1
CHAPTER 1
INTRODUCTION
This thesis seeks to explore and enhance the understanding of Intimate Partner
Violence (IPV) arrest and recidivism and its predictors. I also pursue gaps in knowledge
within the existing literature by investigating this social problem through the lens of
concentrated disadvantage and the related concept of collective efficacy. These theories
will be the guiding frameworks throughout this paper and will hopefully allow us to more
effectively explain and understand IPV recidivism.
As many California inmates are transferred to county jails and released from
prison, public safety has become very important. The question of why people commit
crimes becomes an integral question to the criminal justice system itself. This research
will narrow its focus to one pertinent issue within our society which is; IPV offenses
committed by women. I will explore the factors associated with IPV crimes and the
reasons why people, in particular women, reoffend. Recidivism is a rampant problem
within American society on which the criminal justice system has been increasingly
focused. For example, the recidivism rate in America averages about 67% within three
years for all types of offenses (Bureau of Justice Statistics, 2012). More specifically,
some researchers estimate that 90% of domestic violence abusers recidivate (Buzawa
2012). Therefore, IPV recidivism is a social issue that needs to be understood and further
studied.
Intimate partner violence (also labeled domestic violence) in many cases is a
pervasive crime throughout America. Specifically, in America both women and men
commit acts of violence against each other while in defined relationships. Intimate
2
partner violence recidivism is a very significant topic to discuss because it is a rampant
social issue that needs to be addressed. According to Straus and Gelles (1980), violent
families exist in nearly every American neighborhood and one in every three American
couples will participate in violent acts against each other. In addition, Sacramento District
Attorney Jan Scully has stated that in 2011 her staff reviewed 6,000 cases in which her
prosecutors filed almost half, revealing the degree of domestic violence in the region
(Minugh, 2012).
Intimate partner violence continues to receive significant official attention as
indicated by the recently released Bureau of Justice Statistics special report on IPV
victimization trends from 1993-2010 (BJS 2012).This report illustrated the decline of IPV
over 17 years by 64% although over 900,000 cases are still reported every year. In
relation to gender, “from 2000-2005, the rate of IPV for females continued to decline
(down 31%), while male victimization rates remained stable” (Catalano 2012: 3). These
trend lines thus differ from each other over the years and demonstrate the decrease in
IPV, which perhaps, can be explained given the history of the criminal justice response to
IPV.
Criminal Justice Response to IPV Over The Last 30 Years
Throughout history, humans have enacted laws in order to control human
behavior. Since the 1980’s, “the concept of deterrence as a general preference for crime
control became the dominant perspective in mainstream academic literature and policy
circles” (Buzawa et. al. 2012: 167). Specifically, the social problem of intimate partner
violence has been the target of many changes throughout the last thirty years. For
3
example, Buzawa (2012) explains how domestic violence courts, prosecutors, and police
units have been established in order to explicitly deal with IPV. For example, the criminal
justice system has tried to deal with Domestic Violence by implementing, “mandatory
arrest and “no-drop” prosecution in the 1980’s and early 1990’s,” (Buzawa 2012: 9).
Additionally, the courts have evolved in that there are specialized “dedicated”
prosecutors, DV courts, as well as DV police units (Buzawa 2012: 2) These
specializations have created better outcomes for all parties involved because of its ability
to speed up the process efficiently. Currently domestic violence is now considered a very
salient issue in which many parties are involved. Because of this, more money has been
appropriated for administration and training, which has led to the increase of experts in
the field. Another benefit for the victims of domestic violence lies with the increased
access to civil restraining orders. For instance, by the early 1990s, “all of the 50 states
have enacted laws providing victims of domestic violence direct access to courts via
protective orders” (Buzawa 2012: 279). Buzawa (2012) stated that the access to these
restraining orders has also increased with the help of the Violence Against Women Act
(VAWA), which put a greater emphasis on courts granting them along with improved
enforcement. Victim services units have also been created within prosecutor’s offices in
order to help victims deal with the trauma caused by domestic violence. These units are
typically comprised of victim advocates who are trained to deal with domestic violence
cases. Since 2002, Family Justice Centers have been established to aid victims of
domestic violence by providing them with a one stop shop by bringing law enforcement,
non-profits, prosecutors, and advocates together. These centers focus on the community,
4
organizations already in place to combat DV, and victim’s needs. Family Justice Centers
have been growing, particularly in California with the possibility of one opening up in
Sacramento. This trend highlights the social problem of domestic violence but places it in
a context of reconstruction and prevention and intervention (Minugh, 2012). Hence, in
the late 1990’s, Mills (1999) as well as other researchers in this field, reported that
society must not rely solely upon CJ intervention. Buzawa (2012) postulates that
considering the decline in DV offenses, legal reforms have saved people’s lives by the
responsiveness of the CJ agencies, the involvement of social service institutions, and
shelters for those abused. Over the last thirty years more money has been put into
domestic violence programs and prevention. This money comes from the federal
government as well as through the state level governments. More recently, however, with
budget deficits domestic violence spending has been reduced (Buzawa, 2012). With these
declines, the threat of IPV increasing may become a reality again if we do not change our
societal perceptions and make a conscious effort to intervene and prevent IPV before it
happens within our communities.
Although men tend to be reported and regarded as the primary perpetrators of
IPV, it is also important to know that women can also be found guilty of this crime.
Historically, the societal response to domestic violence has constructed women as the
victims. (For example, there are journals titled “Violence Against Women” whereas
there is no counterpart for violence against men.) One reason why women (as well as
men) may be underreported in committing IPV offenses is because they feel that the
justice system is not the right avenue for recourse with regard to IPV, that nothing will be
5
done, and that the authorities will not believe them (Tjaden 2000). Additionally, men are
seen as the aggressors and dominant figures in society which leads people to believe that
they have a higher tendency to commit violent acts against others and a lower chance of
admitting weakness and victimization. For example, when assuming the status of the
male victim one author states that, “Men who attempt to claim this status will be seen as
denying the dominant male role ascribed to them by most in society and instead
succumbing to the passive, dependent position normally reserved for women. By
acquiescing to a role that is normally ascribed to a woman, the man assumes a position of
subordination, which is considered by many to be anti-masculine. Such a man would fear
being marginalized, causing him to "hide" his experience from others” (Doyle, 1995;
Kimmel,1994 within Migliaccio 2001: 209). Instead of reporting IPV to the police by
filing a report or calling the authorities, men may be too ashamed to let anyone else know
what is occurring thus, creating misrepresentations in research and data. Therefore, it is
important to recognize these stereotypes and the impact they have on research, and to
explore the large gap in the research literature on intimate partner violence committed by
women.
The research question generated from this subject is to determine the relationship
between concentrated disadvantage and IPV arrest and recidivism rates based on zip code
data for female offenders. An additional objective of this research is to identify other
variables (e.g. offender characteristics, victim characteristics, and joint characteristics)
which help explain IPV recidivism of women.
6
CHAPTER 2
LITERATURE REVIEW
Intimate Partner Violence Defined
Throughout human history, we have been interacting with each other and forming
social relationships. These relationships have varied over time through culture,
geographic location, and societal necessity. However, these relationships have
consequences and sometimes they can turn violent. Donald Dutton (2006) defines
domestic violence as any type of violence occurring between intimate partners, which can
include married or unmarried and same sex or not. Domestic violence causes many
problems which can last a lifetime. “The consequences of domestic violence are
substantial – in terms of physical injury, psychological and emotional distress, suicide,
and substance abuse among victims” (Umberson et al. 1998: 442) In this study, we use
Intimate Partner Violence (IPV) to refer to domestic violence. A number of studies
explore the causes of IPV and the disparities between the genders related to the roles of
victim and perpetrator.
Gender Symmetry and IPV
There are many studies that focus on intimate partner violence as a one way street
in terms of the woman being the victim and the man as perpetrator. Loseke (1987) stated,
“Abuse has been defined as a woman’s issue” (p. 232), subsequently defining “women as
victims and men as trouble-makers” (Migliaccio 2002: 27) More recently, the literature
on IPV has slightly shifted towards a more symmetrical view of both women and men as
perpetrators and victims, allowing for less gender discrimination. For example, in one of
his articles, Todd Migliaccio (2002) conducted a qualitative analysis on husbands who
7
were abused by their wives, and the results were comparative to women’s experiences
with partner violence. Migliaccio provided a venue for men to be able to communicate
their stories and add to the literature on IPV. His qualitative analysis helped shine some
light on the understudied violence against men. For example, Migliaccio reminds us that,
“when analyzing a topic that is engendered, such as spousal abuse, one should heed
Lorber’s (1995) call to look beyond gender” (Migliaccio 2002). There are gaps within the
literature on IPV, and this research hopes to capitalize on that by including pieces of
information that has been excluded in the past such as offender criminality or prior
criminal history which we will discuss more in depth later.
In addition, other researchers in this field claim gender symmetry when talking
about the (CTS) Conflict Tactics Scale, Straus and Gelles (1986) and Straus and Kantor
(1994) used the CTS to measure how conflict is dealt with in relationships between
women and men. The CTS is comprised of three variables: verbal aggression, reasoning
and violence or physical aggression. The survey created, “was employed on three
separate occasions with a new random sample of married or cohabitating couples, half of
whom were men and the other half women” (Straus and Kantor, 1994). In all three of the
studies, “the rates of violence by men and women against their spouses were found to be
relatively equal” (Migliaccio 2002: 28). Thus, the concept of gender symmetry is
supported using different tools and strategies to measure IPV by gender.
There are many crimes that are typically committed by men and typically
committed by women but Lauritsen (2011) believes that criminologists are aware that
males outnumber females in amounts of criminal victimization, excluding violence by
8
intimate partners and sexual assault. Lauritsen has written extensively about gender
differences and IPV risks. In one of her articles, Lauritsen (2011) uses data from the 1995
Area-Identified National Crime Victimization Survey (NCVS) to examine whether the
relationships between individual, family, and neighborhood factors and victimization risk
are similar in strength and direction for males and females. She finds that, “most risk
factors for violent victimization are similar across gender and crime type” (Lauritsen
2011: 538). Considering most of the factors for victimization were similar across gender
and type of crime, one can suspect that domestic violence is pervasive by both genders.
In addition, the results also provide an association with concentrated disadvantage in
Lauritsen’s (2011) paper which shows that women’s risk of neighborhood stranger
violence is significantly related to age, length of residence in the current home, and
whether they reside in a central city area. This research offers support for community
level variables or concentrated disadvantage, which is the theoretical framework guiding
this thesis.
Men and women are both victims of domestic violence and they also have the
ability to be the offenders of this socially constructed crime. Straus and Ramirez (2007)
are quoted in saying, “…In the majority of couples where one partner is violent, both
partners have committed one or more assaults” (p.287). Straus and Ramirez are making a
point to say that IPV is a two way street and often times it occurs from both partners.
Some evidence suggests that women abuse men physically and mentally just as men
abuse women. Straus and Ramirez (2007) go further to say, “The results indicate that
women and men have similar prevalence rates for both any and sever[e] assaults, and for
9
chronicity of minor assaults” (p.287). Instead of focusing on one gender committing all
the domestic violence, these researchers posit that both men and women commit severe
and minor crimes. One researcher (Brott 1994) postulates that men are victims of
domestic violence just as much as women are. In addition, Kimmel (2002) believes that
domestic violence displays gender symmetry in that an equal number of men and women
are victims of domestic violence. However, male victims of domestic violence continue
to be an often-ignored problem. These authors are in the minority by representing men as
equally likely as women to be victims. Most of the literature on IPV and domestic
violence claim that women are the primary victims of such assaults, therefore giving less
credibility for accusations made by male victims. Considering the underrepresentation of
men as victims in the field of IPV, it is important to address these gaps within the
literature. This thesis seeks to expose some lacunae within the literature in order to
understand the topic better and to help prevent the crime from reproducing itself by
women as well as by men.
Theories within the Classical Cannon
It would be negligent to not include any mention of classical theory because it
adds detail and historical context to contemporary perspectives and the foundations for
them. These perspectives are then challenged and utilized by other researchers to critique
and develop their own interpretations. Social disorganization theory provides a good
example of classical theory to add to the literature on intimate partner violence
recidivism. Social disorganization theory is defined as, “the inability of a community
structure to realize the common values of its residents and maintain effective social
10
controls” (Kornhauser 1978, 120; Bursik 1984, 12 within Sampson, 1989, 777). Social
disorganization theory is used in the most current research on community disadvantage
thereby making it necessary to include in this research. For example, Benson writes,
“Recent research patterned in the social disorganization tradition reveals that
concentrated poverty, residential mobility, family disruption, and a youthful age structure
may weaken neighborhood organization and collective supervision” (Benson et al. 2004,
328).
Christopher Browning (2002) also uses the theory of social disorganization to
explain the predictors of crime to partner violence in particular. One of Browning’s
(2002) articles adds to the literature on IPV and collective efficacy (also known as the
combination of social cohesion and informal controls) by discussing individual-level
predictors and neighborhood-level processes together in relation to influence on partner
violence. Browning (2002) was able to tie in agency (free will independent of structure)
and structural predictors in order to develop his hypotheses. Browning’s first hypothesis
was, “Structural features of urban communities, concentrated disadvantage, residential
stability, and immigrant concentration are associated with the prevalence of intimate
homicide at the community level and involvement in a violent partnership at the
individual level” (Browning 2002: 837). Browning’s second hypothesis is, “Collective
efficacy is a significant negative predictor of intimate-partner homicide at the community
level and of involvement in a violent partnership at the individual level” (Browning 2002:
837). Both of these hypotheses serve as the basis for my own in this thesis that collective
efficacy reduces the amount of IPV. Four datasets were used in Browning’s (2002) study:
11
1990 Decennial Census, 94/95 project on human development in Chicago Neighborhoods
Community Survey, Chicago Homicide data, and the 1995-97 Chicago Health and Social
life survey.
Browning (2002) found a negative association between neighborhood
cohesion and informal social control and intimate homicide rates and nonlethal partner
violence. This is a telling find because it adds to the explanation of IPV and its
association within a neighborhood context.
In addition, Robert Merton, a classical theorist has also put forward his own
theory termed strain theory in order to explain IPV. For example, “Essentially Merton
argued that when alienation is experienced (strain) a social actor will seek a behavioral
response designed to minimize his or her feelings of alienation. Each of the three
“causes” of battering: individual, cultural, and structural—can all be interpreted as
different forms of “strain,” each of which calls for a behavioral response designed to
reduce the strain” (Collins 2004; Hill 2005; Potter 2004 within Smith 2008: 157). In his
article, Smith (2008) goes further to say that Merton’s strain theory is very applicable to
the perpetuation of IPV. When one person batters another, they alienate that person from
themselves (the intimate partner) which reproduces or perpetuates the system of violence.
On the other hand, Foucault would probably take another viewpoint and suggest that it is
not the individual’s fault; rather it is a structural problem that is recreated and sustained
by those in power because violence and crime in society serve a function.
Modern Theoretical Framework
There are many theories that help to explain social phenomena and in this case we
are trying to discover new insight on the topic of intimate partner violence arrest and
12
recidivism. The theory of concentrated disadvantage and its correlate, collective efficacy,
is the theory guiding this research and its content.
I hypothesize that concentrated disadvantage is positively related to IPV arrest
rates for both male and female offenders. For the purpose of this study, concentrated
disadvantage is measured in a community or neighborhood context in that some contain a
lot of social problems in which they lack the advantages of other communities.
In his recent book, Robert Sampson proposes that social disorganization theory generates
a hypothesis stating, “community-level variations in social control contribute to varying
crime rates” (Sampson 2012: 150). However, it is important to be cognizant of the
shortfalls social disorganization contains, such as requiring direct social controls through
friends or family in its definition. Therefore, Sampson offers a theory of his own to
explain violent criminal behavior by introducing the concept of collective efficacy.
Sampson (2012) states that the concept draws together two fundamental mechanisms –
Social cohesion (the “collectivity” part of the concept) and shared expectations for
informal controls (the “efficacy” part) comparable to social capital. Neighborhood
efficacy relies on mutual trust and social cohesion. Sampson (2012) uses a quantitative
methodology by conducting a Community Survey of 8,782 residents of 343 Chicago
Neighborhoods in 1995. He designed vignettes such as “can neighbors be counted on to
take action if 1: children were skipping school and hanging out on a street corner, 2:
children were spray painting graffiti. 3 children were showing disrespect to an adult, 4: a
fight broke out in front of their house. 5: the fire station closest to home was threatened
with budget cuts” (Sampson 2012: 156). This approach measures how much social
13
control/efficacy neighbors feel is in place by asking questions about their perceptions of
other neighbor’s potential actions. Social science has a greater ability to answer questions
regarding perception instead of predicting actual behavior when faced with a decision.
Attitude can be measured more effectively within Sampson’s work on collective efficacy,
which is a very important aspect of the theory.
The results section of this book reveals the salience collective efficacy
encompasses and how it is defined. For example, “The social cohesion/trust (community
relationships) part of the theory of collective efficacy was measured by
coding whether or not participants agreed with the following propositions
of public perception: ‘People around here are willing to help their
neighbors’ ‘people in this neighborhood can be trusted’ ‘This is a closeknit neighborhood’ ‘People in this neighborhood generally get along with
each other’ and ‘people in this neighborhood share the same values’”
(Sampson 2012: 156).
The results of this study were that social cohesion and social control were strongly related
across neighborhoods, which creates the collective efficacy measurement (Sampson
2012). Sampson found that collective efficacy was associated with lower rates of
violence when controlling for concentrated disadvantage, residential stability, immigrant
concentration, and demographic variables (Sampson 2012: 155). The neighborhoods that
contained higher collective efficacy had a reduced amount of violence. This process
illustrates how previous violence threatens the effectiveness of collective efficacy while
at the same time collective efficacy is very beneficial in reducing crime. In addition,
14
collective efficacy aids in the reduction of crime and violence because it, “helps to
explain the effect of both structural deprivation and the density of personal ties on crime
rates. Ultimately, research has shown that there is a constant negative association
between collective efficacy and crime rates” (Sampson 2012: 157). To help explain this
phenomenon Sampson stated, “Collective efficacy is undermined by the concentration of
disadvantage, racial segregation, family disruption, and residential instability, which in
turn fosters more crime” (Sampson 2012: 157).
Another article that used neighborhood context as an explanatory indicator for
IPV was about household economic condition and neighborhood disadvantage in relation
to IPV. The authors, Benson and Fox (2006) used the 2nd wave of National Survey of
Families and Households (NSFH) combined with tract level data from 1990 U.S. Census.
A subsample of co-resident couples with a child aged 5-17 in the household was selected
for analysis with a total sample of 2,273. In this study, Fox and Benson (2006) measured
IPV in three different ways; as any physical violence in which both partners are identified
as aggressors, and as severe violence in terms of injury and frequency. The authors
discovered that in spite of how IPV was assessed, couples that committed IPV offenses
were more likely to present a vulnerable economic risk profile and to live in
neighborhoods that contained high levels of disadvantage. When these economically
vulnerable couples compared living in advantaged versus disadvantaged neighborhoods
there were no prominent differences in rates of IPV, regardless of how IPV was
measured. However, neighborhood context still mattered in comparisons among
economically advantaged couples; in which rates of IPV were significantly higher among
15
those in disadvantaged neighborhoods (Benson 2006). This study supports the theory of
concentrated disadvantage because it reveals how strong of a factor neighborhood context
is in explaining IPV.
Research and social policy have grown out of concern for victim safety in regard
to IPV offenses, making it a very important subject to explain and prevent. One
researcher within the field of Criminology and Sociology has sought to explain IPV
recidivism by using a large sample of arrestees. Kingsnorth (2006), collected IPV data
from the Sacramento Country Court System. He used a sample size of 1,157 heterosexual
couples collected between January 1, 2000 and April 30, 2000. Kingsnorth was able to
demonstrate that the, “use of weapon, the offender’s prior arrest for any offense, and the
presence of a protective order at the time of the precipitating incident all predicted rearrest for intimate violence within an 18-month follow-up period” (Kingsnorth 2006:
917). All of these variables are very important in understanding recidivism of IPV.
Although these are individual level characteristics, there may be some structural basis
such as neighborhood context that accounts for their frequency of occurrence.
In the Sacramento Bee, an article titled “Right Next Door, But a World Apart” by
Grace Rubenstein (2012) examines inequalities in health, neighborhood appearance, and
violence between two zip codes. Data for this study comes from the years 2004-2008 and
focuses on two zip codes with comparable size populations that are within one mile of
each other in Sacramento, California. This article discusses social problems in a
community context which can also be understood as social ecology. The newspaper
article suggests that beneath the visible surface lie the non-superficial disparities that can
16
and do affect people’s lives within each community (Rubenstein 2012). People’s lives are
influenced from birth depending on one’s family and where they were born. The poorer
neighborhoods have less opportunities/resources/knowledge to help themselves out of the
social problems they experience. Therefore, concentrated disadvantage lies deep in the
roots of these neighborhoods and is continued by social reproduction. Rubenstein (2012)
reminds us that there is no scientific proof to state that these neighborhoods with higher
concentrated disadvantage cause poorer health or violence because life is too complex
and interwoven. Even though life may be structured in this way, trends and themes still
appear within the existing data. These trends reveal to us that some neighborhoods or
communities have better chances or more opportunities to stay away from crime and
increase the well-being of the inhabitants in general. The author claims that ideology,
attitude, norms are part of the problem and that ultimately, individuals reproduce the
social problems. It is just as much of a structural problem as it is an individual problem.
IPV Across Race and Ethnicity
There are many articles on IPV or Domestic Violence that specifically speak to
race and ethnicity; therefore, it is important to examine the effects of race and ethnicity in
this thesis. Race and ethnicity are typically referred as groups of people who have
similarities and differences in biological traits deemed by society to be socially
significant; which often forecast social inequality. It is an important concept to cover
because race is frequently found to be statistically significant in the recidivism literature
(Andrews et al. 1990; Gendreau et al. 1996 within Werhman 2010: 543). While looking
through the research on IPV, the assertion above was true in that many articles suggest
17
race is a predictive variable in determining IPV arrest and recidivism. In addition, in one
article the author contends, “Research demonstrates that Blacks are more likely to
recidivate than Whites overall (Langan and Levin 2002), and also that Black releases are
more likely to cluster in communities characterized by concentrated disadvantage”
(Travis, 2006 within Wehrman 2010: 541). Not only does this suggest something about
race and IPV, it also provides further reaffirmation for concentrated disadvantage in poor
neighborhoods which is more likely to contribute to IPV.
In addition, in the Sacramento Bee article discussed above Rubenstein (2012)
posited that disparities in regards to health may be connected to neighborhoods based on
recent research conducted by Valley Vision and local hospitals. In relation to race and
ethnicity, Rubenstein discussed how factors such as unsafe streets, poor transportation,
low education levels, and poor food choices tend to concentrate in poor neighborhoods
that are typically comprised of minorities because minorities typically live in low-income
areas (Rubenstein 2012). The evidence here advances the claim that there is a disparity
between races because of their social class position. Not only does this position affect
their health, it is also salient in relation to IPV and concentrated disadvantage. As seen
above by Werhman (2010), blacks are more likely to cluster in communities that
encompass concentrated disadvantage, which in turn increases the recidivism and
perpetuation of IPV. By contrast whites tend to be more privileged in that they have
better life chances because of their inherited opportunities although they may not be
conscious of this privilege. This concept is clearly outlined in Eduardo Bonilla-Silva’s
(2006) book Racism Without Racists when he says if color-blind readers were to accept
18
the fact that they belong to the racial group that is favored in America, a huge can of
worms would be opened with possible severe consequences. Bonilla says this is because
then those privileged would have to potentially accept the possibility that they did not
live in a meritocratic society, but rather that they live in a society that benefits some more
than others based on the color of their skin.
Overall, there are many explanations for intimate partner violence and the
differences between men and women’s victimization. Some explanations come from
classical theorists, some from modern theorists, and there are some who like to bring the
two together in order to explain IPV recidivism. The research looking into women as IPV
offenders is still in its infancy and requires further exploration. With the help of statistical
tools and data, answers can be explored, and the issue of IPV recidivism can be further
explained and understood.
As demonstrated in the text above, the following are seven hypotheses developed
in response to the literature that has been extensively collected and reviewed on intimate
partner violence recidivism.
Hypothesis 1: IPV arrest rates for males and females will be positively associated with
community concentrated disadvantage (Straus and Gelles 1986).
Hypothesis 2: IPV arrest rates (both male and female) will be positively correlated with
the total crime rate for communities within the Sacramento Police department’s
jurisdiction (Browning 2002).
Hypothesis 3: Victim report of the offense (versus report by third party) will be positively
associated with community concentrated disadvantage (Sampson 2012).
19
Hypothesis 4: IPV recidivism among female offenders will be positively associated with
community concentrated disadvantage (Lauritsen 2011).
Hypothesis 5: IPV recidivism among female offenders will be positively associated with
the number of prior IPV arrests (Merton 1957).
Hypothesis 6: African-American female offenders will have higher recidivism rates than
other racial/ethnic groups but not when controlling for other variables (Langan and Levin
2002).
20
CHAPTER 3
METHODS
Data and Samples
The master dataset for this study is composed of three subsets. Each subset
contains necessary pieces of information because each one provides very important data
that have the ability to come together in a way to enhance the knowledge and
understanding of intimate partner violence recidivism.
First a dataset consisting of 8,461 IPV arrests was processed by the District
Attorney’s (DA’s) office and “closed” between July 1, 1999 and December 18th, 2001. In
Sacramento County all of the arrests were forwarded to the District Attorney’s office and
this sample is therefore of all IPV arrests including those not filed for court processing by
the DA (e.g. Rejected by the prosecution by reason of insufficient evidence). The IPV
arrests were coded by prosecutors and legal interns in the DA’s office. Coding categories
included offender variables, victim variables, relationship variables, other case
characteristics, and outcome (case processing) variables (See appendix A for a list of
codes and categories).
Secondly, a dataset was developed from the Bureau of the Census 2000 zip code
data creating a “concentrated disadvantage” index composed of six different indicators
for thirty-nine of the forty-nine geographical zip codes in Sacramento County. Ten zip
codes were not included because of a small population size. The remaining thirty-nine
account for 98.99% of the county population. The final index is an average calculated by
adding the z scores and dividing by the number of indicators (six). The composite index
for concentrated disadvantage is the mean of standardized (Z) scores of six variables
21
drawn from the 2000 Census. The six variables are Median household income, percent
having less than a high school diploma, percent in poverty, percent of female headed
households, percent on public assistance, and percent of male unemployment. This type
of approach can be found within the literature on IPV, in which Lee also comprises a
disadvantage index from the Census that is, “constructed as the average of the
standardized scores of the percentage in poverty, the percentage unemployed, the
percentage over age 25 with less than a high school education, the percentage of the
population that is black, the percentage of female-headed households, and the degree of
spatial concentration of the county's poor residents” (Lee and Bartkowski 2004: 1014).
The present analysis is based on a total of 5,421 cases out of the original 8,461
cases because 3,040 cases did not have available information on zip codes. Comparison
of cases with and without zip code data suggest that sample bias, if present, is not strong
(See appendix B). Most of the variables fall between the low to moderate range except
for cohabitation (28%), spouse (12.7%), and victim’s support for prosecution (10.7%).
The third and final subset this study relies on comes from the California
Department of Justice (DOJ) who provided arrest histories for all 892 female arrestees in
the original sample of 8,461. A random sample of 450 cases was selected for detailed
analysis including IPV recidivism rates as well as number and type of non-IPV arrests.
Of these 450 cases, twenty-nine were removed owing to lack of data from the DOJ
leaving 421 cases for closer examination. When the index for concentrated disadvantage
is included in statistical models, this number is reduced by 123 cases (29.2%) leaving 298
cases (70.8%) for analysis.
22
Measures and Variables
Dependent variable. The dependent variable is intimate partner violence arrest
and recidivism as measured by re-arrest. For the purpose of this study, IPV is defined as
any form of physical or sexual abuse (including threats and stalking) that is inflicted on a
person with whom he or she is, or was, in an intimate partnership (See Appendix C for
list of offenses and penal code sections). In Appendix C the dependent variable was
dummy coded so that one equals yes and zero equals no.
Independent variable. The primary independent variable for this study is
community concentrated disadvantage with zip code of offense location serving as a
proxy variable for community. Lee and Bartkowski (2004) reinforced the usage of
concentrated disadvantage in the context of IPV and legitimized the reproduction of it in
this thesis. Concentrated disadvantage is comprised of measures indicative of
disadvantage and described previously (Parker 2008). The secondary independent
variable is race and ethnicity; which is also defined earlier. Control variables include
those offender, victim, offense and relationship variables previously discussed (see
Appendix A).
Data Analysis
The quantitative data is analyzed using SPSS. A correlation matrix for mean Z,
IPV arrest per 1000, IPV male arrest rate, and IPV female arrest rate was performed. This
research describes the relationship between IPV and other forms of criminal behavior as
indicated in the arrest histories. I have indicated the proportion of IPV recidivism arrests
that are felony or misdemeanors. A bivariate table was created, showing the relationship
23
between selected variables and recidivism rate with that variable and whether the
relationship was significant. Lastly, a logistic regression model was run showing the
relationship between selected independent and control variables and female recidivism.
24
CHAPTER 4
RESULTS
Descriptive Statistics
Table one presented the descriptive statistics of selected offender and victim
characteristics. It is important to note that out of the random sample of women selected,
over 56% had a prior arrest history. In particular, over 14% of the female offenders had a
prior domestic violence arrest; signifying IPV recidivism. In addition, in more than threefourths of the cases the victim reported the incident. Furthermore, the charges filed
against the offender were slightly more than half of all arrestees.
In reference to race and ethnicity, whites were underrepresented and African
Americans were extremely overrepresented (see Appendix D.). African Americans in
Sacramento County in 2000 represented 10% of the population while whites comprised
64%. (The 2000 Census did not break down racial categories by gender and therefore this
percentage covered both sexes.) The Census demonstrated that African Americans were
about three times greater than expected in the female offender IPV arrest population as
indicated in Table 1.
Inferential Statistics
Table two contained a bivariate relationship between selected case characteristics
and recidivism. First and foremost it illustrated how 22.1% of offenders recidivated
within this random sample. Offenders who had any prior arrests was significant at p<.001
with 28.6% recidivating. In addition, offenders who had charges filed against them
recidivated at 27.8% (p<.01).
25
Offenders who had a prior domestic violence arrest recidivated 50.8% of the time
(p<.001). Those who had a spouse, recidivated at a rate of 15.7% (p<.05). African
American suspects recidivated 28.3% of the time which was significant in relation to
non-African Americans (p<.05). Finally, suspects who were using substances recidivated
30.3% of the time (p<.05).
Table three was a correlation matrix that showed the relationship between
concentrated disadvantage and selected community and individual variables. The IPV
arrest rate for males and females were positively associated with community concentrated
disadvantage. The hypothesis was supported with a correlation coefficient of .876 (p<.01)
for males and .767 (p<.01) for females.
Table 1. Selected Offender and Victim Characteristics
Variables
Any Prior Arrest
Charges Filed
Co-Parents
Cohabitation
Filed as Felony
PO in Place
Prior DV Arrest
Spouse
Suspect Black
Suspect Latino
Suspect White
Suspect Other
Suspect Substance Use
Victim Injury
Victim Reported Incident
Victim Wants Arrest
N = 421
%
Yes
%
No
56.4 (220)
53.0 (223)
35.9 (151)
72.2 (304)
26.6 (59)
5.7 (22)
14.5 (61)
36.5 (140)
34.7 (145)
17.0 (71)
42.1 (176)
6.2 (26)
21.1 (89)
48.6 (197)
77.4 (233)
54.3 (228)
43.6 (170)
47.0 (198)
64.1 (270)
22.8 (90)
73.4 (163)
94.3 (367)
85.5 (360)
63.5 (224)
65.3 (273)
83.0 (347)
57.9 (242)
93.8 (392)
78.9 (332)
51.4 (208)
22.6 (68)
45.7 (192)
a. When cell sizes total less than 421 it reflects missing values on that variable
26
IPV arrest rates were not positively correlated with total crime rate for
communities within the Sacramento Police Department’s jurisdiction and victims who
reported the offense (versus report by third party) was not positively associated with
community concentrated disadvantage, nor was it significant.
Moreover, female arrest rates were positively associated with total SPD crime,
which was significant. When testing this hypothesis there was a slight problem because
we were unable to separate IPV from non-IPV crime within the data provided. However,
considering the strength of the correlation, it suggested it was not likely to be entirely
caused by the overlap.
Finally, there was no significance or correlation for IPV recidivism among female
offenders being positively associated with community concentrated disadvantage.
Table four analyzed the relationship between selected variables and IPV
recidivism using logistic regression (LR). Considering that all of the variables were
dummy coded I compared their respective influence on recidivism which is typically not
possible within LR. Accordingly, prior IPV was the strongest variable in the table.
Specifically, the odds of a prior IPV offender committing IPV was 3.585 times as great as
that of a person without prior IPV.
In another vein, it was not significant that African-American female offenders had
higher recidivism rates than other racial/ethnic groups. Thus, race did not matter in
predicting the recidivism rates.
27
Table 2. Bivariate Relationship between Selected Case Characteristics and
Recidivism (N=93)
%
Yes
Variables
Any Prior Arrest***
28.6 (63)
Charges Filed**
27.8 (62)
Co-Parents
26.5 (40)
Cohabitation
22.4 (68)
Filed as Felony
32.2 (19)
PO in Place
22.7 (5)
Prior DV Arrest***
50.8 (31)
Spouse*
15.7 (22)
Suspect Black*
28.3 (41)
Suspect Latino
16.9 (12)
Suspect White
19.9 (35)
Suspect Other
15.4 (4)
Suspect Substance Use*
30.3 (27)
Victim Injury
24.4 (48)
Victim Reported Incident
26.6 (62)
Victim Wants Arrest
25.0 (57)
Total sample size = 421 cases of whom 93 recidivated (22.1%)
%
No
13.5 (23)
15.7 (31)
19.6 (53)
20.0 (18)
25.2 (41)
21.5 (79)
17.2 (62)
26.2 (64)
18.7 (51)
23.1(80)
23.6 (57)
22.4 (88)
19.9 (66)
20.7 (43)
19.1 (13)
15.6 (12)
p< .05 = *
p< .01 = **
p< .001 = ***
It was also noteworthy to mention that filing charges against the offender
approached statistical significance at .089. This may indicate that those whom did not
have charges filed were less likely to recidivate than those who did.
Lastly, co-parenting and having a spouse were both significant. In particular, coparenting displayed a high significance even though it failed to do so in the bivariate
analysis (see Table 2). Specifically, “Spouse” was determined to be the suppressor
variable which can be defined as: “Statistical suppressor effects occur when the addition
28
of a suppressor variable to a regression equation improves the predictive utility of another
variable in the model” (Gaylord-Harden et. al. 2010: 843).
Table 3: Correlation Matrix Showing Relationship between Concentrated Disadvantage
and Selected Community and Individual Variables (a.)
Arrests Male
Female SPD
IPV
CDI
Who
Per
Arrest
Arrest
crime
Recid.
(b.)
Reported
1000
Rate
Rate
rate
Rate
Arrests Per
1
1000
Male Arrest
.994** 1
Rate
Female Arrest
.924** .885** 1
Rate
SPD Crime
.589** .570** .585** 1
Rate
IVP Recid.
.22
.238
.119
.138
1
Rate
CDI
.875** .876** .767** .444*
.249
1
Who Reported .039
.049
.012
.042
.019
.052
1
All cell sizes total to 39 except SPD crime (N=20) and IPV Recid. (Recidivism) rate
(N=36).
b. (CDI) = Concentrated Disadvantage Index
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
a.
By running a cross-tabulation between IPV recidivism and spouse and co-parenting, it
was evident that those who are married with children have a 19.3% chance of
recidivating. In contrast, those offenders who are not married and with no children had a
37.7% chance of recidivating. The significance level in this cross-tabulation was p<.031.
29
Table 4: Logistic Regression Analysis of Relationship between Selected Variables and
IPV Recidivism
B
S.E.
Sig. Exp. (B)
Co-parenting
0.751 0.275
**
2.118
Charges filed
0.464 0.273
1.59
Prior IPV
1.277 0.328
***
3.585
Spouse
-0.601 0.3
*
0.548
Suspect Hispanic a.
-0.582 0.404
0.559
Suspect other
-0.583 0.606
0.558
Suspect White
-0.292 0.297
0.747
Constant
-1.581 0.3
***
0.206
a. Reference Category is “Suspect Black”
p< .05 = *
p< .01 = **
p< .001 = ***
30
CHAPTER 5
DISCUSSION
Table 1 displayed the overrepresentation of African Americans by three times the
amount in the population of IPV arrestees. Given the representation of African
Americans within the Sacramento County population, one would expect this group to be
represented less. However, the trend here was consistent with the literature. For instance,
even though African Americans make up 13% of the general US population, they
constitute 28% of all arrests (Hartney and Vuong, 2009: 2). Considering minority
communities contain disproportionate numbers of individuals with lower socio-economic
status might explain the disparity within the African American community and their
higher population IPV and non-IPV arrests.
In reference to hypothesis 1, IPV arrest rates for males and females were
positively associated with community concentrated disadvantage. Here the data supported
the previously reviewed literature. For instance, Robert Sampson believes that there is a
higher risk of IPV arrests associated with people who live in areas that contain high
levels of concentrated disadvantage. Current and classical literature tends to focus
strongly on individuals and gender relations when explaining IPV. By contrast the
intention of this thesis has been to expand the paradigm of IPV recidivism to include
community level variables in order to more effectively explain intimate partner violence
and ultimately its reproduction.
The data confirmed hypothesis 2, which stated that IPV arrest rates (both female
and male) would be positively correlated with total crime rate for communities within the
Sacramento Police department’s jurisdiction. This was true for both males and females
31
within the Sacramento area. The correlation suggested that IPV was not a standalone
crime. In other words, often times multiple offenses can be tracked to offenders of IPV.
In addition, the same community factors that underline non-IPV crime also are very
likely shaping rates of IPV. Hypothesis 2 can further be substantiated by Browning as he
hypothesized in a similar sense, “Structural features of urban communities, concentrated
disadvantage, residential stability, and immigrant concentration are associated with the
prevalence of intimate homicide at the community level and involvement in a violent
partnership at the individual level” (Browning 2002: 837).
Hypothesis 3 proposed that victim report of the offense (versus report by third
party) would be positively associated with community concentrated disadvantage but was
not confirmed by this data set. Using “victim reports the offense” as a variable was
included in this study to test Robert Sampson’s concept of collective efficacy which
assumed that with lower collective efficacy, rates of victim reporting (versus non-victim)
would be higher in communities with high disadvantage. However, the reason for the
rejection of this hypothesis may have been due to men in lower class communities being
ashamed of reporting IPV. For instance, “such a man would fear being marginalized,
causing him to "hide" his experience from others” (Doyle, 1995; Kimmel,1994 within
Migliaccio 2001: 209). If concepts of masculinity are related to social class then some
men may not want to report this type of crime because of socialization into particular
cultural definitions of masculinity.
Hypothesis 4 was: IPV recidivism among female offenders will be positively
associated with community concentrated disadvantage, which was not confirmed with the
32
data analyzed. This could be explained by the operationalization of community
concentrated disadvantage. There are multiple ways to define this term which may
enhance the meaning of it and suggest a correlation with IPV recidivism. Another
explanation for this outcome is the sample size used and if expanded perhaps the
hypothesis could be validated. Therefore, further studies are recommended in order to be
conclusive.
The 5th hypothesis was IPV recidivism among female offenders will be positively
associated with the number of prior IPV arrests was confirmed using this data. The odds
of an offender with a prior IPV arrest committing IPV was 3.585 times as great as that of
a person without prior IPV. This finding was consistent with the literature and other
studies stating that recidivism and prior offending is the best predictor of offending in the
future (Kingsnorth 2006).
Finally, Hypothesis 6: African-American female offenders will have higher
recidivism rates than other racial/ethnic group when controlling for other variables, was
not supported in this study. Supplementary literature offer examples to suggest that
concentrated disadvantage was the overarching explanatory variable and that community
variables are far more important than race/ethnicity in the causal nexus of IPV (Benson
2006).
It is also very important to note that co-parenting was not significant in the
bivariate table but became so in the logistic regression when spousal relationship was
inserted into the equation. As noted in the results, married co-parents had recidivism rates
only half of unmarried co-parents. Marriage and children may also translate into higher
33
levels of interpersonal commitment thus influencing recidivism. In addition, the variable
“no charges filed” approached statistical significance when correlated with lower
recidivism rates. This may indicate that filing charges served as a deterrent effect.
34
CHAPTER 6
CONCLUSIONS AND FUTURE RESEARCH
Social science research is unavoidably subject to bias, flaws, and limitations
that can be improved upon with the development of new literature. The intention of this
thesis was to further the discussion of an important social issue in our society. Intimate
partner violence arrest and recidivism involves many variables that help predict the
causes and reproduction of this form of behavior. The variables themselves contain
limitations that have the ability to affect validity in research. For example, one of the
independent variables (concentrated disadvantage) is comprised of an index of six
variables; however, in order to test if this variable is really affecting IPV recidivism,
researchers must come up with more ways to operationalize it in order to increase validity
in the definition. Specifically, there may be more than six variables to fully define
concentrated disadvantage that would allow us to more successfully predict IPV
recidivism.
Another limitation of this study was using zip codes as a proxy for
neighborhood or community. It is difficult to fully conceptualize a neighborhood because
we are trying to measure communities not zip code numbers. Nonetheless, as other
studies have illustrated (Merolla, David et. al. 2011) zip codes are meaningful indicators
for community-level factors. In addition, the robust nature of the relationship between
IPV and concentrated disadvantaged suggests that zip codes are a meaningful if limited
measure of community.
An additional limitation of this study is that one-third of the arrest cases lacked
zip codes and therefore were not included either due to coder error or no zip code
35
reported by the arresting officer. However, we believe this has a limited impact on this
study considering the robust results and significance levels.
A closer look at the racial/ethnic representation of both offenders and victims
involved in IPV arrest and recidivism is also necessary. Specifically, future studies
examining the reason for the empirical data suggesting racial/ethnic disparities on this
subject are indispensable. For example, it would be valuable to explore these statistics
qualitatively so we could shed light on why the disparity in ethnic representation relative
to county population is occurring and what is causing it in more descriptive terms.
Finally, we are uncertain of the interpretation concerning concentrated
disadvantage and arrest rates. Particularly, we are unsure if concentrated disadvantage is
causing or only predicting higher arrest rates because there are so many other variables
related to committing IPV. As indicated in the literature, one of these variables may be
the absence of traditional male role models or female role models within the community
(Parker 2008).
In future studies, it would be meaningful to compare the recidivism rates of
both genders as this study did not. It is important to research both genders in comparison
to each other because it can increase the reliability of the data by either confirming
outcomes or not. Specifically, if we understand what is causing IPV among males and
females we will be able to enhance our understanding of IPV.
In conclusion, further research is essential to more effectively understand the
topic of IPV arrest and recidivism. Considering IPV is a form of behavior that often goes
36
unreported by both men and women, even in self-report studies as well as official data we
can never be certain how much of it we as researchers are able to capture quantitatively.
37
APPENDIX A
Categories and Codes
Variable
Any Prior Arrest
Charges Filed
Co-Parents
Cohabitation
Dating/engaged
DV Probation
Filed as Felony
Non DV Probation
Protective Order in
Place
Prior Incident DV
Spouse
Suspect Substance Use
Yes = 1
Yes = 1
Yes = 1
Yes = 1
Yes = 1
Yes = 1
Yes = 1
Yes = 1
Yes = 1
Yes = 1
Yes = 1
Yes = 1
Victim Supports Prosecution
Yes = 1
Victim Needs Medical Attention
Yes = 1
Victim Injury
Yes = 1
Victim Reported Incident
Yes = 1
Victim Wants Arrest
Yes = 1
a. DV: Domestic Violence or Intimate Partner Violence.
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
No = 0
38
APPENDIX B
Comparison of cases with and without known zip codes across selected
variables
Unknown
Known (N=5421)
(3040)
%
%
Variable
Any Prior Arrest
75.1
81.3
Charges Filed
75.4
80.4
Co-Parents
39.5
34.4
Cohabitation
78.9
50.9
Dating/engaged
43
39.3
DV Probation
15.9
18.9
Filed as Felony
24
26.4
Non DV Probation
30
35.6
PO in Place
10.4
18
Prior Incident DV
63.7
65.8
Spouse
38.9
26.2
Suspect Substance Use
28.2
21.2
Victim Supports Prosecution
46
56.7
Victim needs Medical Attention
9.5
9.1
Victim Injury
27.8
26.6
Victim Reported Incident
80.8
82.6
Victim Wants Arrest
71.5
76
a. DV: Domestic Violence or Intimate Partner Violence.
b. PO: Protective Order
39
APPENDIX C
Selected Penal Codes* related to Intimate Partner Violence
Penal Code
Section
242
243
262
262
273.5
273.5
273.6
422
646.9
646.9
646.9
Description
BATTERY SPOUSE/EX SPOUSE/DATE/ETC
BATTERY ON NONCOHAB FORMER
SPOUSE/DATING/ETC
RAPE SPOUSE BY FORCE/FEAR/ETC
RAPE OF SPOUSE UNDER CONTROLLED
SUBSTANCE/ETC
INFLICT CORPORAL INJURY ON SPOUSE/COHAB
INFLICT CORPORAL INJURY SPOUSE/COHAB:W/PRIOR
VIOLENT COURT ORDER TO PREVENT DV
THREATEN CRIME WITH INTENT TO TERRORIZE
STALKING
STALKING:TEMP RESTRAINING ORDER/ETC
STALKING W/PR SAME VIC W/IN 7 YR
*Arrest and Sort Codes provided by California Department of Justice. The DOJ
codes identify 48 separate penal code sections associated with Domestic
Violence. Rather than identify all 48, most of which are rarely charged, I have
identified only those most frequently employed by officers when making an
arrest. Unidentified codes available upon request.
40
APPENDIX D
2000 US Census Data – Sacramento County Race/Ethnic Demographics
White ................................................
783,240 (64.0)
Black or African American ..............
121,804 (10.0)
Hispanic or Latino …………….......
195,890 (16.0)
Asian ......................................……..
134,899 (11.0)
Some other race ...............................
119,937 (9.8)
41
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