2000 time period.
In addition to women’s absolute status, prior research provides evidence that
higher levels of residential mobility, young male population, divorce, and being located
in the South are also factors associated with city rates of homicide (e.g. Krivo and
Peterson 2000; Ousey 1999; Parker and McCall 1997; Sampson and Wilson 1995). Table
1 displays that there is a fair amount of residential mobility within the cities being
investigated; on average, 52 percent of people lived in a different house in 1995 than in
the year 2000. In 2000, on average, young men between the ages of 15-34 comprised
around 16 percent of the city population. Of the 199 cities included in the analyses, 32
percent of them were located in the South. Finally, the variable divorce indicates that, on
average, almost 11 percent of individuals over the age of 15 were divorced in 2000.
The proportion of cities in the southern region and the residential mobility of an
area are not treated as varying across the groups of interest in this study. However,
percent young males and the divorce rate are also computed for Blacks and Whites
separately. On average, around 15 percent of the White population was male and between
the ages of 15-34 in the 2000 time period. The respective for young Black males was also
approximately 15 percent. For Whites, on average around 11 percent of the population
over the age of 15 was divorced in 2000 in the cities examined here. This compares to an
average of nearly 13 percent of the adult Black population. In sum, residential mobility
63
and percent young males appear to be fairly similar for the overall population of the cities
under consideration, as well as for Blacks and Whites.
Socioeconomic Gender Inequality and Female Homicide Victimization and Offending
To determine if the relationships reported for female homicide involvement in
earlier research holds for the 2000 period, I analyze the relationship between
socioeconomic gender inequality and total, Black, and White rates of female homicide
victimization and offending. The negative binomial results for the influence of
socioeconomic gender inequality on female homicide are presented in Tables 2
(victimization) and 3 (offending).
Socioeconomic Gender Inequality and Female Homicide Victimization
Results for the relationship between socioeconomic gender inequality and female
homicide victimization are displayed in Table 2. The values are negative binomial
coefficients with the standard errors for the coefficients in parentheses9. What is the
relationship between socioeconomic gender inequality and rates of female homicide
victimization? Beginning with the findings for the total female population,
socioeconomic gender inequality is both significantly and negatively related to rates of
female homicide victimization. In particular, a unit increase in socioeconomic gender
inequality translates into a 30.93 percent decrease in female homicide victimization
9
Negative binomial coefficients are easily interpretable as percentage changes in homicide per unit change
in the independent variables when transformed as follows: [(eb)-1)]*100.
64
([(e.37)-1)]*100). This finding supports the backlash hypothesis that gains in
socioeconomic equality by women results in higher levels of female homicide
victimization.
Besides socioeconomic gender inequality, several other variables appear to be
associated with total levels of female homicide victimization. First, women’s absolute
status is negatively and significantly associated with female homicide victimization. In
particular, a one unit increase in women’s absolute status is associated with a 28.82
percent reduction in female homicide victimization. This finding is consistent with prior
research showing that higher levels of absolute status reduce women’s risk of homicide
victimization. Cities located in the South appear to have higher rates of homicide, with
around 28 percent more killings of females being significantly associated with living in
southern rather than non-southern cities. The percent divorced is also positively and
significantly associated with overall levels of female homicide victimization.
Specifically, each percentage increase in divorce is associated with a 9.42 percent
increase in female homicide victimization.
In general, higher levels of socioeconomic gender inequality are associated with
lower levels of homicide victimization for women overall. Is this true for both Black and
White women? The results for these groups are displayed in the final two columns of
Table 2. When considering White women, socioeconomic gender inequality is indeed
significantly related to levels of female homicide victimization. Specifically, a unit
increase in gender inequality is associated with a 24.42 percent reduction in White female
homicide victimization. Consistent with the findings for women overall, the results for
65
White women appear to be in support of the backlash hypothesis that greater gains in
socioeconomic status made by women relative to men are associated with higher levels of
homicide victimization.
Table 2: Multivariate Results for Female Homicide Victimization, Socioeconomic
Gender Inequality, and Control Variables by Race
Total Female
Victimization
Independent Variables
Socioeconomic Gender
Inequality Index
Control Variables
Women’s Absolute
Status Index
Residential Mobility
Total Percent 15-34
Region South = 1
Divorce
Constant
White Female Black Female
Victimization Victimization
-0.37*
(0.08)
-.28*
(.11)
-.15
(.15)
-.34*
(.06)
-.02
(.01)
.05*
(.03)
.25*
(.09)
.09*
(.03)
-10.43
(.55)
-.28*
(.07)
-.03*
(.01)
.08*
(.03)
.15
(.12)
.11*
(.03)
-10.67*
(.58)
-.33*
(.09)
0.00
(.01)
-.06
(.03)
-.19
(.11)
.03
(.03)
-8.24*
(.67)
N=199
*p<.05, two-tailed test
Regarding the control variables, several of them have the same type of
relationship with killings of White females as was found for total homicide victimization.
Specifically, White women’s absolute status is significantly associated with White female
homicide victimization. In particular, a one unit increase in women’s absolute status is
associated with a 24.42 percent reduction in White female homicide victimization. Also,
66
the percent of White males aged 15-34 and the divorce rate are both significantly and
positively related to female homicide victimization. Residential mobility is significantly
and negatively related to levels of White female homicide victimization, although this
was not found for women overall and is in the opposite direction as would be expected.
Also, in contrast to the previous finding for total women, southern region did not reach a
level of significance for White female victimization.
Above it was shown that socioeconomic gender inequality is associated with
killings of White females. But, is this also the case for levels of Black female homicide
victimization? The evidence presented in Table 2 suggests that the answer to this
question is in the negative. As displayed in Table 2, Black socioeconomic gender
inequality is not significantly related to killings of Black females. Moreover, only one of
the variables in the model has a significant influence on levels of Black female homicide
victimization. That is, similar to findings for total and White women’s homicide, Black
women’s absolute status is significantly and negatively related to levels of Black female
homicide victimization. In particular, for a unit increase in Black women’s absolute
status, Black female homicide victimization is reduced by 28.11 percent. Unlike findings
for total and White women, none of the other control variables are significantly related to
Black female homicide victimization for the 2000 period.
In brief, the findings from the above multivariate analyses reveal that
socioeconomic gender inequality is a significant factor for White, but not Black, city
levels of female homicide victimization. This is consistent with the findings of the single
other study examining homicide victimization for these two groups separately (Veiriatis
67
and Williams 2002). Specifically, higher levels of socioeconomic gender inequality are
associated with lower levels of White female homicide victimization, but apparently are
unrelated to killings of Black females. For White women, the association between higher
levels of gender inequality and lower levels of female homicide victimization support the
backlash hypothesis. Interestingly, this finding is not demonstrated for Black females.
Instead, absolute status emerges as the most important gender related variable driving
levels of Black female homicide victimization.
Socioeconomic Gender Inequality and Female Homicide Offending
Feminist theory posits that socioeconomic gender inequality drives female
homicide offending in similar ways as victimization. In particular, it is argued that
killings by females are a reaction to male violence in a patriarchal society. The results for
whether or not homicide offending is driven by socioeconomic gender inequality are
found in Table 3. First, looking at the results for women overall, socioeconomic gender
inequality is negatively and significantly related to female homicide offending. In
particular, a one unit increase in gender inequality is associated with a 28.40 percent
lower level of overall female homicide offending.
Consistent with the previous findings on victimization, women’s absolute status is
significant and negatively related to overall levels of female homicide offending. Thus,
higher levels of absolute status for women seem to lessen their homicide involvement.
Turning to the other control variables, most are related to female homicide offending in a
manner consistent with prior findings and arguments about the structural causes of
68
violent crime. In general, levels of killings by females are greater in cities where there are
a higher proportion of young males, higher divorce rates, and in cities located in the
South. The unexpected finding is that residential mobility is associated with fewer, rather
than more, female homicide offenses.
When looking at the influence of socioeconomic gender inequality on offending
for White and Black women separately, however, it appears that socioeconomic gender
inequality is not a structural contributor to levels of killings by women. As shown in
Table 3, socioeconomic gender inequality is not significant for levels of homicide
offending for White females. White women’s absolute status approaches significance in
the negative direction, although not at the .05 level. Percent White males 15-34 and
divorce are positively and significantly associated with levels of White female’s
homicide offending.
69
Table 3: Multivariate Results for Female Homicide Offending, Socioeconomic Gender
Inequality, and Control Variables by Race
Total Female
Offending
Independent Variables
Socioeconomic Gender
Inequality Index
Control Variables
Women’s Absolute
Status Index
Residential Mobility
Total Percent 15-34
Region South = 1
Divorce
Constant
White Female
Offending
Black Female
Offending
-.25*
(.10)
.01
(.16)
-.01
(.20)
-.33*
-.19
-.48*
(.11)
-.02
(.01)
.09*
(.04)
-.30*
(.16)
.16*
.04
-13.53*
(.77)
(.13)
0.00
(.01)
0.00
(.04)
-.04
(.14)
.02
(.04)
-9.57*
(.91)
(.09)
-.03*
(.01)
.08*
(.04)
.36*
(.13)
.12*
(.04)
-11.60*
(.74)
N=199
*p<.05, two-tailed test
Turning to killings by Black females, again we see that socioeconomic gender
inequality is not significantly associated with levels of female homicide offending.
Furthermore, only one control variable is significant for Black women’s homicide
offending. In particular, each percent increase in Black women’s absolute status is
associated with a 38.12 percent reduction in levels of female homicide offending. This
finding differs from the results presented above for White women where absolute status
is not significantly related to levels of White female homicide offending.
70
By and large, the results from the multivariate analyses suggest that
socioeconomic gender inequality is less effective in predicting female homicide
offending than victimization. Although socioeconomic gender inequality is significant
and negatively related to overall levels of female homicide offending, it is unrelated to
killings when race is taken into account. Findings for the control variables indicate that
absolute status is an important factor for Black female offenses (greater absolute status
reduces killings by Black females) however, this factor does not contribute to levels of
homicide offending for White women. A greater number of the additional control
variables are related to White female homicide offending when compared to Black
female homicide offending, including the percentage of young males and divorce, neither
of which is related to homicides by Black females.
Poverty Contexts, Race, and the Relationship Between Socioeconomic Gender Inequality
and Female Homicide Victimization and Offending
Female Homicide Victimization and Offending In Low Poverty City Contexts
The next goal of this dissertation is to assess long held feminist assumptions that
socioeconomic gender inequality exerts a stronger effect in high, versus low, poverty
contexts. According to some feminist scholars (e.g. Messerschmidt 1993), greater
amounts of poverty contribute to higher levels of frustration and aggression amongst
men. Within a patriarchal society, male frustrations in the form of violent behavior are
believed to be channeled toward women. In places of high poverty, socioeconomic
gender inequality is argued to make women more vulnerable to inequalities relative to
men, for example as they have fewer economic resources to escape situations of male
71
violence. The following series of multivariate analyses sheds light on this question,
asking: Is it the case that socioeconomic gender inequality is more important for high,
versus low, poverty contexts? Accordingly, results for the multivariate analyses of the
relationship between socioeconomic gender inequality and levels of female homicide
victimization and offending with regards to both low and high poverty city contexts10 are
now presented11. They are found in Table 4 (low poverty contexts) and Table 5 (high
poverty contexts)12.
First, the results for White female homicide victimization (Table 4) indicate that
socioeconomic gender inequality is significant and negatively related to levels of killings
of White females in low poverty city contexts. In particular, a one unit increase in
socioeconomic gender inequality is associated with around a 27 percent decrease in
White female victimization. This mirrors the previous findings of the relationship
between socioeconomic gender inequality and White female homicide victimization
when poverty contexts are not taken into account. Furthermore, as Table 4 indicates,
divorce is also significantly associated with higher levels of female homicide
victimization.
Socioeconomic gender inequality, however, seems to have little to do with
homicide victimizations of Black females in low poverty city contexts. As shown in
10
High and low poverty city contexts are based upon the mean value for the percentage of individuals
living below the poverty line in the population (15.62 percent). Cities with a percentage of individuals
living below the poverty line of 15.62 or higher are considered high poverty, while cities with less than
15.62 are considered low poverty.
11
Descriptive statistics for the dependent and independent variables and controls broken down by high
and low poverty city contexts are located in Appendix (D).
12
Because the above analyses indicate that patterns of the relationship between socioeconomic gender
inequality are not similar for Black and White killings, the remainder of the analyses focuses on these two
groups and not on female killings as a whole.
72
Table 4, although levels of Black females’ absolute status are significantly and negatively
related to levels of Black female homicide victimization, socioeconomic gender
inequality is not significantly related to killings of Black females. The results also
indicate that percent young males is significant for Black female homicide victimization
in low poverty city contexts, although the negative relationship is contrary to
expectations regarding the influence of young males on city levels of crime.
In reference to levels of killings by women, socioeconomic gender inequality
contributes little to understanding female homicide offending for White or Black women
in low poverty contexts. As indicated in Table 4, socioeconomic gender inequality is not
a contributor to levels of White or Black female homicide offending in cities that have
relatively low levels of poverty. Rather, divorce is the only significant variable for levels
of White female offending in low poverty contexts, showing a positive association with
levels of female homicide offending. Once again, Black women’s absolute status is
significant, with their higher levels of absolute status being associated with lower levels
of Black female homicide offending.
73
Table 4: Multivariate Results for White and Black Female Homicide Victimization and Offending, Socioeconomic Gender
Inequality, and Control Variables in Low Poverty City Contexts
Victimization
74
Independent Variables
Socioeconomic Gender
Inequality Index
Control Variables
Women’s Absolute Status
Index
Residential Mobility
Total Percent 15-34
Region South = 1
Divorce
Constant
N=100
*p<.05, two-tailed test
Offending
White
Black
White
Black
-.32*
(.15)
-.18
(.26)
.05
(.22)
-.17
(.39)
-.16
(.11)
.01
(.01)
.03
(.04)
.20
(.16)
.15*
(.05)
-12.91*
(.92)
-.37*
(.15)
.04
(.02)
-.11*
(.05)
-.31*
(.20)
-.01
(.05)
-9.13*
(1.16)
.11
(.17)
-.00
(.02)
.10
(.06)
-.11
(.24)
.31*
(.08)
-16.28*
(1.48)
-.80*
(.24)
-0.01
(.02)
.02
(.07)
-.73*
(.30)
-.13
(.07)
-7.64*
(1.63)
In short, the findings for the relationship between socioeconomic gender
inequality and homicide victimization in low poverty city contexts generally parallel the
findings reported for cities overall (located in Tables 2 and 3). In particular, although
socioeconomic gender inequality is associated with White female homicide victimization
in cities characterized by lower amounts of poverty, it is not related to killings of Black
females in low poverty city contexts. Instead, Black females’ greater absolute status is
associated with lower city levels of Black female homicide victimization. Finally,
socioeconomic gender inequality is unrelated to White or Black females’ homicide
offending in low poverty city contexts.
Female Homicide Victimization and Offending in High Poverty City Contexts
I now turn to the multivariate results regarding female homicide victimization and
offending in high poverty city contexts for Whites and Blacks. As displayed in Table 5,
socioeconomic gender inequality is not significantly associated with victimization or
offending for either group. Rather, the control variables absolute status (in the negative
direction), residential mobility, percent young male and divorce are associated with
killings of White women. Absolute status is the only variable that is significant (also in
the negative direction) for Black female homicide victimizations in high poverty city
contexts.
With regards to offending, absolute status is significantly and positively
associated with killings by White females. In particular, a one unit increase in White
female absolute status is related to a 28.11 percent reduction in city levels of White
75
female homicide offenses. However, none of the other variables achieve statistical
significance for killings by White females. Furthermore, the divorce rate, which achieved
significance for White females in the previous analyses for all cities and low poverty city
contexts, does not achieve statistical significance for levels of White female homicide
offending in high poverty city contexts. The model for Black females contributes little to
the explanation of the structural causes of killings by Black females within cities. In
particular, none of the variables are significantly associated with levels of Black female
homicide offending. Furthermore, Black female’s absolute status, which is significant in
all prior analyses, seems to not be driving killings by Black females within high city
poverty contexts.
Generally speaking, although socioeconomic gender inequality contributes little
to the understanding of Black female homicide victimization in low or high city poverty
contexts, the levels of poverty within cities seem to matter for White women. However,
the way in which it matters runs somewhat contrary to earlier feminist predictions.
Instead of observing a stronger relationship between socioeconomic gender inequality
and female homicide in high poverty contexts, the multivariate analyses demonstrate that
socioeconomic gender inequality may actually matter more in low poverty contexts.
76
Table 5: Multivariate Results for Female Homicide Victimization and Offending, Socioeconomic Gender Inequality, and Control
Variables in High Poverty City Contexts
Victimization
White
Independent Variables
Socioeconomic Gender
Inequality Index
Control Variables
Women’s Absolute Status
Index
77
Residential Mobility
Total Percent 15-34
Region South = 1
Divorce
Constant
N=99
*p<.05, two-tailed test
Offending
Black
White
Black
-.05
-.05
.09
-.01
(.15)
(.17)
(.21)
(.23)
-.22*
-.23*
-.33*
-.26
(.09)
-.06*
(.02)
.12*
(.04)
.00
(.16)
.11*
(.04)
-9.28*
(.77)
(.11)
-.02
(.01)
-.01
(.05)
-.14
(.14)
.05
(.03)
-7.86
(.90)
(.12)
-.02
(.02)
.08
(.06)
-.40
(.21)
.10
(.05)
-12.06*
(.81)
(.14)
.00
(.02)
-.02
(.06)
.14
(.18)
.04
(.05)
-9.63*
(1.19)
CHAPTER 5: AN EXPLORATORY ANALYSIS OF FAMILIAL INEQUALITY AND
FEMALE HOMICIDE VICTIMIZATION AND OFFENDING
This chapter presents the results from the multivariate analyses of the impact of
“familial inequality” variables (i.e., the divorce and separation rate, and levels of
cohabiting and single father households) on levels of female homicide victimization and
offending. I regard this examination of the impact of a variety of familial factors on
female homicide as exploratory for two reasons. First, few studies have examined their
impact, thus we know little about the link between family related structures, inequality or
otherwise, and female crime. Second, familial variables have been argued by scholars to
matter for female homicide involvement, but in contradictory ways (DeWees and Parker
2003; Dunn, Almquist, and Saltzman 1996; Jensen 2001). On the one hand, lower levels
of traditional family structures (i.e., marriage) and greater amounts of alternative
relationship arrangements (i.e., single father households or cohabitation) may indicate
women’s greater freedom and potential to live outside of relationships with men. This,
some feminist scholars assert, is indicative of women’s greater equality at large. As a
result of greater equality between women and men, less violence is channeled toward
women, consequently lowering their risk of being killed or killing in self-defense (Jensen
2001).
78
On the other hand, other scholars argue that traditional male-female relationships,
namely marriage, may protect women from homicide involvement by encouraging
domesticity and thus decreasing their exposure to opportunities of encountering violent
situations (DeWees and Parker 2003; Messner and Tardiff 1993). Furthermore, as
married women typically have greater economic resources when compared to single
females, it is also possible that women in marital relationships are more able to escape
violence perpetrated toward them when compared to single females (see Gartner et al.
1990). Unrelated to gender arguments, higher amounts of marriage have also been argued
to accompany social stability which has been found to be associated with lower levels of
violent crime, such as homicide (see Bailey and Peterson 1995). Few studies, however,
have considered the potential impact of family related variables, other than divorce, on
levels of female homicide victimization and offending. Furthermore, none has yet to
assess the influence of familial variables on levels of female homicide across racial
groups.
This chapter attempts to address the lack of research on familial inequality and
female homicide by exploring the effects of different family related variables that have
been proposed as important for female homicide involvement. Below, I first present the
multivariate analyses for familial inequality variables and White and Black women’s
homicide victimization and then offending. Each set of analyses contains four models,
one with each of the familial inequality variables, along with the socioeconomic gender
79
inequality and control variables (excluding the total divorce rate13), for levels of female
homicide victimization and offending for White (Tables 6 and 8) and Black (Tables 7 and
9) females.
Multivariate Results for the Relationship Between Familial Variables and Female
Homicide Victimization
Familial Variables and White Female Homicide Victimization
Results for the exploratory multivariate analyses of the relationship between
familial inequality variables and levels of White female homicide victimization are
displayed in Table 6. Each of the models (1-4) in the table represents the results from the
regression of female homicide victimization on one of the familial variables , in addition
to socioeconomic gender inequality, and control variables. As Table 6 illustrates,
socioeconomic gender inequality is significant for killings of White females. In
particular, results from all four of the models demonstrate that higher levels of
socioeconomic gender inequality are associated with lower rates of White female
homicide victimization. This demonstrates that including familial inequality variables in
the models does not alter the association between socioeconomic gender inequality and
levels of White female homicide victimization.
The coefficients14 from the models in Table 6 indicate that each of the familial
variables is significantly associated with killings of White females, net of socioeconomic
13
In one of the models, divorce and separation are treated as a familial inequality variable, consistent with
arguments made by Jensen (2001).
80
gender inequality. The ratio of unmarried men to unmarried women is positively
associated with levels of White female homicide victimization. Women’s divorce and
separation rates are also related to White female homicide victimization; a one unit
increase in such levels leads to around a 6 percent increase in killings of White females.
The results also indicate that non-traditional family arrangements are also positively
associated with levels of female homicide victimization. For example, the greater the
percent of White households composed of unmarried heterosexual and homosexual
couples (cohabiting) the higher the level of White female homicide victimization.
Additionally, higher levels of White single father households are related to higher levels
of killings of White females. These positive coefficients suggest that levels of nontraditional family arrangements do not lower levels of female homicide victimization for
White women. Rather, the opposite appears to be true, that higher levels of such family
arrangements positively influence killings of White females.
The inclusion of different familial inequality variables does affect the
relationship between many of the control variables and White female homicide
victimization. Notably, when the ratio of unmarried males to females is considered, none
of the remaining control variables is significant. However, when percent divorce and
separation or single father households is examined, residential mobility, percent young
males, and location in the Southern region (Model 4) are significant for levels of White
female homicide victimization.
14
Negative binomial coefficients are easily interpretable as percentage changes in homicide per unit change
in the independent variables when transformed as follows: [(eb)-1)]*100.
81
Table 6: Multivariate Results for White Female Homicide Victimization, Socioeconomic
Gender Inequality, and the Independent Effects of the Familial Variables
Model 1
Independent Variables
Ratio Unmarried
Model 2
Model 3
Model 4
4.61*
(.95)
Female Divorce/Separation
.06*
(.02)
Cohabitation
.05*
(.01)
Single Father Households
SES Gender Inequality Index
Control Variables
Women’s Absolute Status
Index
Residential Mobility
Percent Male 15-34
South
Constant
-.27*
(.10)
-.34*
(.11)
-.23*
(.12)
.17*
(.05)
-.25*
(.11)
-.22*
(.07)
.00
(.01)
.01
(.02)
.06
(.11)
-14.97*
(1.22)
-.26*
(.08)
-.02*
(.01)
.06*
(.03)
.18
(.12)
-10.49*
(.64)
-.37*
(.08)
-.01
(.01)
.01
(.02)
.34
(.12)
-10.10*
(.52)
-.16*
(.08)
-.02*
(.01)
.06*
(.02)
.37*
(.12)
-10.64*
(.57)
N=199
*p<.05, two-tailed test
Familial Variables and Black Female Homicide Victimization
Results for the impact of familial variables on Black women’s homicide
victimization are displayed in Table 7. As in the earlier model examining socioeconomic
gender inequality and Black female homicide victimization (Table 3), socioeconomic
gender inequality is not a significant predictor of Black female homicide victimization for
large places for the 2000 time period.
82
Table 7: Multivariate Results for Black Female Homicide Victimization, Socioeconomic
Gender Inequality, and the Independent Effects of the Familial Variables
Model 1
Independent Variables
Ratio Unmarried
Model 2
Model 3
1.06
(1.16)
Female Divorce/Separation
.02
(.03)
Cohabitation
.01
(.01)
Single Father Households
SES Gender Inequality Index
Control Variables
Women’s Absolute Status
Index
Residential Mobility
Percent Male 15-34
South
Constant
Model 4
-.11
(.15)
-.15
(.15)
-.10
(.15)
.03
(.04)
-.15
(.14)
-.31*
(.10)
.01
(.01)
.07*
(.03)
-.20
(.11)
-8.98*
(1.32)
-.33*
(.09)
.00
(.01)
-.06*
(.03)
-.20
(.11)
-8.34*
(.79)
-.26*
(.11)
.01
(.01)
-.06
(.03)
-.15
(.12)
-8.14*
(.62)
-.31*
(.09)
.01*
(.01)
-.07*
(.03)
.16
(.13)
-8.00*
(.60)
N=199
*p<.05, two-tailed test
No significant association is observed between the familial variables and levels of
homicide victimization for Black females. Rather, paralleling the earlier findings, Black
women’s absolute status still remains the most important gender related contributor to
levels of Black female homicide victimization. Specifically, greater levels of Black
females’ absolute status are related to lower levels of homicide victimization. With
regards to the other controls that have been found to be associated with city levels of
83
crime, only the percent Black young males is associated with levels of Black female
homicide victimization. This is true for all models except the one assessing cohabitation
(Model 3). However, this relationship is opposite to expectations that greater percentages
of young males will be related to higher levels of lethal violence for Black females.
Multivariate Results for the Relationship Between Familial Variables and Female
Homicide Offending
Familial Variables and White Female Homicide Offending
The results for the familial variables and White females’ homicide offending are
presented in Table 8. The findings demonstrate that familial related variables are
associated with White females’ homicide offending. On average, higher levels of the ratio
of unmarried males to unmarried females, the female divorce and separation rate, and
greater amounts of cohabiting and single father households are positively associated with
rates of killings by White females. A unit increase in the female divorce and separation
rate is associated with about a 14 percent increase in White female homicide offending.
Furthermore, percent cohabiting and single father households are significant, with each
unit increasing levels of killings by White females by about 6 and nearly 20 percent,
respectively. Mirroring the findings reported in the prior chapter on killings by White
females, socioeconomic gender inequality is unrelated to female homicide offending. In
reference to the control variables, White females’ absolute status reaches significance in
Model 3 (cohabitation) and percent young males is associated with an increase in White
female homicide offending in Model 2 (female divorce and separation rate).
84
Table 8: Multivariate Results for White Female Homicide Offending, Socioeconomic
Gender Inequality, and the Independent Effects of the Familial Variables
Model 1
Independent Variables
Ratio Unmarried
Model 2
Model 3
3.31*
(1.42)
Female Divorce/Separation
.13*
(.04)
Cohabitation
.06*
(.02)
Single Father Households
SES Gender Inequality Index
Control Variables
Women’s Absolute Status
Index
Residential Mobility
Percent Male 15-34
South
Constant
Model 4
-.13
(.10)
-.05
(.16)
-.02
(.17)
.18*
(.07)
-.06
(.07)
-.20
(.11)
.02
(.01)
.00
(.04)
-.27
(.17)
-15.82*
(1.77)
-.17
(.11)
-.01
(.01)
.08*
(.04)
-.30
(.17)
-13.74*
(.88)
-.32*
(.10)
.02
(.01)
-.01
(.01)
-.06
(.17)
-12.69*
(.71)
-.08
(.12)
.00
(.01)
.04
(.04)
-.02
(.17)
-13.07*
(.77)
N=199
*p<.05, two-tailed test
Familial Variables and Black Female Homicide Offending
The results for the multivariate analyses of the relationship between family
variables, socioeconomic gender inequality, and Black female homicide offending are
displayed in Table 9. Again, socioeconomic gender inequality is unrelated to killings by
Black females. As is the case with Black female victimization, the familial variables are
not statistically significant for killings by Black women. Thus, the pattern of nil effects of
85
gender inequality found in the basic model (chapter 4) are replicated in models
accounting for familial variables. What appears to be important for Black female killings
is absolute status. In particular, the better off Black women are socially and
economically, the less likely they are to kill. None of the other control variables
demonstrate a significant effect on Black female homicide offending. In brief, the results
indicate that while “familial inequality” variables may matter for killings by White
females, only absolute status is important to levels of Black female homicide.
In sum, the results reported for the familial variables and female homicide
victimization and offending provide evidence that family structure is related to when
women are killed, however, only for Whites. As each of the variables is in a positive
direction (for example, higher rates of female divorce and separation increase levels of
White female homicide victimization) the findings suggest that greater levels of nontraditional relationships are associated with more female killings. Consequently, the idea
that women’s greater freedom from traditional relationships reduces their risk of
homicide victimization is not supported for White females living in large U.S. cities.
86
Table 9: Multivariate Results for Black Female Homicide Offending, Socioeconomic
Gender Inequality, and the Independent Effects of the Familial Variables
Model 1
Independent Variables
Ratio Unmarried
Model 2
Model 3
1.42
(1.53)
Female Divorce/Separation
.01
(.04)
Cohabitation
.00
(.02)
Single Father Households
SES Gender Inequality Index
Control Variables
Women’s Absolute Status
Index
Residential Mobility
Percent Male 15-34
South
Constant
Model 4
.05
(.20)
-.00
(.20)
-.01
(.20)
.00
(.05)
.01
(.20)
-.45*
(.13)
.00
(.01)
-.01
(.04)
-.04
(.17)
-10.77*
(1.75)
-.48*
(.13)
-.00
(.02)
.01
(.05)
-.05
(.14)
-9.52*
(1.09)
-.47*
(.15)
-.00
(.01)
-.01
(.04)
-.04
(.16)
-9.34*
(.84)
-.48*
(.13)
-.00
(.01)
-.01
(.04)
-.05
(.16)
-9.30*
(.83)
N=199
*p<.05, two-tailed test
87
Familial Variables, Poverty Contexts, and White Female Homicide Victimization and
Offending
Results from the prior analyses reveal that socioeconomic gender and familial
inequality exert strong effects on levels of White female victimization and offending.
Consistent with the progression of the analyses in Chapter 4, I now assess whether
familial variables demonstrate a different relationship on victimization and offending for
this group of women in low versus high poverty city contexts. As results from the
analyses on killings by and of Black females did not indicate that socioeconomic and
familial inequality are determinants of these outcomes, the findings presented below
consider only White female homicide victimization and offending for low (Tables 10 and
12) and high (Tables 11 and 13) poverty city contexts. As in Table 8, four models are
presented in each case, for each of the familial variables, along with the socioeconomic
gender inequality and control variables.
Family Variables, Poverty Context, and White Female Homicide Victimization
As displayed in Table 10, socioeconomic gender inequality is significant and
negatively related to levels of White female homicide victimization in low poverty
contexts, except in the model examining cohabitation (Model 3). Thus, the inclusion of
familial variables in low poverty contexts does not change the relationship between
socioeconomic gender inequality and White female homicide victimization.
88
Table 10: Multivariate Results for White Female Homicide Victimization, Familial
Variables and Socioeconomic Gender Inequality in Low Poverty City Contexts
Model 1
Independent Variables
Ratio Unmarried
Model 2
Model 3
4.89*
(1.66)
Female Divorce/Separation
.12*
(.05)
Cohabitation
.06 *
(.02)
Percent Single Father Households
SES Gender Inequality Index
Control Variables
Women’s Absolute Status
Index
Residential Mobility
Percent Male 15-34
South
Constant
Model 4
-.42*
-.38*
-.32*
.22*
(.07)
-.30*
(.14)
(.15)
(.16)
(.15)
-.10
(.12)
.04*
(.01)
-.04
(.04)
.09
(.16)
-16.78
(2.04)
-.16
(.11)
.01
(.01)
.03
(.04)
.18
(.16)
-13.01*
(1.00)
-.35*
(.12)
.03*
(.01)
-.02
(.04)
.35*
(.18)
-11.82*
(.78)
-.07
(.12)
.02
(.01)
.02
(.04)
.43*
(.18)
-12.63*
(.87)
N=100
*p<.05, two-tailed test
Each of the familial variables is related positively to killings of White females in
low poverty city contexts. Consequently, all of the indicators suggest that higher levels of
non-traditional living arrangements increase rates of killings of White females. For
example, a unit increase in the White female divorce and separation rate is associated
with around a 13 percent higher homicide victimization rate. A unit increase in White
single father households leads to an almost 25 percent higher level of White female
89
homicide victimization. As shown in Model 3 of Table 1, the analysis of cohabitation is
the only model that indicates that higher amounts of women’s absolute status are
associated with lower levels of homicide victimization. This is in the expected direction.
Are the findings similar or different for White women living in high poverty city
contexts? The results to answer this question are displayed in Table 11.Unlike the
previous model examining White females in low poverty contexts, socioeconomic gender
inequality does not achieve statistical significance for any of the four models. The
inclusion of familial variables, therefore, does not change the previously reported finding
(in Table 4) that socioeconomic gender inequality is not significantly related to White
female victimization in high poverty city contexts. Three of the four familial variables
achieve statistical significance in the positive direction (ratio unmarried, percent
cohabiting, and percent single father households).
The positive relationships observed between the familial variables and killings of
White women in high poverty contexts again point to the conclusion that, at least for the
cities in this data set, greater freedom for women from traditional marital relationships
does not decrease their risk of homicide involvement. Rather, higher ratios of unmarried
men to unmarried women, divorce and separation rates, and non-marriage households are
associated with higher amounts of female homicide victimization. This finding is
contrary to the prediction of Jensen (2001) that greater freedom from marriage decreases
levels of female homicide involvement. To the extent that non-marital factors represent
disorganization within cities, however, family variables in this instance may highlight the
90
role of general social instability in increasing homicide victimization of females in
conditions of greater poverty, rather than male-female equality.
Table 11: Multivariate Results for White Female Homicide Victimization, Familial and
Socioeconomic Gender Inequality, and High Poverty City Contexts
Model 1
Independent Variables
Ratio Unmarried
Model 2
Model 3
4.71*
(1.10)
Female Divorce/Separation
.07
(.04)
Cohabitation
.04*
(.02)
Single Father Households
SES Gender Inequality Index
Model 4
.02
(.14)
-.10
(.15)
-.02
(.16)
.15*
(.06)
.04
(.15)
-.15
(.09)
-.02
(.01)
.03
(.03)
-.12
(.15)
-13.98*
(1.46)
-.19*
(.10)
-.06*
(.02)
.10*
(.04)
.06
(.17)
-8.97*
(.84)
-.30*
(.10)
-.04*
(.01)
.05
(.03)
.23
(.16)
-8.50*
(.70)
-.11
(.10)
-.05*
(.01)
.08*
(.03)
.24*
(.16)
-9.07*
(.75)
Control Variables
Women’s Absolute Status
Index
Residential Mobility
Percent Male 15-34
South
Constant
N=99
*p<.05, two-tailed test
Family Variables, Poverty Context, and White Female Homicide Offending
The results for the multivariate analyses of the relationship between familial
variables and White female homicide offending are located in Tables 12 (low poverty)
and 13 (high poverty). In low poverty city contexts, socioeconomic gender inequality is
91
not significantly related in any of the four models presented in Table 12. This is similar to
previous findings that socioeconomic gender inequality is not significant for levels of
White female homicide offending. Three of the four family variables are significant and
positively related to killings by White females. Higher levels of the divorce and
separation rate, cohabitation, and single father households are related to higher levels of
killings by White females in low city poverty contexts. None of the other control
variables reach statistical significance in the models.
Table 12: Multivariate Results for White Female Homicide Offending, Familial and
Socioeconomic Gender Inequality, and Low Poverty City Contexts
Model 1
Independent Variables
Ratio Unmarried
Model 2
Model 3
3.76
(2.60)
Female Divorce/Separation
.24*
(.07)
Cohabitation
.10*
(.04)
Single Father Households
SES Gender Inequality Index
Model 4
-.32
(.21)
-.10
(.21)
-.04
(.24)
.26*
(.11)
-.16
(.22)
.06
(.17)
.03
(.02)
-.03
(.06)
-.22
(.26)
-16.44*
(3.18)
.08
(.17)
-.00
(.02)
.08
(.06)
.14
(.24)
-15.90*
(1.58)
-.26
(.19)
.03
(.02)
-.04
(.05)
.12
(.27)
-13.42*
(1.22)
.17
(.18)
.01
(.02)
.02
(.05)
.13
(.28)
-13.80*
(1.32)
Control Variables
Women’s Absolute Status
Index
Residential Mobility
Percent Male 15-34
South
Constant
N=100
92
Table 13: Multivariate Results for White Female Homicide Offending, Familial and
Socioeconomic Gender Inequality, and High Poverty City Contexts
Model 1
Independent Variables
Ratio Unmarried
Model 2
3.39*
(1.52)
Female Divorce/Separation
.06
(.06)
Single Father Households
SES Gender Inequality Index
Control Variables
Women’s Absolute Status
Index
Residential Mobility
Percent Male 15-34
South
Constant
Model 3
.05
(.20)
.02
(.21)
.13
(.07)
.01
(.20)
-.32*
(.12)
.01
(.02)
-.00
(.05)
-.37
(.20)
-15.07*
(1.82)
-.34*
(.12)
-.01
(.02)
.07
(.07)
-.35
(.21)
-12.16*
(1.03)
-.24
(.14)
-.01
(.02)
.04
(.05)
-.13
(.21)
-11.83*
(.77)
N=99
The multivariate results15 for White female homicide offending in high poverty
contexts above (Table 13) also demonstrate that socioeconomic gender inequality is
unrelated to levels of White female homicide offending. Socioeconomic gender
inequality does not achieve statistical significance in any of the family models. This
parallels the findings from the initial analysis of socioeconomic gender inequality as well
15
Table 13 does not contain the model assessing the relationship between levels of cohabitation and
White female homicide offending in high poverty contexts due to lack of convergence when the negative
binomial model regression was conducted. Results from a Poisson model (which does not account for
over-dispersion) did not reveal a significant relationship between levels of cohabitating households and
levels of White female homicide offending in high poverty contexts.
93
as the models assessing White female homicide offending and family variables in low
poverty contexts. One of the variables, the ratio of men to women unmarried, is
significant and positively related to killings by females in high poverty city contexts.
Women’s absolute status is the only control variable that is statistically significant in the
models. In the models assessing the ratio of unmarried men to unmarried women and the
divorce and separation rate, higher levels of women’s absolute status are related to lower
levels of White female homicide offending in high poverty contexts.
To summarize, the results for the models assessing the impact of familial
variables on White female homicide victimization in high and low poverty city contexts
generally resemble those of the models when familial variables are not included with
regards to women’s socioeconomic gender inequality. Though socioeconomic gender
inequality is significant for White female homicide victimization in low poverty contexts,
it does not have a significant impact for killings of White females in high poverty
contexts. With regards to White women’s levels of homicide offending, socioeconomic
gender inequality is unrelated to levels of killings by White females in either low or high
poverty contexts. This mirrors previous findings in this study that gender inequality is
unrelated to levels of White female homicide offending in high or low poverty contexts.
Familial variables achieved significance in some of the models, however, more so for
offending in low poverty when compared to high poverty contexts. In particular, higher
levels of cohabitation, single father households, and the divorce and separation are
associated with higher levels of White female homicide offending in low poverty
94
contexts, while only the ratio of unmarried men to unmarried women was significant and
positively related to levels of White female offending in high poverty contexts.
There are some findings of note with regards to women’s absolute status in the
family models assessing levels of White female victimization in high and low poverty
contexts. While absolute status is associated with less White female homicide
victimization in high poverty contexts when familial variables are not included (Table 5),
when familial variables are included the coefficient for absolute status is significant in
only two of the models. These are the models assessing female divorce and separation
and cohabitation. Although the implications of these findings are not clear, it may be the
case that instability in family arrangements may matter more than women’s absolute
status in some cases and only for White female victimization. For example, rather than
representing women’s liberation, greater amounts of single father households in high
poverty areas (Table 11, Model 4) may be indicating higher amounts of familial
instability that increase women’s risk of lethal violence
95
CHAPTER 6: CONCLUSION
In general, female homicide victims and offenders constitute a relatively small
proportion of those involved in homicide (Belknap 2006). However, the consequences of
homicide involvement are certainly not trivial. Living in areas characterized by greater
amounts of homicide places women at a higher risk of having their lives, and the lives of
those in their communities, disrupted. In more extreme scenarios, homicide offending
may result in a lifetime of incarceration for women. The most obvious cost of higher rates
of homicide is the potential for lives to be prematurely cut short. Statistics reveal that
Black women are more likely, when compared to White females, to incur the above
mentioned costs of homicide. If levels of female homicide are to be reduced, it is
important to investigate the underlying causes of killings by and of females. Increased
attention to the organization of society and structural inequalities is one of the primary
ways by which this goal can be accomplished.
The social structures that contribute to differences in homicide involvement for
women of different racial groups have not received a great deal of empirical attention.
Rather, most studies of female homicide have evaluated women as a singular group. To
date, the majority of empirical work has drawn on feminist arguments to suggest that
socioeconomic gender inequality is the primary factor in understanding levels of female
homicide. Two studies that have considered race provide evidence contrary to the
96
feminist perspective that inequalities between women and men is related to homicide for
all groups of women, showing that socioeconomic gender inequality is less important for
explaining Black, when compared to White, killings by and of females (Haynie and
Armstrong 2006; Veriatis and Williams 2002). Since the publication of these empirical
works, the role of race in the gender inequality-homicide relationship has not been further
investigated. Therefore, the overarching purpose of this dissertation was to assess the role
of gender inequality on levels of female homicide victimization and offending for Black
and White females in the 2000 period, with attention to identifying the structures that
place Black women at an increased risk of homicide involvement. It was also my goal to
assess some untested feminist assumptions pertaining to arguments about the unequal
division of power between the sexes, specifically looking at the role of the impact of
poverty context and family structure on levels of female homicide.
To begin with, I sought to establish the relationship between socioeconomic
gender inequality and city levels of homicide for Black and White women for the 2000
period. In doing so, I replicated prior findings for the relationship between socioeconomic
gender inequality and levels of total, Black and White female homicide victimization and
partially for offending. Then, I assessed early feminist assumptions that women in high
poverty city contexts are more vulnerable to the effects of socioeconomic gender
inequality with regards to homicide involvement. Given Black and White women’s
differing structural position, I believed this may be particularly relevant to Black females
who are more likely to be situated in areas characterized by greater poverty (Peterson and
Krivo 2010). Finally, I explored whether various aspects of family structure, argued by
97
feminist scholars to indicate inequalities between women and men and be important to
female homicide (DeWees and Parker 2003; Jensen 2001), are related to levels of killings
by and of Black and White females. To address the three issues presented above, I
assessed female homicides in U.S. cities with populations greater than 100,000 and Black
populations greater than 2,000, utilizing data from the FBI’s Supplementary Homicide
Reports (1999-2001) and the United States Bureau of the Census for the 2000 period.
In general, this study furthers scholarly knowledge of female homicide by adding
to our knowledge of how poverty contexts influence the gender inequality-homicide
relationship for women of different racial groups. In doing so, I contribute to a better
understanding of the ways in which the intersection of women’s multiple statuses
influences levels of killings by and of females. In looking at familial related variables for
Black and White females, this study provides a broader empirical test of the concept of
gender inequality, as well as contributes to knowledge of how family structure shapes
female homicide involvement. Next, I briefly describe the central findings from the
empirical chapters of this dissertation. I then suggest some implications based upon the
results from the analyses reported in this dissertation.
Summary of Findings
Do feminist theories that argue for the centrality of gender inequality for women’s
criminal outcomes contribute to a better understanding of homicide involvement for
women of different racial groups? The findings from this dissertation suggest that
feminist theory may be applicable to levels of homicide for women. However, these
98
findings are not across the board for all types of homicide involvement or for women
from all walks of life. First, socioeconomic gender inequality was only demonstrated to
be important for levels of female homicide victimization. No support for socioeconomic
gender inequality was found for levels of female homicide offending. Second, the
relationship between socioeconomic gender inequality and levels of female homicide
appears to be dependent upon the racial group being examined. Specifically, levels of
socioeconomic gender inequality were found to be significant and negatively related to
levels of White female homicide victimization, in support of the backlash hypothesis.
Thus, where levels of gender equality are greater, levels of White female homicide
victimization are higher for the 2000 period. However, socioeconomic gender inequality
was not found to be significantly related to killings of Black females. Instead, women’s
absolute status was the most important predictor of Black female homicide victimization.
In addition to race, poverty context also appears to shape the gender inequalityhomicide relationship, however, only for White females and with regards to
victimization. When high and low poverty city contexts were taken into account for
White females, socioeconomic gender inequality was demonstrated to only matter for
levels of victimization in low poverty city contexts. Alternatively, the results indicate that
socioeconomic gender inequality is not significantly related to levels of White, or Black,
female homicide victimization and offending in high poverty city contexts for the year
2000.
The findings regarding poverty contexts run somewhat contradictory to feminist
claims that the gender inequality-homicide relationship will be stronger in areas
99
characterized by greater poverty. Rather, it appears that gender inequality is only
observed amongst women residing in lower poverty areas and only for Whites. This
raises the possibility that feminist claims regarding the role of poverty may be in need of
some revision. F or example, rather than intensify the relationship between gender
inequality and levels of female homicide, it may be the case that impoverished social
conditions override the impact of gender inequality. This may mean that feminist scholars
of gender inequality and homicide may want to pay more detailed attention to the role of
poverty in influencing women’s homicide involvement, and its potential to diminish,
rather than increase, the impact of socioeconomic gender inequality on female homicide
involvement.
Although not the central focus of this dissertation, it is important to note that
women’s absolute status was shown to be a consistent factor in predicting levels of
homicide victimization and offending for women of both racial groups. For example,
women’s absolute status was found to be associated with lower levels of homicide
victimization for both White and Black females. Higher levels of women’s absolute
status were also found to be associated with lower levels of homicide offending for Black
women. Additionally, when poverty contexts were taken into account, absolute status
emerged as an important predictor of all types of female homicide involvement, except
for killings of White females in low poverty contexts.
To consider other contributors to levels of female homicide, this dissertation also
evaluated two potential hypotheses regarding the role of family structure. One potential is
that higher levels of non-traditional family structures (i.e., cohabitation, single father
100
households, divorce, and separation) serve as a proxy for women’s increasing
independence from relationships with men and greater gender equality. Non-traditional
family structures are argued to reduce levels of female homicide victimization and
offending (Jensen 2001). Another possibility is that marriage, by protecting women from
violence that they would otherwise encounter in the public spheres and contributing to
overall social stability, would reduce women’s homicide involvement. According to this
perspective higher rates of non-marriage institutions such as cohabitation and single
father households would be associated with higher rates of female homicide (DeWees
and Parker 2003; Gartner et al. 1990; Messner and Tardiff 1985).
By and large, the results from the multivariate analyses support the latter
hypothesis. Specifically, the findings indicate that greater levels of non-traditional family
structures are associated with more killings by and of White females. No relationship was
observed between the familial variables and levels of Black female homicide
victimization and offending. Once again, women’s absolute status was the only
significant gender related variable for killings by and of Black females. The finding that
higher levels of non-traditional family structures (or more family equality) are related to
higher levels of White female homicide victimization and offending is contrary to the
expectations of Jensen (2001). This would suggest that women’s increasing liberation
from traditional family arrangements is not necessarily associated with lower levels of
White female homicide.
In sum, the findings from this dissertation suggest that socioeconomic gender
inequality may be an important contributor to levels of female homicide for the 2000
101
period, however in limited ways. Specifically, socioeconomic gender inequality appears
to be more important for victimization (when compared to offending) and for White
females (when compared to Black females). Evaluations of the role of poverty contexts
reveal that the amount of poverty within a city also influences the relationship between
socioeconomic gender inequality and homicide victimization for White females. In high
poverty contexts, the relationship between socioeconomic gender inequality and killings
of White females is no longer significant. Instead, this relationship only holds for White
female victimization in low poverty contexts. Finally, support is found for the influence
of family variables on levels of female homicide victimization and offending, however,
only for White females. No relationship is observed between the familial variables and
levels of Black female homicide victimization or offending.
Theoretical and Policy Implications
As of yet, research on the structural causes of homicide for women of different
racial groups is relative sparse. Rather, the tradition of most research on female homicide
has been to treat women as a singular group, with little attention to the ways in which
multiple statuses may influence women’s lives or how factors other than socioeconomic
gender inequality may influence city levels of killings by and of females (Collins 1990;
Daly and Tonry 1997). This dissertation, however, suggests that there are differences
between groups of women with regards to the social structures that contribute to city
levels of female homicide. Notably some of the findings from this dissertation point to
102
the possibility that an approach to female homicide that takes into account multiple
aspects of women’s structural positioning in U.S. society into account may be warranted.
Generally speaking, race appears to play a central role in whether or not
socioeconomic gender inequality is related to levels of female homicide victimization.
Although feminist arguments stress the importance of the institution of gender and the
structural inequalities related to them for female homicide, gender inequality does not
emerge as an important predictor of Black female homicide victimization or offending.
Thus, the findings from this dissertation reveal that relative inequalities between the
sexes may not be demonstrated as significant for all groups of women. Furthermore,
absolute status appears to be an equally or more important factor for explaining levels of
homicide victimization and offending for some groups of women. This reality may be
reflective of the importance of impoverished social contexts for female homicide rather
than gender inequality, particularly for groups of less affluent groups of women.
At the same time, evaluations of high and low poverty city contexts also reveal
some similarities between the structures influencing homicide involvement for women of
different racial groups. In high poverty city contexts, for example, absolute status is the
primary gender related factor influencing levels of female homicide victimization for
levels of killings of both Black and White women. It is also important to note that
absolute status is an important factor for killings of Black females in low poverty
contexts. While it seems logical that levels of absolute status are most significant for
groups of women experiencing the greatest social disadvantage, as this is where women
are likely to experience the lowest levels of absolute status (i.e. Black and White females
103
in high poverty city contexts), it is unclear why the structures related to Black female
homicide victimization in low poverty city contexts would not be similar to the factors
related to White females in low poverty contexts (i.e. socioeconomic gender inequality.)
The fact that absolute status influences levels of Black female homicide
victimization in both low and high poverty contexts, while only influencing White
females in high poverty contexts, potentially adds to evidence of the deep racial
disparities between Black and White females with regards to their involvement in violent
victimization. That is, even in the best conditions in which Black females live (i.e. low
poverty city contexts), the structures contributing to homicide may still be equal to, or
worse than, the poor conditions White women may reside in (i.e. high poverty city
contexts) (e.g., Peterson and Krivo 2010). In short, it appears that race may
fundamentally shape how women experience gender inequality, particularly as race may
be tied to experiencing generally greater social disadvantage. Consequently, researchers
of female homicide may want to pay greater attention to the way in which race shapes the
distribution of absolute status for women in the United States and how this contributes to
Black women’s increased risk of homicide victimization and offending, as well as White
females living in areas of greater poverty.
The results pertaining to race and poverty context also shed light on potential
ways to reduce city levels of female homicide involvement in the United States. In
general, the findings regarding the importance of absolute status for most groups of
women indicate that any efforts to reduce female homicide would need to take into
consideration improving women’s general condition, not only their condition relative to
104
men. At least for Black females in general and White females in high poverty contexts,
improved access to resources such as well paying jobs and education appear to lessen
levels of female homicide victimization and offending. Job creation within cities
characterized by poverty may also be important to reducing levels of homicide
victimization and offending for women living within cities.
Efforts to reduce women’s involvement in homicide may also want to take into
consideration the significant findings for the relationship between socioeconomic gender
inequality and levels of White female homicide victimization for total cities as well as
women in low poverty contexts. Overall, these results indicate that where gender equality
is higher we should expect levels of killings by and of women to be higher as well.
However, the implications for this finding are not readily apparent. Although a
“straightforward” interpretation of this finding would suggest that women may be “safer”
from homicide in areas where they are less equal to men, this is unlikely a sensible
approach to dealing with female killings as a “backlash” finding may really mean that
gender equality is not yet high enough or widespread enough to have the potential effects
for women (i.e., reducing homicide) posited by feminist theorists.
Furthermore, if it were the case that lower levels of gender inequality reduced levels
of White female homicide victimization, it is unlikely that women’s absolute status
would generally reduce their levels of homicide victimization and offending, as
demonstrated in this study. Thus, maintaining low levels of gender equality as a
mechanism of reducing female homicide may counteract efforts to improve women’s
condition and lower their involvement in homicide. Rather than a call to limit gender
105
equality, findings in favor of the backlash hypothesis may point to the importance for
women to continue to achieve greater equality with men. Additional resources to protect
women from male backlash as they achieve greater equality (for example, battered
women’s shelters or police education to reduce male violence toward women) may also
be potential avenues for reducing levels of homicide in this group.
In general, it is important to be cautious about drawing too firm of a conclusion about
the findings regarding the backlash hypothesis. The backlash theory is arguably a short
lived phenomenon in response to women’s increased equality. In order to know if White
females in low poverty contexts were indeed experiencing a backlash in 2000, the
proceeding years would need to be evaluated to determine if the backlash eventually
gave way to greater social acceptance of women’s equality and consequently lower levels
of homicide. Thus, focusing on one time period, as this study did, precludes a real test of
theories of backlash. For example, it could be assessed if in the 2005 period the
relationship between socioeconomic gender inequality and homicide finally gave way to
amelioration. Only then could the backlash claim be fully substantiated. Otherwise, it is
possible that women’s absolute status is primarily driving homicides of all women, and
the backlash finding is attributed to chance or coincidence.
Similarly, the implications of my findings regarding the influence of family
variables are not straightforward. Generally, the results indicate that greater levels of nontraditional family arrangements are associated with higher levels of female homicide
victimization and offending. However, this is only the case for White females. A feminist
interpretation might suggest that higher levels of White female homicide victimization
106
and offending in the context of higher levels of non-traditional family arrangements may
speak to women’s increased risk of incurring lethal violence when they “step out of their
place,” for example by leaving marriages or engaging in cohabitation. This interpretation
would be consistent with the findings for White females in low poverty contexts for
which the backlash hypothesis was demonstrated. However, once again this claim could
not be confirmed without an assessment of the years following 2000.The difficulty in
interpreting findings pertaining to “backlash” may speak more generally to the need for
greater theoretical development of concepts related to backlash or the redefinition of what
backlash means in a more contemporary time period. For example, is backlash a onetime phenomena or does it occur intermittently throughout the years? Furthermore, is
there a threshold for backlash in which women have achieved great enough equality for it
to no longer be applicable?
Theoretical refinement is also necessary in terms of what non-socioeconomic
dimensions signal gender inequality, and in what ways. I considered several familial
inequality variables; however, family variables may not be the only non socioeconomic
aspect important to levels of killings by and of females. Furthermore, as family structures
such as divorce and separation may also potentially be capturing general social
instability as argued by other scholars of crime (e.g., DeWees and Parker 2003) (at least
for White females in this study) it is even more imperative to find other factors that may
represent inequalities between women and men. Furthermore, family factors were not
found to be significant to levels of killings by and of Black females. Why this is so and
what factors of gender inequality may be relevant to Black, or both Black and White,
107
women? In considering these theoretical issues, it is important to articulate and assess
their meaning for women that are differentially situated along race and other (e.g., age,
immigrant status lines).
Limitations and Directions of Future research
There are several limitations of this research that are important to note. The first
of these limitations concerns the availability of data for female homicide. Women
account for a relatively small proportion of homicide victims and offenders. The paucity
of cases of female homicide poses challenges to assessments of female homicide,
particularly when the data are further disaggregated by other factors such as race or
poverty contexts. This is especially true for killings by females, as rates of homicide
offending are substantially lower than rates of victimization. However, the consequences
of women’s homicide are severe and worth understanding. Furthermore, giving a
backseat to women’s homicide involvement ignores structures that are potentially unique
to females and further marginalizes women as a group (Daly and Tonry 1997).
One potential way to improve upon research on gender inequality and female
homicide would be to consider multiple types of women’s criminal involvement.
Feminist theory hypothesizes that homicide victimization and offending, as well as
physical assault and rape, all stem from female directed violence in patriarchal social
systems. Combining different types of violence towards women in future analyses, for
example, can mean greater data availability by which researchers may be more able to
effectively disaggregate by race and poverty status. For example, if victimization is
108
proposed as instances of violence toward women that might turn lethal, aggravated
assault data (which might represent non-lethal instances of female directed violence)
could be combined with homicide victim data. The National Incidence Based Reporting
System which includes data on incidences such as physical assault, as well as data on the
victim's age, sex, and race, may prove as an important resource toward this end. Future
research may also benefit from collecting and analyzing homicides over a longer time
period than three years, looking at spans of ten or even twenty years.
Another potential for future investigations would be to employ micro-level
investigations of female homicide. Researchers may want to look at more detailed
information regarding homicides that take place in individual cities. For example, data on
the reason and type of homicide victimization/offense may be analyzed to tease out the
particular causes of female homicide and whether or not they stem from issues pertaining
to gender inequality. Researchers may also want to consider evaluating the case files of
homicide victims and offenders, perhaps assessing the male-female power dynamic in the
events leading up to instances of homicide to see how non socio-economic indicators of
gender inequality play out. Such information may be particularly valuable to assessing
how family structure influences when women kill and are killed. For example, are female
homicide victims and offenders more likely to have taken on traditionally feminine tasks
within the family as Jensen suggests? Do single fathers have more “progressive” attitudes
toward women or greater number of single father households more reflective of tension
arising between women and men over relationships that lead to homicide victimization
and offending? Finally, what differences between Black and White women with regards
109
to family structure and inequality might explain why family variables were only found to
be significant for White, but not Black, levels of female homicide involvement?
A second limitation of this research concerns challenges inherent in trying to
capture overarching gender inequality in macro-level research. As many feminist scholars
point out, inequalities between women and men are broad and include social, economic,
political, and cultural factors. Thus, it is doubtful that the full spectrum of gender
inequality can be captured in any one analysis. As this dissertation only included aspects
of socioeconomic and familial inequality variables, we do not know how other factors of
gender unequal systems influence killings by and of women from different racial
backgrounds. The lack of support for gender inequality for some groups of women in this
dissertation may not be because gender is unimportant, but rather that researchers have
not yet captured the full spectrum of gender inequality with the current variables being
used. For example, how might laws pertaining to violence against women contribute to
killings by and of Black and White females? Furthermore, will the availability of
governmental resources, such as battered women shelters or legal aid (e.g. Messner 1993)
influence Black and White female homicide differently? Or, do aspects of gender
inequality, for example social expectations regarding women’s roles, influence Black and
White levels of female homicide victimization and offending differently?
More research is needed to fully understand the structural causes of female
homicide. I expanded upon existing work by demonstrating that socioeconomic gender
inequality, which has served as the primary explanation for female homicide, only
110
appears to be important for White females in low poverty contexts. Thus, prevailing
feminist theory used in empirical work on killings by and of females
may not provide a sufficient explanation for the factors contributing to female
homicide for all groups of women. Rather, feminist theories regarding gender inequality
and violence toward women only appear to apply to a subset of female homicide victims.
While in no way should we ignore the structural causes relevant to homicide of and by
any group of women, it is my hope that this research paves the way for researchers of
female homicide to expand upon current applications of feminist theory in research and
pay more detailed attention to investigating how social structures impact levels of
homicide for women from different walks of life.
111
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121
APPENDIX A: CITIES WITH POPULATIONS OVER 100,000 EXCLUDED FROM
THE ANALYSES
List of Cities Dropped Because of Missing Supplementary Homicide Reports Data
Athens-Clarke County (balance), Georgia
Augusta-Richmond County (balance), Georgia
Columbus, Georgia
Aurora, Illinois
Joliet, Illinois
Naperville, Illinois
Peoria, Illinois
Rockford, Illinois
Springfield, Illinois
Indianapolis, Indiana
Sterling Heights, Michigan
Kansas City, Missouri
Omaha, Nebraska
Nashville, Tennessee
Provo, Utah
Bellevue, Washington
List of Cities Dropped Because of Insufficient Black Population
Burbank, California
Costa Mesa, California
El Monte, California
Garden Grove, California
Huntington Beach, California
Irvine, California
San Buenaventura, California
Simi Valley, California
Thousand Oaks, California
Arvada, Colorado
Fort Collins, Colorado
Lakewood, Colorado
Westminster, Colorado
Cape Coral, Florida
Boise, Idaho
Livonia, Michigan
Eugene, Oregon
Salem, Oregon
Brownsville, Texas
Laredo, Texas
McAllen, Texas
West Valley City, Utah
122
APPENDIX B: OPERATIONALIZATIONS OF ALL VARIABLES INCLUDED IN THE EMPIRICAL
CHAPTERS
Variables
Dependent variable
Black Female Homicide Victimization
White Female Homicide Victimization
Black Female Homicide Offending
White Female Homicide Offending
123
Independent Variables
Socioeconomic Gender Inequality Index
Income Inequality
Employment Inequality
Educational Inequality
Occupational Inequality
Operationalizations
Three-year (1999-2001) average number of Black female homicide
victims per 100,000 Black city population
Three-year (1999-2001) average number of White female homicide
victims per 100,000 White city population
Three-year (1999-2001) average number of Black female homicide
offenders per 100,000 Black city population
Three-year (1999-2001) average number of White female homicide
offenders per 100,000 White city population
Average of the standard score for four variables for total, Black, and
White Females: Income Inequality, Employment Inequality,
Educational Inequality, and Occupational Inequality
Ratio of the median yearly earnings in 1999 of total, Black, or White
males to females
Ratio of the percentages of total, Black, or White males to females 16
years or older employed in the civilian labor force
Ratio of the percentages of total, Black, or White males to females 25
years and older with a bachelor’s, master’s, or professional degree
Ratio of the percentages of total, Black, or White males to females 16
years or older employed in the civilian labor force in executive,
managerial, and professional occupations
Ratio Unmarried
Table, Continued
Female Divorce and Separation
Cohabitation
Single Father Households
Control Variables
Absolute Status Index
124
Female Absolute Income
Female Absolute Employment
Female Absolute Education
Female Absolute Occupation
Residential Mobility
Young Male Population
South
Divorce
Ratio of the percentages of total, Black, or White men to women
unmarried, divorced, or separated
Table continues
Percentage of total, Black, or White females 15 years and older
divorced and separated
Percentage of total, Black, or White unmarried partner households out
of married and unmarried partner households
Percentage of single father households with children under the age of
18 out of married and single parent households with children
Average of the standard score for four variables for total, Black, and
White Females: Absolute Income, Absolute Employment, Absolute
Education, and Absolute Occupation
Median yearly earnings for total, Black, or White females in 1999
Percentage of total, Black, or White females 16 years and older
employed in the civilian labor force
Percentage of total, Black, or White females 25 years and older with a
bachelor’s, master’s, or professional degree
Percentage of total, Black, or White females 16 years and older
employed in the civilian labor force in executive, managerial, and
professional occupations
Percentage of population age five and over who lived in a different
residence in 1995
Percentage of males between the ages of 15-34
1 is South, 0 if else
Percentage of individuals fifteen years and older divorced
APPENDIX C: DESCRIPTIVE STATISTICS FOR LOW AND HIGH POVERTY CITY
CONTEXTS
Table 14: Means and Standard Deviations for Female Homicide Victimization and
Offending, Socioeconomic Gender Inequality, Familial Aspects, and Control Variables
for Low Poverty City Contexts
Dependent Variables
Female Homicide Victimization Rate
Female Homicide Offending Rate
Independent Variables
Socioeconomic Gender Inequality Index
Income Inequality
Employment Inequality
Educational Inequality
Occupational Inequality
Ratio Unmarried
Female Divorce and Separation Rate
Cohabitation
Single Father Household
White
Black
5.25
(4.87)
1.37
(1.92)
15.39
(20.30)
7.79
(19.10)
.00
(.64)
1.34
(.11)
1.00
(.01)
1.22
(.10)
.91
(.10)
1.10
(.06)
15.07
(1.92)
11.82
(4.32)
6.29
(1.53)
.00
(.51)
1.19
(.13)
.99
(.03)
1.02
(.24)
.77
(.15)
.93
(.07)
20.61
(2.64)
16.85
(6.30)
8.67
(3.07)
Table Continues
125
Table 14, continued
White
Control Variables, continued
Female Absolute Status Index
0.00
(.83)
40.38
(8.08)
31044.05
(5,289.06)
95.51
(1.55)
27.85
(11.72)
54.31
(6.17)
14.82
(2.63)
.33
(.47)
11.51
(1.88)
Percent in Professional Occupations
Median Yearly Income (in dollars)
Percent Employed
Percent with College Degree
Residential Mobility
Percent Males 15-34
South =1
Percent Divorced
N=100
126
Black
0.00
(.86)
33.32
(8.49)
28,308.81
(5,658.40)
91.75
(2.94)
20.39
(7.95)
54.31
(6.17)
16.09
(2.95)
.33
(.47)
13.28
(2.32)
Table 15: Means and Standard Deviations for Female Homicide Victimization and
Offending, Socioeconomic Gender Inequality, Familial Aspects, and Control Variables
for High Poverty City Contexts
Dependent Variables
Female Homicide Victimization Rate
Female Homicide Offending Rate
Independent Variables
Socioeconomic Gender Inequality Index
Income Inequality
Employment Inequality
Educational Inequality
Occupational Inequality
Ratio Unmarried
Female Divorce and Separation Rate
Cohabitation
Single Father Household
Control Variables
Female Absolute Status Index
White
Black
9.94
(8.28)
1.72
(2.0)
22.93
(16.67)
9.29
(11.14)
.00
(.59)
1.28
(.11)
1.00
(.02)
1.15
(.09)
.87
(.10)
1.13
(.07)
15.08
(2.25)
15.26
(4.81)
7.00
(1.66)
.00
(.49)
1.19
(.12)
.98
(.04)
.93
(.21)
.67
(.12)
.96
(.05)
19.96
(2.35)
21.04
(5.03)
8.45
(2.22)
.00
(.84)
.00
(.75)
Table Continues
127
Table 13, Continued
White
Control Variables, continued
Percent in Professional Occupations
39.26
(9.39)
28,695.62
(5,282.43)
93.31
(2.52)
26.77
(13.50)
50.59
(5.24)
15.81
(2.68)
.32
(.47)
11.45
(2.13)
Median Yearly Income (in dollars)
Percent Employed
Percent with College Degree
Residential Mobility
Percent Males 15-34
South =1
Percent Divorced
N=100
128
Black
28.48
(5.47)
24,630.42
(4,183.03)
87.15
(22.80)
13.34
(5.07)
50.59
(5.24)
14.65
(2.45)
.32
(.47)
12.50
(2.60)
APPENDIX D: CORRELATION MATRICES OF ALL VARIABLES FOR TOTAL, BLACK, AND WHITE FEMALES
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Total Females
129
1. Female Homicide Victims
1.000
2. Female Homicide Offenders
0.959
1.000
3. SES Gender Inequality Index
-0.219
-0.206
1.000
4. Income Inequality
-0.294
-0.297
0.655
1.000
5. Employment Inequality
-0.037
-0.024
0.583
0.256
1.000
6. Educational Inequality
-0.164
-0.161
0.823
0.403
0.277
1.000
7. Occupational Inequality
-0.09
-0.067
0.611
0.091
0.024
0.518
1.000
8. Ratio Unmarried
-0.083
-0.087
0.133
-0.002
0.039
0.158
0.161
1.000
9. Female Divorce and Separation Rate
0.086
0.119
-0.25
-0.121
-0.069
-0.148
-0.331
-0.099
1.000
10. Cohabitation
0.176
0.194
-0.506
-0.523
-0.402
-0.347
-0.08
-0.018
0.334
1.000
11. Single Father Households
0.067
0.074
-0.293
-0.178
-0.108
-0.124
-0.373
0.225
0.479
0.552
1.000
12. Women's Absolute Status Index
-0.091
-0.101
0.254
-0.129
-0.132
0.204
0.735
0.079
-0.414
-0.146
-0.477
13. Women's Absolute Income
0.023
-0.006
0.144
-0.187
-0.064
0.174
0.459
0.105
-0.336
-0.136
-0.324
0.786
1.000
14. Women's Absolute Employment
-0.24
-0.257
0.29
0.081
-0.141
0.325
0.509
0.224
-0.264
-0.358
-0.319
0.763
0.554
1.000
15. Women's Absolute Educational Status
-0.051
-0.038
0.184
-0.189
-0.127
0.05
0.756
-0.006
-0.395
0.037
-0.449
0.883
0.498
0.502
1.000
16. Women's Absolute Occupational Status
-0.033
-0.036
0.229
-0.135
-0.108
0.13
0.723
-0.06
-0.382
-0.03
-0.496
0.897
0.565
0.482
0.939
1.000
17. Young Male Population
-0.004
0.011
-0.106
-0.327
-0.014
-0.212
0.269
0.122
-0.354
0.227
-0.078
0.231
-0.1
0.04
0.483
0.34
1.000
18. Residential Mobility
-0.25
-0.237
0.256
0.01
0.122
0.183
0.369
0.045
-0.092
-0.042
-0.056
0.346
0.119
0.335
0.383
0.31
0.47
1.000
19. South
-0.025
0.018
0.165
0.035
0.262
0.059
0.086
-0.144
0.291
-0.221
-0.353
0.015
-0.17
-0.01
0.098
0.13
0.01
0.1
1.000
20. Percent Divorced
-0.053
-0.029
-0.092
0.037
-0.196
0.033
-0.12
0.099
0.849
0.214
0.397
-0.18
-0.22
0.072
-0.22
-0.22
-0.4
0.028
0.18
1.000
1.000
White Females
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
130
1. Female Homicide Victims
1.000
2. Female Homicide Offenders
0.851
1.000
3. SES Gender Inequality Index
-0.134
-0.117
1.000
4. Income Inequality
-0.203
-0.203
0.682
1.000
5. Employment Inequality
-0.015
-0.007
0.497
0.089
1.000
6. Educational Inequality
-0.12
-0.117
0.739
0.421
0.165
1.000
7. Occupational Inequality
0.003
0.035
0.574
0.19
-0.015
0.257
1.000
8. Ratio Unmarried
0.074
0.034
-0.287
-0.283
-0.033
-0.152
-0.247
1.000
9. Female Divorce and Separation Rate
-0.012
0.073
-0.034
-0.04
0.04
0.095
-0.181
0.074
1.000
10. Cohabitation
0.095
0.142
-0.561
-0.55
-0.348
-0.501
-0.001
0.214
0.121
1.000
11. Single Father Households
0.004
0.065
-0.407
-0.186
-0.211
-0.141
-0.475
0.281
0.518
0.426
1.000
12. Women's Absolute Status Index
0.052
0.046
0.146
-0.053
-0.216
-0.105
0.738
-0.26
-0.296
0.175
-0.503
1.000
13. Women's Absolute Income
0.089
0.059
0.136
-0.109
-0.099
-0.015
0.562
-0.216
-0.274
0.193
-0.339
0.827
1.000
14. Women's Absolute Employment
-0.019
0.154
0.167
-0.367
0.108
0.475
-0.223
-0.024
-0.112
-0.285
0.651
0.339
1.000
15. Women's Absolute Educational Status
0.046
0.057
0.061
-0.137
-0.131
-0.288
0.709
-0.212
-0.352
0.291
-0.5
0.908
0.665
0.406
1.000
16. Women's Absolute Occupational Status
0.056
0.036
0.134
-0.098
-0.119
-0.155
0.704
-0.213
-0.333
0.208
-0.546
0.934
0.742
0.416
0.943
17. Young Male Population
0.043
0.052
-0.281
-0.402
-0.04
-0.468
0.211
0.071
-0.364
0.373
-0.192
0.312
0.138
-0.05
0.54
0.4
1.000
18. Residential Mobility
-0.142
-0.06
0.18
0.052
0.068
-0.009
0.336
-0.324
0.1
-0.042
-0.138
0.258
0.109
0.214
0.303
0.23
0.38
1.000
19. South
-0.051
-0.096
0.26
0.079
0.274
0.093
0.202
0.16
0.047
-0.291
-0.42
0.131
-0.14
0.115
0.213
0.25
0.09
0.1
1.000
20. Percent Divorced
-0.027
0.065
-0.087
0.033
-0.165
0.031
-0.115
0.147
0.893
0.171
0.509
-0.19
-0.29
0.149
-0.25
-0.25
-0.3
0.063
0.07
12
13
14
15
16
Black Females
1
2
3
4
5
6
7
8
9
10
11
20
1.000
17
18
19
1.000
20
131
1. Female Homicide Victims
1.000
2. Female Homicide Offenders
0.952
1.000
3. SES Gender Inequality Index
-0.27
-0.284
1.000
4. Income Inequality
-0.097
-0.083
0.353
1.000
5. Employment Inequality
-0.139
-0.129
0.47
0.012
1.000
6. Educational Inequality
-0.174
-0.204
0.66
-0.147
0.077
1.000
7. Occupational Inequality
-0.141
-0.165
0.562
-0.143
-0.128
0.419
1.000
8. Ratio Unmarried
0.163
0.185
-0.138
-0.027
-0.127
-0.11
-0.018
1.000
9. Female Divorce and Separation Rate
-0.097
-0.088
0.076
-0.055
-0.022
0.127
0.105
-0.051
1.000
10. Cohabitation
0.156
0.17
-0.106
0.012
-0.145
0.008
-0.091
0.45
0.02
1.000
11. Single Father Households
-0.118
-0.137
0.241
-0.035
0.045
0.25
0.231
0.359
0.247
0.294
1.000
12. Women's Absolute Status Index
-0.162
-0.198
0.112
-0.233
-0.058
0.137
0.384
-0.315
0.01
-0.473
0.012
1.000
13. Women's Absolute Income
-0.045
-0.095
0.087
-0.374
-0.102
0.237
0.417
-0.312
0.055
-0.325
0.038
0.839
14. Women's Absolute Employment
-0.243
-0.267
0.088
-0.092
-0.185
0.126
0.33
-0.217
0.112
-0.394
0.065
0.781
0.504
1.000
15. Women's Absolute Educational Status
-0.155
-0.173
0.125
-0.148
0.059
-0.014
0.359
-0.249
-0.1
-0.459
-0.011
0.903
0.622
0.646
1.000
16. Women's Absolute Occupational Status
-0.111
-0.143
0.083
-0.185
0.028
0.118
0.21
-0.299
-0.033
-0.44
-0.05
0.903
0.746
0.525
0.824
1.000
17. Young Male Population
-0.221
-0.229
0.13
-0.178
0.118
0.081
0.245
0.168
-0.037
-0.064
0.371
0.124
-0.07
0.187
0.258
0.05
1.000
18. Residential Mobility
-0.312
-0.283
0.295
-0.071
0.142
0.2
0.331
-0.12
0.055
-0.169
0.125
0.239
0.027
0.281
0.341
0.17
0.39
1.000
19. South
-0.001
0.057
-0.134
0.111
0.179
-0.258
-0.306
-0.02
-0.076
-0.146
-0.346
-0.16
-0.45
0
0.017
-0.11
0
0.1
1.000
20. Percent Divorced
-0.134
-0.129
0.101
0.02
0.02
0.037
0.13
0.172
0.718
0.068
0.3
0.023
0.017
0.116
-0.03
-0.03
0.09
0.069
-0.1
1.000
1.000