Bias-Motivated Homicides: Toward a New Typology

City University of New York (CUNY) CUNY Academic Works

All Dissertations, Theses, and Capstone Projects Dissertations, Theses, and Capstone Projects

9-2018

Lindsey Sank Davis The Graduate Center, City University of New York

How does access to this work benefit ou?y Let us know!

More information about this work at: https://academicworks.cuny.edu/gc_etds/2813 Discover additional works at: https://academicworks.cuny.edu

This work is made publicly available by the City University of New York (CUNY). Contact: [email protected]

BIAS-MOTIVATED HOMICIDES: TOWARD A NEW TYPOLOGY

LINDSEY SANK DAVIS

A dissertation submitted to the Graduate Faculty in Psychology in partial fulfillment of the

requirements for the degree of Doctor of Philosophy, The City University of New York

2018

LINDSEY SANK DAVIS

Bias-Motivated Homicides: Toward a New Typology

Lindsey Sank Davis

This manuscript has been read and accepted for the Graduate Faculty in Psychology in satisfaction of the dissertation requirement for the degree of Doctor of Philosophy.

______Date Louis B. Schlesinger Chair of Examining Committee

______Date Richard Bodnar Executive Officer

Supervisory Committee:

Kevin L. Nadal

Chitra Raghavan

Sarah Craun

Ernest Drucker

THE CITY UNIVERSITY OF NEW YORK

iii

ABSTRACT

Bias-Motivated Homicides: Toward a New Typology

Lindsey Sank Davis

Advisor: Louis B. Schlesinger

Despite significant progress towards equal protection under the law for women, LGBT individuals, and people of color in the United States, hate crime remains a pervasive problem, and rates appear to have increased in recent years. Bias-motivated homicide – arguably the most serious form of hate crime – is statistically rare but may have far-reaching consequences for marginalized communities. Data from the Uniform Crime Reports and the National Crime

Victimization Survey have suggested that, on average, fewer than 10 bias-motivated homicides occur in the United States per year; however, data from open sources indicate that the rate of bias-motivated homicide is much higher when utilizing different criteria. In addition to this lack of clarity about prevalence, the dynamics of bias-motivated homicide remain understudied. The present study explores a non-random U.S. sample of 58 closed, adjudicated case files provided by the FBI’s Behavioral Analysis Unit for research purposes. The utility of the leading hate crime typology by McDevitt, Levin, and Bennett (2002) is examined by applying the typology to this sample of bias-motivated homicides, and interrater reliability of the typology is considered.

To address weaknesses in the typology, this study explores observable expressive and instrumental crime scene behaviors and their relationship to victim identity group membership,

provocation, and victim-offender relationship. Results provide preliminary support for a bias- motivated homicide typology based on victim identity and victim-offender interaction preceding the offense. Implications for prevention, offender rehabilitation, and law enforcement are discussed.

Keywords: Hate Crime, Bias Crime, Homicide, Sexual Orientation, Gender Identity,

Intersectionality, Racism

Acknowledgements

The data for this study were taken from closed, fully adjudicated state and local cases that were given to the FBI Behavioral Analysis Unit by law enforcement agencies around the United

States for the purpose of research. All identifiers, including names of victims, suspects, offenders, officers, departments, and correctional agencies, have been removed, and only aggregate data have been reported. The author would like to express her gratitude to the FBI

Behavioral Analysis Unit for coordinating this effort. The author’s opinions, statements, and conclusions should not be considered an endorsement by the FBI of any policy, program, or service.

Dedication

I would like to thank my research mentors, Dr. Schlesinger and Dr. Nadal, who have both been instrumental in the development of my identity as a researcher and my success as a student. I would also like to thank my committee members, Dr. Raghavan, Dr. Drucker, and Dr. Craun, for their contributions and generosity in donating their time toward this effort.

Additionally, I would like to thank my tireless teaching and research assistants: Caitlin Brady,

Justine Ganz, Jennifer Sobol, and Andrew Thompson. Their enthusiasm and dedication kept this project moving forward when the demands of graduate school were overwhelming. Similarly, I would like to thank my friends who provided encouragement and comic relief – particularly Dr.

Vikash Reddy and Dr. Kristin Davidoff, who helped keep me on track when I thought the wheels might fall off.

Finally, this would not have been possible without the unconditional love and support of my parents, Anne and Bruce, who exposed me to the realities of the world at an early age and empowered me to view myself of an agent of change.

vii

“Hate violence is motivated by social and political factors and is bolstered by belief systems which (attempt to) legitimate such violence…It reveals that the personal is political; that such violence is not a series of isolated incidents but rather the consequence of a political culture which allocates rights, privileges and prestige according to biological or social characteristics”

(Sheffield, 1995, p. 438).

“Hate crime is grounded in a culture of hate, not a subculture” (Perry, 2001, p. 33).

viii

Preface

The United States has been hailed as a “melting pot” of cultures - a nation built on the principles of freedom and diversity - yet expressions of prejudice are commonplace. Hate crimes, or criminal behaviors motivated by biases toward a particular identity group or groups, manifest in a variety of ways, ranging from low-level property crimes to mass homicide. Bias motives are often missed, uninvestigated, or underreported, leaving a large portion of victims’ stories untold. The present study takes a small step toward giving a voice to these neglected victims.

Lawrence (1999) noted that he preferred to use the term bias crime over hate crime in order to “emphasize that the key factor in a bias crime is not the perpetrator’s hatred of the victim per se, but rather his bias or prejudice toward that victim” (p. 9). For this reason, the term bias-motivated homicide will be the preferred term to indicate a homicide motivated, in whole or in substantial part, by the offender’s apparent prejudice toward a particular group or identity.

The terms bias crime and hate crime will be used interchangeably in reviewing the literature, as they are functionally equivalent for most scholars in the field.

Table of Contents

Abstract……………………………………………………………………………………….…..iv

Acknowledgments…………….….….….…..……………………………………………………vi

Dedication………………………………………………………………...……………………...vii

Epigraph…………………………………………………………………………………………viii

Preface……………………………………………………………………………………………ix

List of Tables………………………………………………………...………………………….xvi

List of Appendices………………………………………………………...……………………xvii

Chapter 1 – Homicide……………………………………………….…………………………….1

Homicide Victims………………………………………………….……………………...1

Homicide Offenders…………………………………………………………….…………2

Offense Characteristics……………………………………………………………………4

Homicide Classification Systems…………………………………………………………4

Crime Classification Manual………………………………………………...……5

Criminal enterprise homicide……………………….…………….……….5

Personal cause homicide…………………………………………..………6

Sexual homicide………………………………………..………………….6

Group cause homicide………………………………………………..……6

Uniform Crime Reports………………………………………….………………..7

Organized/Disorganized typology…………………………………………….…..7

Motivational spectrum………………………………………………………….…9

Sociogenic and environmental homicides……………………….………..9

Situational homicides…………………………………………………….10

Impulsive homicides…………………………...………………………...10

Catathymic homicides ……………………………………………………10

Compulsive homicides…………………………………………………...12

Homicides due to organic or psychotic disorders………………………..13

Expressive and instrumental offenses ……………………………………………13

Homicides Motivated by Bias ……………………………………………………………16

Chapter 2 – Hate Crime…………………………………………………………...……………..17

Hate Crime Legislation……………………………………………………………...…...17

Theories of Hate Crime………………………….…………………………..…………..19

Strain theory……………………………………………………………..………20

Geography and socioeconomic competition………………………………...…...20

Psychological processes…………………………………………...……………..22

Prevalence………………………………………………………………………...……...23

Offense Characteristics…………………………………………………………………..24

Offender Characteristics………………………………………………………...……….25

Hate groups……………………………………………………………………....28

Adolescent bias-motivated offenders…………………………………………….28

Female-perpetrated hate crime…………………………………………………...29

Offender Motivation…………………………………….……………………………….29

Targeted Groups………………………………………………………………………….31

Racial and ethnic crimes………………………………………………………....31

Anti-Black hate crime ……………………………………………………32

Anti-Latina/o hate crime…………………………………….……...……34

Anti-Asian hate crime ………………………...... ………………36

Anti-Arab hate crime……………………………………...... …..38

Anti-Native American hate crime…………………………...... 38

Anti-White hate crime………………………………………...... 40

Religious hate crimes………………………………………………...... 40

Anti-Jewish hate crime…………………………...………...... …40

Anti-Muslim (Islamophobic) hate crime…………………...... …42

Anti-LGBTQ hate crimes…………………………………...... ………...44

Anti-LGB hate crimes ……………………………...... …………45

Anti-transgender hate crimes………………………...... ……….49

Crimes against persons with disabilities…………………...... …………52

Misogynistic hate crimes………………………………...... …………..54

Hate crimes based on multiple marginalized identities…………...... ….56

Hate crimes against other groups………………………………...... …...57

Psychological Effects of Hate Crime……………………...... ………………….57

Bias-Motivated Homicide…………………………………...... ………………..60

Prevalence…………………………………………...... ………………..60

Offenders……………………………………………...... ………………61

Lynching……………………………………………………...... ……….61

Anti-LGBT homicides………………………………...... ….……………62

Problems with Existing Hate Crime Data……………………...... ……………...65

Gaps in the Literature……………………………………………...... …………..67

Chapter 3 – Current Study………………………………………………...... …………..70

xii

Hypothesis 1………………………………………………...... 72

Hypothesis 2………………………………………………………………...... 73

Hypothesis 3…………………………………………………………...... ……...74

Hypothesis 4…………………………………………………………...... ……...74

Hypothesis 5……………………………………………………...... …………...75

Hypothesis 6………………………………………………………...... ………...76

Chapter 4 – Methodology…………………………………………………...... …….…...77

Procedure…………………………………………………………...... ………77

Measures………………………………………………………...... …………….78

Sample………………………………………………………………,,,...... ………79

Statistical Analyses……………………………………………………...... ……80

Chapter 5 – Results…………………………………………………………...... ………82

Total Sample………………………………………………………...... ………..82

Offender characteristics……………………………………...... ……….82

Offense characteristics…………………………………...... …………...85

Victim characteristics……………………………………………...... …89

Typology data ……………………………………...... …………….…...90

Comparing Anti-LGBT and Racial/Ethnically Motivated Offenses…...... ……..91

Offender characteristics…………………………………………...... ….91

Offense characteristics……………………………………………...... 92

Victim characteristics………………………………………………...... 95

Intersectionality & Expressed Emotion…………………………...... …………..96

Victim-Offender Relationship & Expressed Emotion……………...... …………96

xiii

Provocation & Expressed Emotion……………...... ……………………..………97

Intergroup Difference in the Proposed Typology…………...... …………..……..98

Offender characteristics………………………………………...... …….98

Victim characteristics…………………………………….………...... ….99

Offense characteristics…………………………………………...... ……100

Chapter 6 – Discussion…………………………………………………………...... …...101

Bias-Motivated Homicides…………………………………………………...... 101

Offenders…………………………………………………………...... ….101

Offenders’ psychological processes………………………...... 102

Hate groups…………………………………………………...... 103

Victims……………………………………………...... …………………104

Offenses………………………………………………………...... ……..105

Type of Bias & Victim Identity…………………………………...... …………..106

The role of intersectionality…………………………………………...... 109

The Role of Provocation…………………………………………………...... ….109

The Role of Expressive and Instrumental Crime Scene Behaviors………...... …110

Utility of the McDevitt, Levin, & Bennett (2002) Typology ……………...... …111

Proposed Typology………………………………………...... …………………112

Type 1………………………………………………………...... ………113

Type 2 ………………………………………………………...... ….……114

Type 3 ………………………………………………………...... ….……114

Type 4 …………………………………………………………...... ……115

Implications for Prevention and Rehabilitation………………………...... ……..116

xiv

Implications for Law Enforcement………………………………….……...... ….117

Limitations………………………………………….……………...... ….………..119

Strengths………………………………………………….…….…...... ………….120

Future Directions………………………………………….…….…...... …………121

Tables……………………………………………………………….….……...... ……….122

Appendices…………………………………………………………….….……...... …….132

References……………………………………………………………………...... ………137

LIST OF TABLES

Table 1 Operational Definitions for Offender Variables…………………...... ……122

Table 2 Operational Definitions for Victim Variables…………………...... ….……123

Table 3 Operational Definitions for Situational Variables……………...... ………...124

Table 4 McDevitt, Levin, & Bennett (2002) Typology………………...... ………..125

Table 5 Proposed Bias-Motivated Homicide Typology………………….…...... ….126

Table 6 Intersectionality & Offense Variables………………………………...... …127

Table 7 Victim-Offender Relationship & Offense Variables……………...... ….....128

Table 8 Bias Type & Offense Variables………………………………...... ……...... 129

Table 9 Provocation and Offense Variables…………………...... …………………130

Table 10 Proposed Bias-Motivated Homicide Typology & Offense Variables...... …131

xvi

LIST OF APPENDICES

Appendix A Data Collection Sheet……………………………………….133

Appendix B Ad Hoc Expressive and Instrumental Violence Scales……...135

Appendix C Bias Indicators Observed in Sample...………………………136

xvii

Chapter 1

Homicide

According to the Douglas, Burgess, Burgess, and Ressler’s (1988) Crime Classification

Manual, homicide is defined as “the unlawful taking of human life” (p. 18). The Federal Bureau of Investigation (FBI), in conjunction with the United States Department of Justice (USDOJ), prepare an annual report of homicide statistics known as the Uniform Crime Report (UCR). The

UCR program defines murder as “the willful (nonnegligent) killing of one human being by another” (2014). According to UCR statistics (USDOJ, 2014), approximately 14,196 murders occurred in the United States in 2013. The homicide rate in 2013 was down 5.1% from the previous year and 12.1% from 2004, consistent with a downward trend over the past decade.

Similar trends have been observed by local law enforcement agencies, such as the New York

Police Department (NYPD, 2016, 2017) and the Chicago Police Department (2014). Although homicides tend to draw more media attention and more investigative resources, murder constitutes only 1.2% of violent crimes (USDOJ, 2014) and 0.6% of felony convictions annually

(Reaves, 2006).

Homicide victims. The FBI reports that in 2013, the majority (77.7%) of homicide victims were male (USDOJ, 2014). Among victims for whom race was reported, more than half were Black (51.7%), almost half were White (including White-identified Hispanic; 45.7%), and

2.5% were of another race. Victims most commonly fell into the 20- to 24-year-old age group (n

= 2,249), followed by 25- to 29-year-olds (n = 1,746), 30- to 34-year-olds (n = 1,497), 35- to

39-year-olds (n = 1,101), 17- to 19-year-olds (n = 911), and then tapering at both the higher and lower ends of the age spectrum. At the extremes, children and infants under 5 years comprised

413 victims; and adults 75 years and older comprised 263 victims.

Wolfgang’s (1958) classic study examined a sample of 588 murders committed in

Philadelphia between the years of 1948 and 1952, from which he concluded that victims may play some role in precipitating their own deaths. Most victims (87%) knew their killer and almost all (94%) were of the same race as their offenders. Similarly, in Luckenbill's (1977) sample, 41% of victims verbally provoked their killers with comments perceived as offensive,

34% of victims refused to comply with the killer's demands, and 25% of victims offended the killer with a physical behavior or nonverbal gesture. Whether or not the offense was intentional, all of the killers sampled perceived the victim's behavior(s) as personally offensive. In most cases, the victim is of the same race as the offender (e.g., USDOJ, 2014; Wolfgang, 1958), and

Meloy (2000) found that more than half of homicide victims sampled (53%) were under the influence of alcohol at the time of their deaths, consistent with Wolfgang’s (1958) findings.

Homicide offenders. In 2013, 89.3% of known homicide offenders were male

(USDOJ, 2014). Among offenders for whom race was reported, just over half were Black

(53.6%); 43.9% were White (including White-identified Hispanic); and 2.5% were of other races

– a distribution mirroring that of homicide victims. Most offenders were over the age of 18 years; however, the largest groups were 20- to 24-year-olds (n = 2,496), 25- to 29-year-olds (n =

1,541), and 17- to 19-year-olds (n = 1,227).

In Wolfgang’s (1958) study, about two-thirds of homicide offenders had previous convictions. This proportion appears to have increased over time. For example, the Chicago

Police Department (2014) reports that in 2011, 76.9% of identified homicide offenders had a prior arrest history. The USDOJ (2006) reported that 15% of homicide offenders convicted in large urban counties between 1990 and 2002 were on probation at the time of arrest, 13% were on pretrial release, and 8% were on parole. Just over half (58%) of those convicted of homicide

had at least one prior felony arrest. Half of convicted homicide offenders were under the age of

25, and 10% were under the age of 18. The mean age of convicted homicide offenders was 27 years.

Mental illness or instability of some kind is common among homicide offenders, although most are not severely mentally ill (Shaw et al., 2006). The major mental disorders appear to be associated with an increased risk of committing homicide (Schanda et al., 2004).

According to a study by Nielssen and Large (2010), one in 9,090 treated schizophrenics commit homicide annually, versus one in 629 untreated schizophrenics, which suggests that psychiatric treatment may reduce the risk of homicide among schizophrenics. Major depressive disorders have been found to be fairly common among homicide offenders who commit mass murders and school shootings (Arrigo, 2006), and in cases where the offender kills members of his own family (familicide), the offense is often preceded by a depressive disorder with psychotic symptoms (Malmquist, 1981). Similarly, in Meloy's (2000) study of sexual homicide offenders,

68% had a history of depression.

Substance use disorders are also common among homicide offenders (e.g., Eronen, Panu,

& Tiihonen, 1996; Fazel & Grann, 2004). A study of Swedish homicides (Lindqvist, 1986) revealed that both the offender and the victim were intoxicated at the time of the homicide in

44% of offenses. Ressler, Burgess, and Douglas's (1988) study of sexual homicide offenders indicated that 49% of the offenders reported consuming alcohol immediately prior to their offenses, and 35% reported using drugs prior to their offenses. Felthous et al. (2001) also found a high rate of alcohol intoxication among murder-suicide offenders. Alcohol dependence has also been associated with increased rates of recidivism among homicidal offenders (e.g., Eronen et al., 1996).

Offense characteristics. In Wolfgang’s (1958) sample, stabbing was the most common cause of death. This is no longer representative of causes of death today, as most murders are now committed using a firearm (e.g., Holmes & Holmes, 2001; USDOJ, 2010, 2013, 2014). For example, the Chicago Police Department (2014) reported that 83.4% of murders in Chicago in

2011 were committed using a firearm, most commonly a handgun. NYPD also reported that most homicides in 2017 were committed using a handgun (n = 153; 52%).

According to UCR data (USDOJ, 2014), the most common situation precipitating homicide was an argument of some kind (39.6%), followed by the commission of another felony

(24.4%). Most victims were killed by someone with whom they were previously acquainted

(55.9%); 13.6% were murdered by a family member. Only 10.9% were murdered by strangers.

It should be noted that the relationship between victim and offender was not identified for 45.5% of reported offenses. More than one-third of female victims (36.6%) were murdered by a husband or boyfriend.

Homicide Classification Systems

The legal system classifies homicides according to the offender’s intent and attempts to punish the offender accordingly. Black’s Law Dictionary refers to murder as a crime committed by “a person of sound mind and discretion” in which a human is killed “without any warrant, justification, or excuse in law” (Black & Nolan, n.d., para. 1). It requires that the offender act

“with malice aforethought,” which refers to having “a deliberate purpose or a design or determination distinctly formed in the mind before the commission of the act (Black & Nolan, n.d., para. 1).” Murders are further differentiated by degree. First-degree murder generally refers to a deliberate and premeditated killing or a killing committed during the commission of another felony, whereas second-degree murder generally refers to a killing that lacks

premeditation but occurs as a result of a desire to physically harm the victim (Black & Nolan, n.d.). A related lower level offense is manslaughter, “the unlawful killing of a human creature without malice, either express or implied, and without any mixture of deliberation whatever; which may be voluntary, upon a sudden heat of passion, or involuntary, in the commission of an unlawful act, or a lawful act without due caution and circumspection” (Black & Nolan, n.d., para. 1).

Meanwhile, homicide scholars have proposed a variety of classification systems or typologies to describe and organize homicidal behavior. Douglas et al.’s (1992/2013) Crime

Classification Manual and the UCR (USDOJ, 2014) each have their own categorization systems for criminal offenses, which are described below. Two well-known typologies based on the psychodynamics of the offenses are also discussed, though there are many more (for example, those by Tanay, Halleck, and others).

Crime Classification Manual. The Crime Classification Manual (Douglas et al.,

1992/2013) divides homicide into an exhaustive 24 types, organized within four overarching groups: criminal enterprise homicide, personal cause homicide, sexual homicide, and group cause homicide.

Criminal enterprise homicide. Criminal enterprise homicide refers to murder committed for material gain, including money, goods, territory, or favors. The victim(s) may or may not be known to the offender. Criminal enterprise homicides include: contract killing, gang- motivated murder, criminal competition (for control of a territory or market), kidnap murder

(often with a demand of ransom), product tampering, drug murder (murder committed to facilitate illegal drug trade), insurance-motivated murder (which may be for individual profit or

for organizational/commercial profit), and felony murder (which may be indiscriminately or situationally determined).

Personal cause homicide. Personal cause homicide refers to murders resulting from interpersonal aggression and emotional conflict, rather than material gain, sexual motive, or group sanctions. The victim(s) may or may not be known to the offender. Personal cause homicides include: erotomania-motivated killing, domestic killing (which may be spontaneous or staged), argument murder, conflict murder, authority killing, revenge killing, nonspecific motive killing, extremist murder (political, religious, or socioeconomic motives), mercy killers, hero killers, and hostage murder.

Sexual homicide. Sexual homicide refers to homicides with a sexual element, ranging from genital penetration to insertion of foreign objects. The victim(s) may be preselected or chosen by random chance when the opportunity presents. Sexual homicide offender may be classified as organized, disorganized, or mixed. These classifications are described in detail below (see Organized/Disorganized typology). They may also be classified as sadistic, indicating the offender’s arousal in response to the humiliation and helplessness of the victim.

Group cause homicide. Group cause homicide refers to homicides committed by pairs or groups of individuals with a shared ideology that sanctions a particular act of homicide.

Victims are often chosen purposefully due to their identities. This type of homicide includes: cult murder (committed by members of a religious or secular cult), extremists (political, religious, or socioeconomic motives), and group excitement homicides. The extremist subtype of group cause homicide includes individuals acting alone with the endorsement or support of a group sharing their ideology, as well as groups of two or more individuals working in concert.

This differs from the extremist murder subtype of personal cause homicide in that the personal

cause version of this offense is not endorsed by the offender’s in-group. Most bias-motivated homicides would likely fall into one of these two subcategories.

Uniform Crime Reports. For the purposes of the Uniform Crime Reports (UCR), the

FBI uses a different scheme, dividing homicides into five classifications: felony murder, suspected felony murder, argument-motivated murder, miscellaneous or nonfelony types (other than felony type murder), and unknown motives. Felony murder refers to homicides committed during the commission of a felony (e.g., rape, armed robbery). Suspected felony murder refers to homicides in which elements of a felony are present, but the felony aspect of the offense has not been confirmed. Argument-motivated murder refers to homicides that are “noncriminally motivated,” such as those that result from drug- or alcohol-fueled brawls or arguments about money or property. Miscellaneous or nonfelony types refers to any homicide with a known motivation that is not included in the previous three categories (e.g., child killed by babysitter).

Finally, unknown motive murder refers to homicides in which the motive is unknown or fits into none of the previous categories.

Douglas and colleagues (1992/2013) concluded that this classification system is inadequate, in that 40% to 50% of the homicide cases reported in the UCR each year are placed in the miscellaneous and unknown motive categories. They also note an increase in the percentage of crimes falling into these categories from the mid-1970s through the late 1980s.

Recent UCR data (USDOJ, 2014) reflect that this is a persistent issue in homicide reporting; in

2013, just over 50% of homicides recorded fell into the unknown circumstances or other than felony type: other – not specified categories.

Organized/disorganized typology. Hazelwood and Douglas’s (1980) commonly used typology separates offenders into two groups: organized and disorganized. This classification

system was originally used by Hazelwood and Douglas (1980) to describe a sample of sexual, or lust, homicides. It was later used by Ressler, Burgess, and Douglas (1988), whose findings were convergent with Hazelwood and Douglas (1980). Although this typology has typically been used to describe sexual or serial homicides (which are, themselves, predominantly sexual homicides [e.g., Holmes & Holmes, 2001; Schlesinger, 2007]), the Crime Classification Manual

(Douglas et al., 1992/2013) uses this terminology to describe a spectrum of crime scene features and offender behaviors that are indicative of the offender’s level of criminal sophistication.

These features may be applicable to a wide variety of criminal behaviors, including homicides without a sexual motive.

The organized killer possesses average or above-average social skills but socializes only with those whom he deems fit (Hazelwood & Douglas, 1980). He typically plans his crimes, carefully selects his targets, and executes his crime according to plan, unless interrupted by unexpected circumstances. In a sexual homicide, an organized offender is more likely to have sexual intercourse with a living victim than engage in post-mortem sexual activity. The organized offender fantasizes about his crime and usually attacks following a precipitating life stressor. A crime scene on the organized end of the spectrum provides little or no forensic evidence and demonstrates the offender’s ability to control his victim (Douglas et al.,

1992/2013). The offender is likely to bring a weapon of choice to the scene and take it with him after the offense.

On the other hand, the disorganized offender is typically someone who has social skill deficits which have kept him from interacting effectively in society. In a sexual homicide, this offender tends to kill in a frenzied manner, without planning (Hazelwood & Douglas, 1980). He often leaves forensic evidence at the scene, including his murder weapon. The disorganized

offender tends to offend near his home or comfort zone. A crime scene on the disorganized end of the spectrum shows a lack of control over the victim and few or ineffective efforts to prevent apprehension (Douglas et al., 1992/2013).

Motivational spectrum. Other researchers (e.g., Revitch, 1977; Revitch & Schlesinger,

1981; Schlesinger, 2004) have argued that homicide – as well as other criminal offenses – must be classified rationally in order to understand all of the relative psychopathological, psychodynamic, and prognostic factors associated with a particular instance of homicide. The clinically derived motivational spectrum developed by Revitch and Schlesinger (1978, 1981) organizes such offenses based on the dynamics of the act itself. On one end of the spectrum lie crimes motivated by purely external, or sociogenic, factors and on the other end lie those motivated by purely internal, or psychogenic, factors. Five categories of homicide have been differentiated: (1) sociogenic or environmental, (2) situational, (3) impulsive, (4) catathymic, and (5) compulsive.

Sociogenic and environmental homicides. While laypersons often presume that homicide is primarily irrational and the result of mental illness, many crimes are the product of external or social influences rather than psychological forces within the individual. For example, contract killings - murders typically ordered by individuals in criminal organizations - may be carried out for the purpose of material gain, to obtain membership in a criminal organization, or in response to threats of harm against one’s family or person. Terroristic murders are another type of sociogenic crime, commonly influenced by religious or political ideologies. Such offenders can be expected to continue to commit similar criminal offenses as long as they remain under the influence of those forces that stimulated the initial offense. Experimental laboratory research, such as the classic studies conducted by Milgram (1963) and Zimbardo (Haney, Banks, & Zimbardo, 1973), as well as real-world observations (e.g., Zimbardo, 2007) have consistently shown that external forces have

the capacity to influence individuals to commit ego-dystonic acts that they might otherwise have never considered.

Situational homicides. Situational homicides are violent reactions to stressful circumstances and may be committed by individuals with or without psychopathology (Schlesinger,

2004). The prototypical situational homicide is the biblical murder of Abel by his brother Cain. As the story goes, Cain slew Abel suddenly, in a fit of jealousy and rage. Situational homicides are characterized by their spontaneity and may lack the features of a premeditated crime. Murders resulting from the escalation of arguments and inebriated brawls are most commonly situational offenses and constitute at least 26% of homicides reported in 2012 (USDOJ, 2013).

Impulsive homicides. Individuals with poor impulse control often find themselves in a variety of disciplinary and legal difficulties throughout their lifetimes due to uncontrolled expressions of hostility and anger. As an example of this type of offense, Schlesinger (Davis &

Schlesinger, 2012) cites one of his own clinical cases, in which a 25-year-old man impulsively strangled a woman after having sexual intercourse with her, because she accused him of rape.

Catathymic homicides. Catathymia is a psychodynamic concept that was initially employed to explain delusional content in psychotic patients (Maier, 1912). The term derives from the Greek kata and thymos, which loosely translates to “in accordance with emotions.” Maier

(1912) postulated a psychodynamic explanation for the content of psychotic delusions; although the content may seem bizarre, he believed that the delusions are actually reflections of deep emotionally charged conflicts. The patient’s hidden fears and desires come to the surface in the form of his delusions.

The term was introduced into the field of criminal behavior by Wertham (1937) to describe unprovoked, isolated episodes of severe violence lacking an organic basis. Similar to Maier (1912),

Wertham attempted to explain a phenomenon that appeared inconsistent with the overall character of the individual. He described a five-stage catathymic process (Wertham, 1978):

1. An initial thinking disorder, which follows an original precipitating (or traumatic)

circumstance;

2. Crystallization of a plan, when the idea of a violent act emerges into consciousness. The

violent act is seen as the only way out. Emotional tension becomes extreme, and

thinking becomes more and more egocentric;

3. Extreme emotional tension culminating in the violent crisis, in which a violent act

against oneself or others is attempted or carried out;

4. Superficial normality, beginning with a period of lifting of tension and calmness

immediately after the violent act. This period is of varying length, usually several

months; and

5. Insight and recovery, with the reestablishment of inner equilibrium (p. 166).

Wertham (1937, 1978) points out that the offender may not reach the fifth stage, in which case he will return to the second stage and repeat the process, eventually committing a crime that bears some symbolic relationship to the original crime. Revitch (1977), Revitch and Schlesinger

(1981), and Schlesinger (2004, 2007) further differentiated two types of catathymic homicides: acute and chronic. Catathymic homicides of both acute and chronic types derive from a breakthrough of underlying sexual conflicts, typically deep feelings of sexual inadequacy.

In the chronic catathymic process, a feeling of frustration, helplessness, or inadequacy builds over a period ranging from a day to several years (Schlesinger, 2004). The crime may be more planned and organized, often the product of long periods of rumination. The offender may experience depressive mood or psychotic-like distortion prior to or during the murder; he may

express to others, either directly or indirectly, that he feels as though he is about to explode

(Schlesinger, 2007). The typical victim of a chronic catathymic homicide is a current or former romantic partner; at times, it is a relative stranger with whom the subject has become obsessed and possibly stalked (Meloy, 1992).

The acute process is marked by a sudden, unprovoked murder triggered by the eruption of an overwhelming emotion attached to underlying conflicts, often related to sexual inadequacy

(Schlesinger, 2004). The victim is typically a stranger, often a female, possibly representing the offender’s mother in some cases. The incubation period lasts only seconds, and the crime is unplanned and disorganized. These homicides generally map onto Ressler et al.’s (1988) classification of “blitz attack”. These crimes are not the result of paranoid delusions or the influence of substances, and the offender is often unable to explain his behavior and may have limited recall of the events that transpired.

Compulsive homicides. Compulsive homicides stem from internal, psychogenic forces and require little or no external provocation. Homicidal fantasies usually precede these offenses, and the killing of the victim is sexually arousing in itself as part of the offender's sexual arousal pattern

(Schlesinger, 2007, 2008). The offender's behavior at the crime scene tends to involve sexually gratifying ritualistic behavior, such as provocative positioning of the corpse or insertion of foreign objects (e.g., Schlesinger, Kassen, Mesa, & Pinizzotto, 2010). Repeated homicides are encouraged by the sexual stimulation and gratification of the first offense. Such a compulsion is reflected in serial killer William Heirens’ plea to law enforcement: “Catch me before I kill more; I cannot control myself” (Keppel & Bimes, 2009, p. 22). Frequently, these compulsive homicide offenders have a history of destructive firesetting or cruelty toward animals and humans (Davis &

Schlesinger, 2012; Petersen & Farrington, 2007; Ressler, Burgess, Hartman, & Douglas, 1986;

Schlesinger, 2001).

Homicides due to organic or psychiatric disorders. A class of homicides considered distinct from this motivational spectrum are those homicides that are a direct outgrowth of a psychiatric disorder or state, such as a psychotic condition, an organic condition, or intoxication.

An offender may be responding to command hallucinations that may direct him to hurt the victim.

The offender may also be disinhibited by the intoxicating effects of a substance, as is reflected in

Meloy’s (2004) homicide sample, in which just over half of offenders were under the influence of drugs or alcohol at the time of the offense.

Expressive and instrumental offenses. Another classification system (Feshbach, 1964) that refers to the concept of offender motivation differentiates criminal acts as either expressive or instrumental (or along a spectrum in between these two poles). Expressive offenses are often reactions to intense emotions and serve to discharge or demonstrate these emotions. There may be no secondary gain beyond harming the victim. For example, a man who murders his lover when he discovers she has been unfaithful to him would be an example of an expressive offender; his offense brings him no secondary gains (money, property, sex, etc.), but discharges his rage and hurts the victim in response to his feelings of being hurt by her. On the other hand, instrumental offenses are oriented toward an external goal that is beyond the offense itself. The instrumental offense is a means to another end. For example, a man who murders a witness to prevent her from testifying against him in court would be an example of an instrumental offender; the violence helps the offender to achieve his goal of avoiding incarceration for a prior offense.

Feshbach (1964) suggested that aggressive behavior may be divided into instrumental acts and drive-mediated acts. Instrumental aggression “is directed toward the achievement of

nonaggressive goals” and includes only “behaviors producing injury which are motivated by a desire for some outcome other than injury to an object” (p. 258). Meanwhile, aggressive drive- mediated behavior refers to acts produced by an aggressive impulse. Aggressive drive-mediated acts could be further differentiated into an expressive type and a hostile type. According to

Feshbach (1964), expressive aggression is characterized by the desire to “hit” the victim, and hostile aggression is characterized by the desire to “hurt” the victim (p. 257). Hostile aggression was thought to be preceded by exposure to punishment and triggered by an immediate threat to the offender’s self-esteem.

A relationship between expressive crime scene behaviors and the relationship between victim and offender has been explored and supported in the literature. For example, Green

(1981) found that matricides (murders of one’s mother) were significantly more likely to feature overkill (excessive wounding) than were other types of homicide. Similarly, Mass, Prakash,

Hollender, and Regan (1984), looking at a small sample of parricide and matricide cases, posited a positive, graded relationship between the severity of injury to the victim and the closeness of the relationship between the victim and offender. Daly and Wilson (1988) found that manual violence and the use of blunt force were indicative of reactive, unplanned offenses between an offender and victim who have previously had a close relationship. Cornell and colleagues (1996) similarly characterized expressive offenses as impulsive, undercontrolled, and frenzied attacks that occur when the offender feels provoked by the victim.

More recently, Salfati and Canter (1999) found that unplanned, emotionally expressive homicides were often committed using a weapon found at the scene. Furthermore, they found that injury to the head or face was characteristic of these offenses; this has been posited as a possible depersonalization of the victim by a familiar offender. Salfati (2000) conceptualized

expressiveness and instrumentality as features of the role the victim played relative to the offender.

Salfati (2000) suggested that instrumental offenders are more likely to steal their victim’s property or engage in sexual activity with their victims. Salfati (2003) reported that multiple wounds and wounds spanning several areas of the body are more likely to indicate an intimate relationship between offender and victim.

Last and Fritzon (2005) studied several crime scene features observed in a sample of 82 homicides. They determined that crime scene variables were indicative of the relationship between the victim and the offender; most predictive of a close relationship was the presence of multiple wounds to a single area of the body. Close, familial relationships were characterized by offenses in which the offender used a weapon found at the scene, excessively wounded the victim, injured the victim’s face, inflicted multiple wounds to the same region of the victim’s body, or committed the offenses using only their hands. These results mirror, in some ways, non- homicidal domestic assaults, in which wounds to the victim’s head, face, and neck have been found to be common (Sheridan & Nash, 2007).

On the other hand, Trojan and Krull (2012) found that gunshot wounds are more indicative of a nonintimate relationship between offender and victim. They again stated that offenders who know their victims are more likely to use a weapon from the crime scene and/or inflict death via blunt force trauma. Fox and Allen (2013) suggested an instrumental-expressive continuum along which crimes may be arranged based on the presence or absence of significant crime scene features. They observed that firearms were most commonly associated with instrumental offenses, while knives were most commonly associated with expressive offenses that were defensive in nature, and blunt objects and hands are most commonly associated with expressive offenses that are unprovoked, or offensive, in nature.

Most recently, Alvarez Cussin (2017) examined various patterns of injury in homicidal violence and their relationship to the victim-offender relationship. Using a sample of adjudicated homicide cases spanning domestic, sexual, and felony homicides, she found that the use of a single weapon to inflict moderate to excessive wounding was indicative of an intimate or domestic relationship between victim and offender. Furthermore, multiple facial injuries were indicative of an intimate relationship between victim and offender.

Homicides Motivated by Bias

In the American legal system, bias-motivated homicides are conceptualized as mostly internally motivated; thus, to make a statement against hate, the Violent Crime Control and Law

Enforcement Act (1994) included a provision to subject bias-motivated homicide offenders to greater penalty than would be applied in situational or environmentally driven homicides.

However, a review of the literature on hate crime suggests that these crimes are not entirely hate- driven and may have strong environmental, as well as situational, triggers that evoke the offender’s criminal behavior. As Perry (2001) and other scholars have noted, hate crime has not been studied extensively by psychologists or criminologists, and even less attention has been paid to bias-motivated homicides specifically. First, these crimes must be situated in the overarching hate crime literature.

Chapter 2

Hate Crime

The FBI defines hate crimes as “criminal offenses motivated, in whole or in part, by the offender’s bias against a race, religion, disability, sexual orientation, ethnicity, gender, or gender identity” (USDOJ, 2015, p. 4). While this definition makes the murky concept of hate crime easier to operationalize, Perry’s (2001) definition better contextualizes these offenses, stating that hate crime is “a mechanism of power intended to sustain somewhat precarious hierarchies, through violence and threats of violence (verbal or physical). It is generally directed toward those whom our society has traditionally stigmatized and marginalized” (p. 3). Similarly, Wolfe and Copeland (1994) describe hate crime as “violence directed toward groups of people who generally are not valued by the majority society, who suffer from discrimination in other arenas, and who do not have full access to remedy social, political, and economic injustice” (p. 201).

Perry (2001) and other hate crime scholars have theorized that hate crime constitutes an attempt to establish control over the “wayward” Other – the outgroup who has ventured beyond the accepted societal roles, either by trying to assert rights not commonly afforded to them or by displaying their difference openly. Like other forms of discrimination, hate crime is seen as a way to reinforce social hierarchies that privilege the dominant groups: Whites, heterosexuals,

Christians, Americans, and cisgender males (self-identifying men who were assigned male at birth). As such, some sociologists (e.g., Grattet & Jenness, 2001) have conceptualized hate crimes as responses to the Black, women’s, and LGBTQ civil rights movements of the last century.

Hate crime legislation. The U.S. Civil Rights Act of 1968 (2013) called for the prosecution of any person who "willingly injures, intimidates or interferes with” another

individual who is attempting to exercise his or her civil rights (e.g., attending school, patronizing a public place, applying for employment, serving as a juror, voting). The act was signed into law following the assassination of Black civil rights leader Martin Luther King, Jr. and the ensuing riots. The Fair Housing Act (Title VIII) and the Indian Civil Rights Act were also included at this time. The Fair Housing Act decreed that landlords, property owners, and financial institutions may not discriminate against any person seeking housing based on their race, color, religion, sex, disability, familial status, or national origin. The Indian Civil Rights Act declared that Native Americans, while self-governing, must have equal protection under the law, access to due process, and freedom of religion, effectively ensuring certain civil rights for all Native

Americans. The most notable effect of this legislative package was to protect Africans and

African-Americans from violence and harassment by Whites in the post-desegregation period, although it also provided federal protection for other racial, ethnic, and religious minorities.

In 1990, the federal Hate Crime Statistics Act (HCSA) decreed:

[T]he Attorney General shall acquire data, for the calendar year 1990 and each of the

successive four calendar years, about crimes that manifest evidence of prejudice based on

race, religion, disability, sexual orientation, or ethnicity, including where appropriate, the

crimes of murder, non-negligent manslaughter, forcible rape, aggravated assault, simple

assault, intimidation, arson, and destruction, damage or vandalism of property (para. 1).

This act has been cited as the first official use of the term hate crime (Turpin-Petrosino, 2009b).

The Hate Crime Sentencing Enhancement Act appended to the Violent Crime Control and

Enforcement Act of 1994 required the U.S. Sentencing Commission to enhance penalties for bias-motivated crimes committed on the basis of “the actual or perceived race, color, religion, national origin, ethnicity, gender, disability, or sexual orientation of any person” (Henry, 2009, p.

193).

The most recent hate crime legislation – the Matthew Shepard and James Byrd, Jr. Hate

Crimes Prevention Act – was signed into law by President Barack Obama in 2009 (USDOJ,

2015). In response to the horrific bias-motivated murders of a young gay man named Matthew

Shepard and a young Black man named James Byrd, Jr., this act expanded the federal government’s rights to allow prosecution of violent hate crimes motivated by a victim's actual or perceived gender, sexual orientation, gender identity, or disability status, but only those crimes that affect interstate or foreign commerce, crimes for which the state has requested federal aid or oversight, or those in which “a prosecution by the United States is in the public interest and necessary to secure substantial justice.” The act makes specific reference to bias-motivated violence as “deeply divisive” and acknowledges the eradication of racially motivated violence as a means of restoring justice in the wake of the history of slavery in the United States. This act was an expansion of the Civil Rights Act of 1968, removing the prerequisite that the victim be engaging in a federally protected activity and giving the federal authorities jurisdiction over hate crime investigations that local authorities choose not to pursue. Additionally, $5 million of funding were provided each year for fiscal years 2010 through 2012 in order to help state and local agencies pay for the investigation and prosecution of hate offenses. The Matthew Shepard and James Byrd, Jr. Hate Crimes Prevention Act also expanded on the Hate Crime Statistics Act by requiring the FBI to track crimes based on gender and gender identity.

Theories of hate crime. Several theories have been put forth to describe the etiology of the hate crime phenomenon, most of which have been developed by sociologists and criminologists. Some theorists suggest that hate crime is driven by economic concerns (e.g.,

Merton, 1957); others believe it is driven by proximity and demographic trends (e.g., Green,

Strolovitch, & Wong, 1998). Psychologically, hate crime offenders also use certain cognitive processes to explain their behavior and preserve their self-image (Byers, Crider, & Biggers,

1999; Sun, 2006; Sykes & Matza, 1957).

Strain theory. Strain theory, originally devised by Merton (1957), describes criminal behavior as the result of unequal access to the so-called “American dream”, a set of societally proscribed goals (e.g., education, employment, property, family). The frustration with and disengagement from society that ensues is referred to as anomie. As opposed to frustrations that individuals experience on the personal level, strain theory proposes that criminal behavior arises from a societal structure that prevents subsets of the population from achieving their aspirations via prosocial avenues and thus urges individuals to disregard social rules and norms in pursuit of their goals.

Merton (1957) proposed five types of anomic individuals based on mode of response: conformists, innovators, ritualists, retreatists, and rebels. Hate crime offenders might be described as fitting into the innovators category, as they are devising a new way to achieve their ends by going outside of societal norms (i.e., committing criminal offenses). They might also be described as fitting into the rebels category, as hate crime offenders are acting out against some of the supposed core values of the United States, including freedom, equality, and diversity.

However, as Perry (2001) states, strain theory fails to fully explain the phenomenon of hate crime, even if only that it is most often the victims - rather than the perpetrators - of these crimes who are in the most marginalized positions in American society.

Geography and socioeconomic competition. Another group of sociological theories involves geographic proximity and socioeconomic competition among identity groups. As

Dozier (2002) states,

Some of the most virulent, violent, and intransigent forms of hate surface when

competing groups are trapped together in the same geographical area…Similarly, some of

the most extreme forms of racism and violent hatred in America have emerged from the

multiple ethnicities of the struggling inner cities and from prisons, with their volatile

racial mix (p. 21).

The defended neighborhoods theory of hate crime (Green, Strolovitch, & Wong, 1998) indicates that higher rates of racially motivated hate crime will occur in areas where Whites are the dominant racial group demographically. Cross-burning and other forms of intimidation are intended to discourage minority group members from moving into predominantly White neighborhoods. As Bronski (2011) noted, hate crime waves have often been precipitated by an influx of immigrants or some other marginalized identity group into an area that has not been predominated by that group historically. For example, a steep uptick in crimes against Asians and Hispanics was observed following their influx into California. Research on hate crime patterns in New York City (Green, Glaser, & Rich, 1998) has also indicated that higher levels of hate crime offending are often observable in areas where marginalized groups are increasing in size.

Several explanations for this behavior have been suggested. White residents may have exaggerated fears regarding economic competition with racial minorities, and there is a tenuous connection between economic conditions and hate crime rates (Green, Glaser, & Rich, 1998).

Blalock’s (1967) group threat theory posits that as marginalized groups grow in size relative to the majority group, they threaten to diminish the majority group’s economic and political power.

Meanwhile, Suttles (1972) suggests that some Whites have a sentimental attachment to the

original racial composition of their communities and may use criminal means in an effort to maintain this structure.

Psychological processes. At the individual psychological level, it has been postulated that hate crime offenders commonly use neutralization techniques, whereby injury to a certain target is rationalized and justified (Byers, Crider, & Biggers, 1999; Sun, 2006; Sykes & Matza,

1957). Sykes and Matza (1957) state that neutralization separates a criminal act from the offender’s personal responsibility for the act. These mental tactics allow offenders to view their victims as deserving of the “punishment” they suffer (Levin & McDevitt, 1993).

In a study of offenders who engaged in anti-Amish activities (Byers et al., 1999), several cognitive processes were apparent. First, offenders endorsed negative stereotypes about the

Amish. Their ignorance about Amish culture was evident. Second, offenders did not deny their actions, but frequently denied that their actions resulted in injury. They viewed their behavior as harmless fun. Third, offenders suggested that their victims “had it coming to them” or deserved to be victimized. One offender stated that the annoyances generated by Amish buggies meant that they deserved to be victimized. Fourth, offenders engaged in dehumanization of their victims – by denying the victim’s human value, the social and legal impact of the behavior is also denied. As one offender stated, “When we were doing things, we didn’t think of them as people…Their social status was so far below ours, because they weren’t even actual acting humans” (Byers et al., 1999, p. 87). Fifth, offenders justified their behavior as acts of loyalty to their groups. They described victimization of the Amish as a male bonding ritual for non-Amish

White men. As a result, they did not report each other to the police and expected the same treatment in return. Sixth, the offenders redirected their attention away from their own behavior onto the victims or onto those who condemned their behavior (e.g., law enforcement). They

attempted to condemn their condemners by questioning or discrediting their moral standing. For example, one offender pointed to local law enforcement’s apparent mistreatment of the Amish and suggested that law enforcement officials had probably engaged in similar anti-Amish acts when they were younger. Finally, some offenders attempted to neutralize their responsibility by externalizing blame. One offender cited his upbringing as the cause of his hateful behavior. All of these cognitive processes helped offenders to preserve their positive self-image.

Prevalence. In 2013, 5,928 hate crime incidents were reported to the FBI (USDOJ,

2014). Of these incidents, all but six were determined to have been motivated by a single source of bias (e.g., race only). Nearly half (48.5%) of reported incidents were motivated by racial bias.

The next leading motivation was sexual orientation bias (20.3%), followed by religious bias

(16.8%) and ethnicity bias (11.3%). Crimes based on bias against disabilities comprised 1.3%, crimes based on gender identity bias comprised 0.5%, and crimes based on gender bias comprised 0.4%.

The Bureau of Justice Statistics’ (BJS) National Crime Victimization Survey (NCVS) has provided an additional source of data on hate crimes since 2003. Unlike the UCR, the NCVS measures crimes perceived to be bias-motivated by either law enforcement or victims and comprises the results of interviews of a nationally representative sample of households in the

United States. Because it is based on interviews, it necessarily excludes bias-motivated homicides. In 2012, 162,940 persons over the age of 12 were interviewed and 293,790 hate crimes were reported (Wilson, 2014). Most hate crimes (89.7%) were reportedly violent in nature, and at least 24% involved the use of a weapon. Hate crimes accounted for 4.2% of all reported violent victimizations in 2012. The number of hate crimes reported in the NCVS remained fairly stable from 2004 to 2012.

Offense characteristics. In 2013, 82% of hate crimes reported in the UCR were directed at individuals (USDOJ, 2014). Compared to crimes without a bias motive, hate crimes are more likely to be violent in nature, and they appear to have become increasingly violent over the last

10 years (e.g., Levin, 1999, 2009; USDOJ, 2012, 2014). Compared to other crimes, hate crimes more often involve overkill, or excessive violence; multiple offenders and co-conspirators; attacks on stranger victims; and serial offending (Levin & Fein, 1998; Levin & McDevitt, 1993).

According to the USDOJ (2012), weapons were used in at least 24% of violent hate crimes, about as frequently as they were used in violent crimes without a hate motive during the same time period. About 20% of violent hate crimes reported in the 2012 NCVS (USDOJ, 2013) resulted in physical injury to the victim, a proportion similar to that observed in violent crime that was not bias-motivated; however, bias-motivated assaults have been found to be more likely to result in serious injury to the victim (e.g., Messner, McHugh, & Felson, 2004). National

Incident-Based Reporting System (NIBRS) data from 2005 to 2010 show that 6.5% of bias crimes involve serious injury or death, compared to 5.7% of non-bias incidents (Lyons &

Roberts, 2014).

Levin and McDevitt (1993) surmised that hate crimes are characterized by four main features: excessive violence, stranger victimization, interchangeability of victims, and multiple offenders working together. The presence of multiple offenders is also reflected in the crimes reported in the Southern Poverty Law Center’s Intelligence Report (SPLC, 2015). According to

UCR and NCVS data, about 37% of violent hate crimes are committed by someone known to the victim, and about half of nonviolent hate crimes are committed by someone known to the victim

(e.g., Langton & Planty, 2011). NIBRS data indicates that hate crimes are significantly more likely to be directed at strangers than towards individuals known to the offender (Lyons &

Roberts, 2014). Nearly all surviving hate crime victims report that offenders used slurs or derogatory language toward them during the commission of the crime (Langton & Planty, 2011).

According to the UCR (USDOJ, 2014), most hate crime incidents reported in 2013

(31.5%) occurred in or near residences. More than 18% occurred outdoors on roads or sidewalks; about 8% occurred at schools or colleges; about 6% occurred in parking lots or garages; and 3.5% percent took place in places of worship (e.g., churches, temples). Hate crimes have become a growing concern on college campuses and appear to occur with greater frequency at predominantly White colleges and universities with large fraternity systems (Van Dyke &

Tester, 2014).

Offender characteristics. Hate crime offenders are typically male (e.g., Castle, 2009;

Dunbar, 2002; Dunbar, Quinones, & Crevecoeur, 2005; Harlow, 2005; Lyons & Roberts, 2014;

Strom, 2001), young (e.g., Cotton, 1992; Levin & McDevitt, 1993), and White (e.g., McDevitt,

1996). USDOJ statistics (2014) indicate that 32% of hate crime offenses reported in 2013 were committed by individuals under the age of 18, and that 52.4% of offenders were White.

According to Perry (2001), “Bias-motivated crime provides an arena within which white males in particular can reaffirm their place in a complex hierarchy and response to perceived threats from challengers of the structure – especially immigrants, people of color, women, and homosexuals” (p. 2).

A study of 204 defendants charged with hate crimes (Dunbar et al., 2005) found that 58% had a prior criminal conviction, and 33% had more than one prior conviction. Almost half of the offenders sampled had a prior arrest or conviction for a violent crime. Of those who had prior convictions, nearly half had a parole or probation violation on record. Many offenders had committed other violent offenses prior to the commission of their first hate crime (e.g., Gadd &

Dixon, 2009), and as Messner, McHugh, and Felson (2004) pointed out, these offenders are more likely to be generalists than specialists when it comes to their criminal behavior.

Dunbar et al. (2005) found that 23% of their sample had a criminal record for substance use or abuse; while this indicates a rate of lifetime substance abuse problems much higher than the general population, determining substance abuse by arrest record only is very likely to generate a significant underestimation of the pervasiveness of substance use disorders among hate crime offenders. Some of the offenders in Gadd and Dixon’s (2009) sample of 15 British individuals implicated in acts of racial harassment had alcohol problems, and two of those offenders reported experiencing intensified feelings of paranoia when intoxicated. Additionally, intoxication at the time of the offense appears to be more common among bias-motivated offenders than among non-bias offenders (Messner et al., 2004).

The limited research in this area suggests that there are certain psychological and historical factors that may predispose individuals to commit hate crimes. For example,

Anderson, Dyson, and Brooks (2002) found that hate crime offenders tend to be isolated and depressed. In the sample of 15 hate offenders interviewed by Gadd and Dixon (2009), one-third

(n = 5) had been diagnosed with a mental illness, and one-fifth were diagnosed as having paranoid delusions. Many hate crime offenders had unhappy childhoods; more than half reported abuse, neglect, or domestic violence experiences, and at least 60% were not raised by both biological parents. Dunbar et al. (2005) also found that hate crime offenders often hail from childhood households affected by domestic violence or parental separation.

White Supremacists have been characterized as individuals with poor self-concepts who establish self-esteem by dominating others (Hamm, 1993). Similarly, Sibbitt (1997) concluded that among the British hate crime offenders in her study, “expressions of racism often

serve[d] the function of distracting their own - and others’ - attention away from real, underlying concerns which they feel impotent to deal with” (p. viii). Ray, Smith, and Wastell (1994) detected unacknowledged shame in the verbal and nonverbal behavior of the hate offenders they studied, concluding that the offenders “saw themselves as weak, disregarded, overlooked, unfairly treated, victimized without being recognized as victims, made to feel small” (p. 355).

Furthermore, Gadd and Dixon (2009) reported that some of the hate crime offenders they interviewed did not openly endorse racist attitudes at all. They suggest that the racial epithets vocalized during these offenders’ offenses were not reflections of their own racial attitudes, but rather a frantic defense mechanism, by which their feelings of worthlessness are projected onto the victim. The language and behavior were chosen for their known ability to denigrate and demean. Additionally, some of the offenders in Gadd and Dixon’s (2009) sample had been victims of racial harassment or violence themselves prior to the commission of their crimes.

They viewed their crimes as retaliation for the wrongs they experienced at the hands of members of the group who had targeted them.

Dunbar et al. (2005) conducted what appears to be the only study looking at offender violence risk among hate crime offenders. Offender violence risk was assessed using the

Historical-Clinical-Risk 20 ([HCR-20]; Webster, Douglas, Eaves, & Hart, 1997) in a sample of

581 accused hate crime offenders. The most prevalent criminal risk factors were prior offending, prior supervision failures (e.g., probation violations), and significant occupational problems.

Higher risk scores on the HCR-20 demonstrated a statistically significant positive correlation with the severity of the hate crime(s) committed.

Research indicates that hate crimes are more commonly perpetrated by groups of offenders than are traditional forms of crime (e.g., Bufkin, 1999). As many as two-thirds of hate

offenses may be committed by two or more people working together, indicating a social/interpersonal contribution to the hate crime equation (Craig, 2002; Franklin, 2000).

Furthermore, a relationship has been found such that as the number of perpetrators involved in an offense increases, the level of violence severity also increases (Craig, 2002).

Hate groups. Although approximately 989 hate groups were active in the United States as of 2013 (SPLC, 2014), research indicates that modern hate crimes are far more likely to be committed by young people who are not members of organized hate associations (e.g., Dunbar,

2003; Levin, 2002; Levin & McDevitt, 1993; McDevitt, Levin, & Bennett, 2002). For example, in one study of 204 accused hate crime offenders (Dunbar et al., 2005), only 16% of the offenders sampled were associated with a hate-oriented gang or organization, while Perry

(2009d) cites fewer than 5% of known hate crime offenders as members of hate groups.

Nonetheless, Dunbar et al. (2005) found that offenders who are members of hate groups are more likely to have extensive violent criminal histories, and that the hate crimes they committed were more severe. This is particularly noteworthy in light of recent evidence that the number of hate groups in the United States has been steadily increasing since 2000 (Beirich & Potok, 2009).

Adolescent bias-motivated offenders. USDOJ statistics (2014) show that adolescents under 18 constitute only a small portion of offenders arrested annually (9.7%) but a much larger portion of bias-motivated offenders (32%). In a study of crimes investigated by the New York

Police Department (Cotton, 1992), 80% of the hate offenders sampled were adolescents.

Research suggests that adolescent hate crime offenders are particularly likely to be physically violent toward their victims (e.g., Maxwell & Maxwell, 1995), and they are more likely to choose strangers as their victims (e.g., Reasons & Hughson, 2000).

Female-perpetrated hate crime. Female involvement in hate crime perpetration is generally considered to be minimal. For example, of the 3,072 hate crime offenders identified in the NIBRS between 1997 and 1999, only 17% were female (Strom, 2001); of the violent hate crimes reported in the NCVS between July 2000 and December 2003, 21.1% were committed by females (Harlow, 2005). Female participation in hate crimes has typically been described as secondary (e.g., Bufkin, 1999), with most females acting in concert with male offenders. In the aforementioned NCVS sample (Harlow, 2005), 6.6% of hate crimes were committed by male and female offenders working together. One sample of hate crimes (Castle, 2009) indicated that female hate crime offenders often committed their crimes in groups with other females, with

40% of female-perpetrated crimes involving multiple female offenders. In Castle’s (2009) sample, 43.5% of female hate crime offenders were under the age of 18. Additionally, researchers (e.g., Blee, 2002; Perry, 2004) have suggested that females are participating in hate crimes at higher rates, which is consistent with increasingly broad gender roles for females in

American society.

Offender motivation. Levin and McDevitt (1993) studied a sample of 169 solved hate crimes recorded by the Boston Police Department, from which they derived three main subcategories of hate crime based on the offenders’ motives. Their original typology included three types: thrill, defensive, and mission. A later investigation (McDevitt et al., 2002) expanded this typology to include an additional subcategory: retaliatory.

Thrill offenders constituted 66% of McDevitt et al.’s (2002) sample. This group comprised offenders who reported to law enforcement that they had committed their offenses out of boredom. No triggering event was evident in these cases. Similarly, Byers et al. (1999) reported that most of the hate crime offenders in their sample were motivated by thrill-seeking.

Most of McDevitt et al.’s (2002) thrill offenders reported intentionally seeking out a potential victim in an area known to have target minority group members present. As such, their victims were typically strangers. They generally derived nothing from the crime except for sadistic pleasure or social status. Phillips (2009), using McDevitt et al.’s (2002) typology, reported that thrill offenses are often committed by groups of offenders. Gaining social acceptance or recognition may be particularly important to these offenders.

Defensive offenders constituted 25% of McDevitt et al.’s (2002) sample. This group comprised offenders who often use a severe form of violence to send a message to the target’s group. The offender views the victim as a representation of the group that is infringing upon the offender’s territory or the territory of his in-group; therefore, the specific individual targeted is of no consequence to the offender (Franklin, 2000). Consistent with Green, Glaser, and Rich’s

(1998) research on racially motivated hate crime, this type of offender sees himself as the protector of his in-group.

Mission offenders appear to be quite rare, constituting less than 1% of Levin and

McDevitt’s (1993) sample. This group comprised offenders whose crimes were motivated by a personal ideology. Mission offenders typically want to rid the world of a particular target group that they find to be offensive. These offenders are not casual in their offending, but rather are fully committed to their cause. Mission offenders may be members of hate groups, and may exhibit greater forensic awareness, often removing their weapons from the crime scene. On the other hand, they may be laboring under paranoid or grandiose delusions, in which case their crimes would be more likely to appear disorganized or take on an excessively violent quality

(e.g., Laajasalo & Hakkanen, 2006; Taylor et al., 1998).

Finally, retaliatory offenders constituted 8% of Levin and McDevitt’s (1993) sample (as reported in McDevitt et al., 2002). This group comprised offenders who commit their crimes in an attempt to restore their honor after a perceived bias-motivated attack by the victim or members of the victim’s group. It has been noted that offenses of this nature are more likely than others to trigger additional hate violence from the victim’s community in response.

Further research on the McDevitt et al. (2002) typology, however, has failed to support this organization. For example, Phillips (2009) investigated a set of hate crimes prosecuted in

New Jersey and determined that more than one-third of cases failed to be classifiable into one of the four subtypes. Phillips (2009) also noted that many of the crimes were motivated by not only animus toward the target group, but also other factors (e.g., financial gain). Fisher and Salfati

(2009) also found the typology to be invalid when applied to a non-random sample of adjudicated bias-motivated homicide cases.

Targeted groups. In addition to the general hate crime literature reviewed above, a variety of studies have looked specifically at the victimization of a single target group. Although any person could theoretically be a target of bias-motivated crime based on any of their identities, there is significant variation in the prevalence of hate crimes targeting various groups.

The groups most frequently victimized in the United States in recent years are also the groups most frequently addressed in the hate crime literature: Blacks, Latina/os, Asians, Native

Americans, Whites, Muslims, Jews, LGBTQ persons, and persons with disabilities.

Racial and ethnic crimes. Various sources of hate crime data indicate that the most frequently reported hate crime motivation over the past ten years has consistently been race (e.g.,

Dunbar et al., 2005; Fisher & Salfati, 2009; USDOJ, 2014). NCVS data (Wilson, 2014) suggests that ethnicity was a motive for 51% of hate crimes committed in 2012, which is a marked

increase over the 30% reported in 2011 and the 22% reported in 2004. Between the years of

2003 and 2008, UCR and NCVS data suggest that almost 90% of hate crime incidents were motivated by race, ethnicity, or a combination of the two (Langton & Planty, 2011). Among racially motivated crimes, African-Americans are most commonly victimized. As Perry (2001) points out, African-Americans constitute approximately 15% of the population, yet they have constituted roughly one-third of the victims of racial hate crime.

Green, Glaser, and Rich (1998) report that bias-motivated crimes towards Asians,

Latinos, and Blacks occur most frequently in predominantly White areas, especially those in the midst of an influx of racial or ethnic minority group members. Many White men now feel themselves to be disadvantaged in the job market and complain that affirmative action policies have denied employment and educational opportunities to qualified Whites in favor of less- qualified people of color (Dovidio, Mann, & Gaertner, 1989). In turn, the U.S. Commission on

Civil Rights (1990, 1992) has found a correlation between hostility toward affirmative action efforts and violence against racial and ethnic minorities.

Anti-Black hate crime. Bias-motivated violence against Blacks in the United States must be viewed in the context of a long history of racial subordination and conflict. As Bronski

(2011) wrote,

[S]lavery constructed a legal system that mandated noncitizenship for slaves (which, after

slavery was abolished, evolved into second-class citizenship for African Americans).

This denial of citizenship, however, did not release slaves from the obligation of obeying

the law, which was often enforced more harshly on them than on full citizens (p. 23).

Bronski reports that White colonists feared Africans due to a perception of them as hypersexual

beings, and their anxieties were permutated into various forms of sexual and nonsexual violence towards Africans and African-Americans. Similarly, Dollard (1937) observed that

[W]hite people fear Negroes. They fear them, of course, in a special context, that is,

when the Negro attempts to claim any of the white prerogatives or gains…By a series of

hostile acts and social limitations the white caste maintains a continuous threatening

atmosphere…when successful, the effect is to keep the social order intact (pp. 316-317).

Accordingly, in the 1860s, following the U.S. emancipation of enslaved African-

American, the Ku Klux Klan, a White Supremacist group, became especially active in the South, lynching Blacks and burning crosses and Black churches in order to intimidate newly-freed

Blacks (e.g., Perry, 2001; Turpin-Petrosino, 2009b). Although Klan membership declined by the

1870s and is at an all-time low today, this did not lead to the demise of racial violence (Levin,

2009). In the early 1900s, there were countless race riots across the United States in which at least 47 African-Americans were killed (Perry, 2001). The Ku Klux Klan gained prominence again between 1915 and 1925 to become the most successful incarnation of any hate group in in

U.S. history (Chalmers, 1981).

Hate crime scholars (e.g., Levin, 2009; Perry, 2001) have argued that modern anti-Black hate crimes are part of an enduring narrative arc of African American oppression. As Levin

(2009) wrote, “so many of the disparities that exist in the African American community today can be directly traced to inequalities passed on from an earlier generation that suffered under the brutal legacy of slavery and Jim Crow” (p. 1). In turn, many scholars (e.g., Bobo & Hutchings,

1996; Turpin-Petrosino, 2009b) have suggested that the persistence of anti-Black crimes and intergroup conflicts is likely due to the depth of Black-White intergroup conflict throughout U.S. history.

Torres (1999) noted an increase in the rate of anti-Black hate crime between 1992 and

1996, which he believes reflects the changing racial demographics in the United States. This trend is consistent with the aforementioned minority group threat theory (Blalock, 1967). The trend also supports the aforementioned defended neighborhoods theory (Green, Glaser, & Rich,

1998).

Turpin-Petrosino (2009a) investigated a sample of 88 anti-Black bias incidents in the

United States. Consistent with the concept of defended neighborhoods, nearly half of the incidents occurred in or around the victim’s home. Anti-Black hate crimes were not limited to any particular geographic region of the United States, despite the variance in racial demographics from state to state. (For example, Arizona, a state with a small Black population, reported that most of the racial incidents in their state between 1992 and 2006 were anti-Black crimes.) Most hate crime offenders (94%) verbally or symbolically communicated their anti-Black motivation during the commission of the crime. The races/ethnicities of the offenders in this sample were not reported.

Anti-Latina/o hate crime. The U.S. government has a history of inconsistent, exploitive treatment of Latina/os, particularly Mexicans (Ituarte, 2009). After the Mexican-American War of 1848, the U.S. government took over a large sect of Mexican land. Suddenly, Mexicans were considered “foreigners” in their own homeland. Since then, the United States has embraced

Mexicans at times when laborers have been in demand and rejected them in times of economic uncertainty. For example, during the Great Depression, the U.S. government created the

Mexican Repatriation Program, whose goal was to motivate individuals of Mexican descent to relocate to Mexico, at times through use of force.

Government measures disadvantaging Latina/os have been plentiful, thus lending a sense of legitimacy to acts of violence or intimidation directed at Latina/os (Ituarte, 2009). Law enforcement has often been complicit in the victimization of Latina/os; for example, during the

Zoot Suit Riots of 1943, American military servicemen were permitted to beat individuals of

Mexican descent and strip them naked without facing any legal repercussions for their actions

(Mahan, 2002). In 1954, the U.S. Attorney General placed 800 U.S. Border Patrol officers along the Mexican border and used a campaign of raids and blockades in an attempt to deport one million Mexicans, an effort known as Operation Wetback (Cardenas, 1975; Ituarte, 2009). As recently as the 1990s, legal restrictions on the rights of Latina/os were passed by the California state government in an effort to maintain social control, and a sweep of Chandler, Arizona in

1997 violated the civil rights of many Latina/o citizens who were perceived as illegal immigrants and asked to produce formal documentation (Ituarte, 2009).

In the twenty-first century, immigration continues to be a leading motive for anti-Latina/o offenses. According to Katel (2009), most anti-Latina/o hate crimes are directed towards

Latina/o individuals who are thought to be illegal immigrants, whether or not this perception is accurate. Latina/o day laborers, many of whom are legal U.S. citizens, are common targets of bias-motivated offenses, harassment, and exploitation (Ituarte, 2009). Traditionally racist hate groups have become interested in the issue of illegal immigration in recent years (Beirich &

Potok, 2009), and undocumented workers make ideal targets for crime, due to their lack of willingness to report victimization to the authorities and the likelihood that they will be carrying cash when attacked (López, 2012). Furthermore, White vigilantes have created paramilitary organizations, such as “the Minutemen,” and have continued to patrol the Mexican border, freely threatening, and possibly killing, Latina/os.

Hate crimes directed towards Latina/os have largely gone unstudied (e.g., Perry, 2009b).

Most knowledge in this area is related to victim risk, with very little information available regarding those responsible for these offenses, and there is reason to believe that UCR numbers drastically underestimate their prevalence, as immigrant victims may fear that reporting victimization could result in deportation or may not fully understand their legal rights (Kittrie,

2006). An investigation by Carrigan and Webb (2003) documented at least 597 lynchings of

Latinos between 1848 and 1928. More recent research (Stacey, Carbone-Lopez, & Rosenfeld,

2011) indicates that trends in anti-Latina/o hate crimes, as recorded in the UCR, are more common in areas with smaller Latina/o populations and greater variation in the size of the

Latina/o population over shorter periods of time. The nationwide statistics show a positive correlation between the size of the U.S. Latina/o population and the number of anti-Latina/o hate crimes recorded in the UCR. Recent UCR data (USDOJ, 2014) indicates that 331 anti-Latina/o hate crimes were reported in 2013, with Latina/os constituting more than half (52.6%) of victims targeted due to ethnicity.

Anti-Asian hate crime. Biases toward Asians appear to be similarly linked to perceptions of immigrant threat. Workers from Asia were invited to the United States to help build the transcontinental railroad, but once here, they experienced prejudice and their work opportunities were limited. Asian workers were paid less and were expected to work longer hours (Chinese Railroad Workers in North America Project, 2015). Racial violence was commonly experienced by the early Chinese immigrants (Takaki, 1994), and as Bronski (2011) notes:

[A]s the presence of immigrants [in San Francisco] grew, so did strong anti-immigrant

sentiment. In the 1850s there was organized mob violence against people from Latin

America. Anti-Chinese sentiment led to the passage of the federal Chinese Exclusion Act

in 1882, which was enforced until 1943 (p. 47).

Fifty-five anti-Chinese incidents were reported in nine Western territories and states between the years of 1849 and 1910 (Tsai, 1986), and this number is likely to vastly underestimate the true prevalence of such offenses.

Similarly, a significant wave of anti-Filipino hate crime followed the large-scale increase in the Filipino population due to immigration to the Western states in the early 20th

Century. Filipinos were quickly seen as competition in the agricultural job market, as well as sexual rivals, as the lack of female Filipina immigrants in the early waves of immigration left many Filipino men to date White women (Bankston, 2006). Anti-Filipino riots began in the late

1920s throughout California. In a 1934 edition of the news magazine Current History,

Sacramento nativist businessman C. M. Goethe warned that “Filipinos do not hesitate to have nine children [which means] 729 great grand-children as against the white parent’s twenty- seven” (p. 354). Most nativists came to support the independence of the Philippine nation in order to “solve” the Filipino “problem” in the United States. In 1934, the Philippines were granted independence, and Filipinos were later declared aliens and encouraged to return to the

Philippines by subsidizing their relocation using public funds. An annual immigration quota of

50 (less than any other Asian nationality) was enacted from 1934 to 1946, and the intensity of anti-Filipino violence gradually dissipated.

Kang (1993) demonstrated that there is a strong association between negative stereotypes about Asians and Asian-Americans and violence perpetrated against them. On one hand, Asians are often perceived as physically inferior, making them ideal targets for crime; on the other hand, Asians are seen as “un-American” competitors in the job market.

Asians have been largely underrepresented in the hate crime literature, although the existing literature suggests that anti-Asian violence rose throughout the 1990s and early 2000s

(e.g., USDOJ, 2007; Perry, 2009b; US Commission on Civil Rights, 1992). The National Asian

Pacific American Legal Consortium (NAPALC, 1996) has reported a wave of anti-Asian violence that corresponds with an increasingly common anti-immigration attitude, and this trend has been consistent through the end of the twentieth century and beyond (Perry, 2002). Recent

UCR data (USDOJ, 2014) indicates that 135 anti-Asian offenses were committed in 2013; however, comparisons between NAPALC data and FBI data show that the UCR tends to vastly underestimate the number of anti-Asian hate crimes occurring in the United States each year, some years (e.g., 1994) by as much as 50% (Perry, 2002). Like anti-Latina/o hate crimes, anti-

Asian hate crimes may not be reported to the police due to fear of deportation or poor understanding of legal rights (Kittrie, 2006).

Anti-Arab hate crime. The Arab-American Anti-Discrimination Committee (ADC,

1997) has reported a rising tide of violence toward Arabs in the time following the Gulf War.

For the most part, recent violence and harassment toward Arabs and Arab-Americans is inextricable from attitudes toward Muslims, as a result of associations with the September 11,

2001 (9/11) terror attacks. These crimes are discussed in detail later in this review, under Anti-

Muslim Hate Crime.

Anti-Native American hate crime. In the nineteenth century, British and American military officials instructed their troops to infect blankets with diseases such as smallpox in order to exterminate Native Americans in large quantities (Stiffarm & Lane, 1992). The U.S. military assaulted Native American villages; for example, in 1884, the massacre of Sand Creek led to the violent deaths of 132 Southern Cheyenne and Arapaho men, women, and children (Perry,

2009b). An estimated 10,000 Native Americans lost their lives in these attacks. Another 8,000 subsequently lost their lives along the Trail of Tears, a 1,500-mile trek from present-day Georgia to present-day Oklahoma. Native Americans were forced into reservations, which served to maintain geographic boundaries between the Natives and the Whites (Perry, 2009a, 2009c).

Perry (2009a, 2009d) argues that the violent conquest of the Native Americans foreshadowed and enabled continuing systemic discrimination and violence. A survey of nearly

300 Native Americans across the United States (Perry, 2009a) indicates that bias-motivated violence towards Native Americans remains pervasive. Informants reported being stopped by

White police officers as soon as they went beyond the reservation borders. Many Native

Americans have come to view off-reservation violence by Whites as a normative experience.

Informants reported that this violence kept them within the confines of the reservation; fear of violence reportedly deterred Native Americans from seeking employment, education, goods, and services outside of the reservation. In this way, routine violence and threats of violence reinforce the boundaries between Native Americans and Whites and reminds Native Americans that they are perceived as less-than.

Hate crimes motivated by bias against Native Americans are understudied and underrepresented in the literature (e.g., Nielsen, 1996, 2000; Perry, 2009c). In 2013, 4.3% of hate crimes reported in the UCR were motivated by anti-American Indian or Alaska Native bias

(USDOJ, 2014). However, due in part to the long history of negative relations between Native

Americans and law enforcement, it is very likely that most acts of anti-Native American violence are not reported to the police (Perry, 2009d). Most informants in Perry’s (2009a, 2009d) study reported multiple violent victimizations, which strongly suggests that the small number of crimes

depicted by UCR data is unrepresentative of the lived experience of Native Americans in the

United States.

Anti-White hate crime. Bias-motivated offenses against Whites constitute a special case, in that Whites are not considered a marginalized group in United States. Though the term hate crime most commonly calls to mind the image of a White offender victimizing a person of color, the case of Wisconsin v. Mitchell, 508 U.S. 476 (1993) upheld the protection of White citizens against crimes committed due to race. It is likely that White denigration and subjugation of other racial and ethnic groups serves as the primary impetus for crimes motivated by bias against

Whites. Paige reported in 1970 that “it would seem that most blacks have eminently rational reasons for resenting their treatment by the white majority” (p. 69). Similarly, Bell (1978) noted that “it is extremely difficult to distinguish black racism from a reaction to white racist practices”

(p. 90).

Anti-White hate crime remains statistically rare and is rarely addressed in the hate crime literature. The UCR (USDOJ, 2014) indicates that 21.4% of racially motivated hate crimes reported in 2013 were motivated by anti-White bias. A total of 728 anti-White hate crimes were reported in 2013 (USDOJ, 2014).

Religious hate crimes. The percentage of reported hate crimes motivated by religious bias increased from 10% in 2004 to 28% in 2012 (Wilson, 2014). The UCR (USDOJ, 2014) reported that 1,163 religiously motivated offenses took place in 2013. The most common victims were Jews and Muslims.

Anti-Jewish Hate Crime. Anti-Jewish sentiment, or anti-Semitism, has been a societal force in the United States since its inception (Turpin-Petrosino, 2009b). In turn, Jews have consistently constituted roughly 10% of all reported victims of hate crime in the United States

(Perry, 2001). In 2003, anti-Jewish crimes accounted for one in eight reported hate crimes

(USDOJ, 2005). The rate appears to have declined significantly since then. The UCR (USDOJ,

2014) reports that more than half (59.2%) of crimes motivated by religious bias were anti-

Semitic in nature, for a total of 689 anti-Semitic crimes in 2013, most of which were acts of vandalism or destruction of property (n = 437).

According to the Anti-Defamation League (ADL) of B’Nai B’Rith (2014), about 9% of

U.S. citizens sampled hold anti-Semitic views, making the United States one of the least anti-

Semitic nations in the Western hemisphere. The ADL conducts its own audits of anti-Semitic crimes, in order “to provide the community and its elected and law enforcement officials with an accurate and reliable measure of overt anti-Semitic activity, and thus a basis for response evaluation and counteraction regarding a troubling and dangerous problem (ADL, 1995, p .18).

The ADL derives its data from crimes reported by law enforcement agencies, as well as crimes or complaints filed with the ADL that may not have resulted in official police reports. The ADL

(2015) reports that 912 anti-Semitic hate crimes were reported in 2014, which marks a 21% increase over the previous year. Despite going beyond UCR data, ADL data are still likely to underestimate the number of anti-Semitic crimes (Perry, 2001). Additionally, ADL data indicates that the number of anti-Semitic hate crime incidents has declined, while the severity of these incidents has increased (ADL, 2015; Perry, 2001). In particular, college campuses have seen an increase in anti-Semitic crimes (Perry, 2001).

Research conducted in the European Union (Bergmann & Wetzel, 2003) indicates that crimes motivated by anti-Jewish sentiment have been on the rise since the escalation of conflict in the Middle East in 2000, with a peak in early 2002. Many crimes against Jewish people and institutions (e.g., synagogues) are reportedly committed by Muslim-Arabs, a group of individuals

who have themselves been subject to very similar violence. Bergman and Wetzel (2003) suggest that social problems endemic to the marginalized status of migrants are “an essential factor for their propensity to violence and susceptibility to anti-Semitism” (p. 27).

Anti-Muslim (Islamophobic) hate crime. Although 9/11 may now be the most salient memory associated with American hatred and fear of Middle Eastern individuals, American anti-

Arab sentiment and Islamophobia predate 9/11 (e.g., Abraham, 1994; Ismael & Measor, 2003).

In 1994, Abraham wrote that “events occurring in the Middle East, particularly violence against

U.S. citizens, often trigger jingoistic violence against Arabs and others who could conceivably be confused with them, such as Muslims, Iranians, or Palestinians” (p. 194). For example, it was reported in the L.A. Times (Toth, 1991) that 48 incidents of violence or harassment directed at

Arab-Americans occurred in the United States within the first month of Operation Desert Storm in 1990.

Nonetheless, the 9/11 attacks created what Ismael and Measor (2003) referred to as a

“blend of xenophobic fears of the ‘other,’ and that of terrorism” (p. 103) – a perfect storm for the justification of violence against a group of people deemed “evil.” Perry (2009b) argues that three types of false assumptions underlie this justification: 1. All Muslims are presumed to be terrorists, or at least must be suspected of potential terrorism; 2. Muslims are not loyal

Americans; and 3. All Arabic people are Muslim. Prior to the 9/11 terror attacks, Muslims were not a frequent target of hate violence; for example, the Council on American Islamic Relations

(CAIR, 2006) recorded only 80 complaints of anti-Muslim civil rights violations. However, following the 9/11 attacks, a steep increase in the number of hate crimes targeting Muslims (or those perceived to be Muslim) was observed (Ibish & Stewart, 2002; Kaplan, 2006; Perry, 2003;

USDOJ, 2002). Within 24 hours of the attacks, several anti-Muslim homicides had been

reported, and within a week, the FBI was investigating 40 crimes as possible anti-Muslim hate crimes (Perry, 2009a). By the time one month had passed, the FBI was investigating 145 possible hate crimes, and the Muslim Public Affairs Council of Southern California reported 800 anti-Muslim hate crimes nationwide (Perry, 2009a).

Non-Muslim individuals were commonly targeted in this sweep of hateful aggression, with anyone who looked vaguely Middle Eastern becoming a possible target. As Blazak (2009) points out, rampant American misconceptions about Middle Eastern heterogeneity were likely fueled by mainstream media, as well as public remarks by then-President George W. Bush casting those of Arab descent as the target in America’s “War on Terror.” The Sikh organization

Khalistan Affairs Center estimated that at least 200 crimes against Sikhs had been targets of violence within a month of 9/11, and other dark-skinned people were affected as well. For example, in Massachusetts, in the months following 9/11, a Greek American had the windows of his café smashed, and the message “Freedom for all” was left at the scene (Perry, 2009c). More than half of the civil rights complaints received by CAIR in 2006 were committed on the grounds of similar misperceptions (CAIR, 2007).

According to the Pew Research Center (2010), the proportion of Americans with favorable opinions of the Islamic religion dropped from 41% in 2005 to 30% in 2010. Abu-Ras and Suarez (2009) found that, in a study of 102 Muslims living in New York City, 25% reported being verbally assaulted and 19% reported being physically assaulted. Workplace and law enforcement harassment were also commonly reported. Similarly, in a survey of 139 American

Muslims (Abu-Raiya, Pargament, & Mahoney, 2011), most respondents had experienced one or more stressful encounters with anti-Muslim sentiment. This sentiment has unfortunately affected not only Muslim adults, but Muslim children and adolescents as well (Sirin & Fine, 2008),

creating significant amounts of stress among American Muslim individuals and communities.

These occurrences are apparently not limited to the United States, but have also abounded in

Canada (Kilgour, Millar, & O’Neill, 2002) and Australia (Poynting, 2002).

Although USDOJ (2013, 2014) and CAIR (2008) statistics indicated that anti-Muslim crimes tapered off significantly by 2007, the UCR (USDOJ, 2016) reported a 67% increase in anti-Muslim hate crimes in 2015; scholars have pointed out that this year also marked the commencement of Donald Trump’s “Make America Great Again” campaign for the U.S. presidency (Mathias, 2017). Data released by the Center for the Study of Hate and Extremism

(2017) showed that 6 of 7 major cities polled reported increases in anti-Muslim hate crime from

2015 to 2016. Only Los Angeles reported a decline in the rate of anti-Muslim crime during this period. Spikes in anti-Muslim hate crime were also observed in the period following President

Donald Trump’s institution of a federal Muslim travel ban in December 2015, leading scholars such as Brian Levin to surmise that anti-Muslim attacks may be associated with Trump’s public statements correlating the Islamic religion with terrorism (Mathias, 2017).

Anti-LGBTQ hate crime. With the passage of new legislation in 2009, the federal government gained the authority to prosecute violent hate crimes, including violence directed at lesbian, gay, bisexual, transgender, and queer (LGBTQ) individuals. UCR statistics indicate that over 1,400 anti-LGBT hate crimes were reported in 2013, making it the second most prevalent type of hate crime offense (USDOJ, 2014). Although methodological issues make it difficult to discern trends in anti-LGBT hate crimes over time, research by Reasons and Hughson (2000) indicates that during a period in which the rate of hate crimes had decreased by 3% overall, the rate of anti-gay hate crimes had risen by 81%. Similarly, the Anti-Violence Project has noted increasing rates of anti-LGBT homicide since 2007, reaching a record high of 30 anti-LGBT

murders in 2011 and 25 in 2012 (NCAVP, 2013). California, New York, New Jersey, and

Massachusetts have consistently reported the highest anti-LGBT hate crime rates (e.g., USDOJ,

2010, 2014); however, this most likely reflects regional differences in hate crime recording and reporting practices, as well as the strong presence of LGBTQ communities in these states.

LGBT youth are also affected by this phenomenon. Research published by the Gay,

Lesbian, and Straight Education Network (GLSEN; Kosciw, Greytak, Bartkiewicz, Boesen, &

Palmer, 2012) indicates that 18.3% of LGBT students reported that they were physically assaulted at their middle school or high school in the past year due to their sexual orientation, and 12.4% reported being assaulted because of their gender expression/identity. These startling trends highlight the need for better research into the causes of anti-LGBT violence.

Anti-LGB hate crime. Although same-sex sexual activity has been recorded as common practice dating back at least as far as Ancient Greece and Rome, in the 1950s and 1960s

- a time of great conformity in the United States - the dominant position in the American psychoanalytic literature was that homosexuality was a pathological defense against castration fears or a failure to properly progress through the stages of psychosexual development (Mitchell

& Black, 1995). Psychoanalysts often insisted that their homosexual patients deny their sexual orientation and attempted to “convert” them to heterosexuality; Hatterer (1970) even cited a 45% success rate in curing homosexuality among his gay male patients seen for analysis in the late

1960s. Hatterer, among others, denounced homosexuality as a deviant behavior, not an identity.

After a personal incident in which his colleagues rejected the presence of his lesbian friend at a social gathering, George Weinberg began to publicly criticize this perspective on homosexuality

(Grimes, 2017), and in 1972, he used the term homophobic to denounce his colleagues who labored under such biases (Herek, 2004).

Over the past few decades, Americans’ attitudes toward homosexuality and same-sex relationships have become more positive (Avery et al., 2007, Gibson, 2006; Pew Research

Center, 2013, 2017; Russell, 2002); however, negative stigma surrounding LGB identities remains pervasive (Hansen, 2007; Horn, 2006; Nadal, Issa et al., 2011; Wyss, 2004). For example, the Pew Research Center (2017) estimated that 70% of Americans agree that homosexuality “should be accepted by society” (p. 41); this number is up from 60% in 2013 and

49% in 2007. Yet, nearly one quarter (24%) of Americans polled endorsed the belief that homosexuality “should be discouraged by society” (Pew Research Center, 2017, p. 7), and legislators’ positions appear to be more conservative on this issue than are the positions of the general public (Herrick, 2010).

Several theories of anti-gay aggression have been posited, and research in this area is burgeoning in comparison to research on other types of hate crime. Herek (1984, 1986, 1988,

1989, 2000, 2004) has been a leader in this research agenda, putting forth a model of sexual prejudice as a precursor to anti-gay violence and aggression. Herek proposes that rigid beliefs about gender roles form the basis of heterosexism, a belief system that privileges heterosexuality and denigrates homosexuality and bisexuality as unnatural, immoral, or illegitimate. Individuals who hold sexually prejudiced beliefs perceive same-sex relationships as violations of gender roles, and these beliefs have proven to be associated with perceptions of gender role violations as threatening in some way (Herek, 2000; Kilianski, 2003; Parrott, Adams, & Zeichner, 2002; Sinn,

1997). Sexual prejudice has also been linked to self-reported aggressive behavior towards gay men (Franklin, 2000; Hegerty, Pratto, & LeMieux, 2004; Patel, Long, McCammon, & Wuensch,

1995). Heterosexual-identified men appear to be especially affected by this phenomenon (Herek,

2002; Kite & Whitley, 1998; Parrott & Zeichner, 2005), an observation that is mirrored in

statistics indicating that males are responsible for the vast majority of anti-gay hate crimes and are more prejudiced against gay men than are women (e.g., Baker & Fishbein, 1998; Whitley &

Kite, 1995). Laboratory research (Parrott & Peterson, 2008) indicates that anger mediates the relationship between sexual prejudice and violence, such that increased levels of anger increase the likelihood of aggression toward gay men.

A peer dynamics model has also been proposed, in which anti-gay aggression served the function of proving “both toughness and heterosexuality to friends” (Franklin, 1998, p. 12). This model indicates that when a man’s masculinity is challenged, it will likely result in an exaggerated demonstration of masculinity, in the form of anger and aggression. In this model, anti-gay aggression is also seen as a way of maintaining privileged group membership; acts of anti-gay violence serve to separate the offender from the victim and the associated out-group, as well as to bond him to his in-group (Franklin, 1998). Laboratory research (Parrott & Peterson,

2008) indicates a positive association between strong needs to prove heterosexuality and masculinity to peers and an increased frequency of committing acts of anti-gay aggression.

Research (e.g., Weinstein et al., 2012) also supports a social learning perspective, such that those with homophobic parents are more likely to endorse anti-gay attitudes themselves.

Yet another theory understands homophobic crimes as the product of an offender’s attempts to suppress his or her own same-sex desire (Ryan & Ryan, 2012). Psychodynamic theory attributes homophobia primarily to a process Freud (1917/1977) termed reaction formation, in which an individual combats an impulse that he or she finds deeply troubling by rejecting it and endorsing an opposing impulse. For example, in 2006, vocal anti-gay evangelist

Ted Haggard was exposed for having had an affair with a former male prostitute. Haggard himself suggested that his aggressive anti-gay rhetoric was “because of [his] own war” (Ryan &

Ryan, 2012). Research has provided support for the notion that homophobia is often associated with same-sex attraction (Weinstein et al., 2012) and suggests that males who espouse very negative attitudes toward homosexuality are more likely to become sexually aroused in response to homosexual pornographic images (Adams, Wright, & Lohr, 1996).

Those who hold strong, negative attitudes toward LGB individuals tend to differ from more accepting individuals in a variety of ways. They are more likely to be male than female

(Bouton et al., 1987; Long & Millsap, 2008; Whitley & Kite, 1995), embrace traditional gender roles (Kite & Whitley, 1996), tend to be more religious (Herek, 1984; VanderStoep & Green,

1988), are often also racially prejudiced (Basow & Johnson, 2000), and have less personal contact with LGB individuals (Herek & Capitanio, 1996). Homophobic attitudes have been found to correlate with fear of acquiring the AIDS virus, although this association is weaker now than it was 20 years prior (Bouton et al., 1987; Long & Millsap, 2008). It has also been suggested (Long & Millsap, 2008; Williams, 2015) that Black Americans as a group are generally more homophobic than Latino/as and Asians, though explanations for this phenomenon have been unclear to date.

Younger people are more likely to support gay rights than are older Americans (e.g.,

Olson, Cadge, & Harrison, 2006; Wilcox & Norrander, 2002; Wilcox & Wolpert, 2000); however, LGB (and T) adolescents are at great risk of victimization by peers. Research has repeatedly confirmed that LGB (and T) adolescents are significantly more likely than their straight, cisgender counterparts to be bullied, harassed, or assaulted (e.g. District of Columbia

Public Schools, 2007; Poteat & Espelage, 2005; Robin et al., 2002; Russell, Franz, & Driscoll,

2001; Williams, Connolly, Pepler, & Craig, 2003, 2005). Franklin’s (2000) study of homophobic violence among college students suggests that the commission of anti-gay crime is

not limited to hardcore criminal offenders, but rather is interwoven into our societal structure in a way that permits or encourages this behavior in otherwise law-abiding young men.

In her study of offenders’ self-reports of anti-gay assaults, Franklin (1998) observed that many anti-gay crimes are motivated by boredom. Offenders perceived gay men as “easy targets” and found their crimes to be a source of fun and amusement. Franklin (1998, 2000) has pointed out that many of the offenders who attack gay victims for thrills may not hold strong sexually prejudiced ideas but go along with the predominant group mentality. Furthermore, laboratory research (Parrott & Peterson, 2008) indicates that thrill-seeking tendencies are a predictor of perpetration of anti-gay aggression.

As a result of harassment, gay and bisexual individuals often report being fearful about openly expressing their sexuality because of the possibility of violent victimization and may feel embarrassed or ashamed about being the victim of bullying and harassment (Nadal, Issa et al.,

2011; Nadal, Wong et al., 2011). And aptly so, as surveys indicate that between 60 and 90% of

LGBT individuals experience verbal abuse, and up to 30% experience physical abuse – rates much higher than that observed in the general population (Perry, 2001). Furthermore, anti-gay crimes tend to be more violent than other forms of victimization (Berrill, 1992, 1993; Cheng,

Ickes, & Kenworthy, 2013). Of the anti-LGB crimes reported in the UCR (USDOJ, 2014), the most common offenses were simple assault (n = 547), intimidation (n = 318), and aggravated assault (n = 193).

Anti-transgender hate crime. Transgender individuals - those whose gender assigned at birth does not match their experience or perception of their own gender - are frequent victims of violence (Grant et al., 2011), but anti-transgender hate crimes have received little research attention. Although transgender, or trans, persons are often included in organizations, initiatives,

and acronyms including lesbian, gay, and bisexual individuals (e.g., the common acronyms

LGBT and LGBTQ), legal protections and public acceptance have lagged behind efforts on behalf of lesbians, gays, and bisexuals. For example, according the National Gay and Lesbian

Task Force (2013), only 15 states and the District of Columbia include gender identity in their hate crime statutes to enhance penalties for other offenses.

Recent research suggests that transgender individuals experience higher rates of violence in the community, in institutions, and in police custody (e.g., Grant et al., 2011). Transgender individuals have reported being mistreated by police officers and disrespected by nurses and doctors, sometimes leading to avoidance of the utilization of their services (e.g., Nadal,

Davidoff, Davis, & Wong, 2014). Avoidance of the law enforcement and health care institutions can put transgender individuals at further risk of adverse outcomes. As the National Gay and

Lesbian Task Force concluded:

Transgender and gender non-conforming people face injustice at every turn: in childhood

homes, in school systems that promise to shelter and educate, in harsh and exclusionary

workplaces, at the grocery store, the hotel front desk, in doctors’ offices and emergency

rooms, before judges and at the hands of landlords, police officers, health care workers

and other service providers (Grant et al., 2011, p. 2).

Transwomen, or female-identifying transgender persons, appear to bear a greater share of this burden compared to transmen, or male-identifying transgender persons (e.g., Goldblum, et al.,

2012; Transgender Community Health Project, 1999).

Experiences of gender-based victimization in high school settings is commonly reported by transgender individuals; for example, in one study of 290 transgender adults (Goldblum et al.,

2012), 44.8% retrospectively reported having been victimized because of their gender identity or

gender expression while in school. This experience was more common among transwomen than transmen and was often severe enough that it caused the individual to drop out of high school. In another study (Clements-Nolle, Marx, & Katz, 2006), 83% of transgender respondents reported that they had been verbally abused or assaulted because of their gender identity or gender expression, and 36% reported that they had been physically abused or assaulted because of their gender identity or gender expression. These findings are especially troubling in light of corresponding evidence that having experienced anti-transgender harassment or violence is associated with attempted suicide and greater frequency of suicide attempts (Clements-Nolle et al., 2006; Goldblum et al., 2012).

Xavier’s (2000) study of transgender individuals in Washington, DC indicates that roughly 15% had experienced transphobic victimization, which is a conservative estimate compared to other samples. For example, Clements-Nolle et al.’s (2006) study of transgender individuals in the San Francisco area found that 83% of respondents had experienced transphobic verbal attacks, 59% had been forced to engage in sexual acts, and 39% had been physically assaulted due to their gender identity. Another survey study of 402 transgender individuals in the United States (Lombardi, Wilchins, Priesing, & Malouf, 2002) reported that approximately

60% of respondents had experienced some form of transphobic violence or harassment.

Although the prevalence estimates have varied from study to study, it is clear that hate crime victimization is common in the transgender population.

A study of Los Angeles County Commission on Human Relations data (Stotzer, 2008) suggests that most transphobic hate crimes in Los Angeles County between 2002 and 2006 took place in public places, such as streets, parks, and parking lots. Offenders commonly approached victims engaging in everyday activities and began attacking them with transphobic and

homophobic language before engaging in violence. Most victims were male-to-female (MTF) transgender individuals. The victims were disproportionately Black, given the demographics of the area. Most victims were attacked while alone, and most perpetrators acted alone. The majority of perpetrators were male (80.6%), and most of the female perpetrators were not acting alone. Typically, the perpetrator was a stranger to the victim (87.2%).

Crimes against persons with disabilities. Research (e.g., Baladerian, 1991; Burgdorf,

2000; National Organization on Disability, 2000; Sobsey, 1994; Sobsey & Doe, 1991; Wilson &

Brewer, 1992) indicates that individuals with physical or psychological disabilities are the targets of crime at rates that far exceed the general public. Some researchers (Garland, 2011; Novis,

2010) have argued that this is not owing to persons with disabilities being more “vulnerable” to criminal victimization, but rather that these crimes are the product of offenders’ biased beliefs about persons with disabilities. Smart (2001) has concluded that “no other racial, cultural, ethnic, linguistic, religious, political, national, sexual orientation, or gender group has experienced such a pervasive degree of generalized prejudice and discrimination” (p. 72). For example, Lane, Shaw, and Kim (2009) report that the involuntary medical sterilization of persons with disabilities to prevent their sexual reproduction was a legally permitted practice in the

United States until as recently as the 1970s. Although many state statutes permitting involuntary sterilization were overturned since World War II, due to its association with Hitler’s eugenics campaign, 21 states still have involuntary sterilization laws, and legal guardians continue to have success in achieving court-ordered sterilization of individuals with intellectual disabilities

(Jennings, 2015).

Persons with physical, intellectual, and/or developmental disabilities constitute approximately 20% of the U.S. population (McNeil & Binette, 2001) and have been protected

under hate crime law since the 1996 update to the Hate Crime Statistics Act. The 1999 torture and assault of New Jersey resident Eric Krochmaluk is reportedly the first crime against a person with a disability to ever go to trial as a hate crime in the United States (MacFarquhar, 1999).

The young man with intellectual disability was lured to a party, where he was held captive, tormented, and beaten for hours by a group of adult men. The case resulted in seven of the eight perpetrators being convicted of bias assault, but this crime is different from many crimes against disabled persons in the conspicuous nature of the bias component. Overall, UCR and NCVS data consistently suggest that individuals with disabilities are the group least likely to report hate crime victimization to the police (Langton & Planty, 2011; McMahon, West, Lewis, Armstrong,

& Conway, 2004; USDOJ, 2013, 2014).

The UCR (USDOJ, 2014) reports that just 1.3 percent of hate crimes in 2013 resulted from bias against disabilities (n = 83). However, this is almost certainly not due to a lack of hate crimes against this population. Research (Sobsey, 1994) indicates that, in general, crimes against persons with disabilities are most often committed by those closest to them – family members and other caregivers. This both limits the likelihood of the victim reporting a crime and the likelihood that a bias-motivated offense will be recognized as such, due to it violating a basic assumption about hate crime (i.e., most offenders are strangers to their victims). Furthermore, many individuals with disabilities lack access to law enforcement and may be unaware of their legal rights (Lane, Shaw, & Kim, 2009).

Of those disability-motivated hate crimes reported in the UCR for 2013 (USDOJ, 2014),

26.5% of offenses targeted an individual with a physical disability, and 73.5% of offenses targeted an individual with an intellectual disability. The most commonly reported offenses were

simple assault (n = 16) and intimidation (n = 21). More research is needed to accurately suss out bias-motivated offenses from other forms of crime targeting this population.

Misogynistic hate crimes. Crimes against women are an area in which hate motive determinations remain even murkier (Center for Women’s Policy Studies, 1991). Experimental studies (Hertl & Sinclair, 2008; Saucier, Brown, Mitchell, & Cawman, 2006; Sinclair & Hertl,

2010) indicate that crimes committed against women are statistically significantly less likely to be considered hate crimes than are crimes against other marginalized groups, even when similar bias indicators are present. One apparent problem is that crimes against women are typically committed by individuals who are known to them (e.g., Koss, Goodman, Fitzgerald, Keita, &

Russo, 1994); if this is also true of misogynistic hate crimes, then they contradict the prototypical hate crime and are likely to go unidentified (Center for Women’s Policy Studies, 1991).

Furthermore, hate speech against women is not taken as seriously as discrimination towards other groups (Cowan & Hodge, 1996), and protection for gender was not added to the federal definition of hate crime until 2009, when the Matthew Shepard and James Byrd, Jr. Act was passed.

As Perry (2001) points out,

[W]hile not all violence against women is necessarily bias motivated - just as not all

violence against people of color is bias motivated - much of it is inspired by the anxieties

and frustrated expectations of ‘woman’s place.’ It is meant to teach women, both

individually and collectively, a lesson about remaining accountable to their femininity (p.

83).

Misogynistic hate crime offenders appear to endorse traditional gender roles in which women are inferior and relegated to the home. Feminist scholars (e.g., Brownmiller, 1975; Rothschild,

1993) have pointed out similarities between violence against women and the lynching of Black men as means of maintaining the status quo and keeping victims in a position of disadvantage relative to White men.

Though most crimes against women are probably not motivated by a bias against all women, just as most crimes against individuals from other identity groups are not motivated by bias, some criminal offenses against women have clear misogynist motives. For example, in

1989, Canadian Marc Lepine entered a classroom of engineering students, separated the men from the women, and then shot and killed fourteen of the women before killing himself. Nine other women were injured. His suicide note and behavior at the crime scene provided clear indication of a gender bias motive. His murderous rage has been seen as the product of his sense of disempowerment as a White man, particularly with regard to his victims’ infiltration into a traditionally male-dominated field (Caputi & Russell, 1992).

Some legal scholars (Carney, 2012; Goldscheid, 1999; MacKinnon, 1991) have posited that rape in particular is inherently a bias-motivated offense, in that women and girls are targeted due to their female identity. Others (e.g., Campo-Engelstein, 2015) have pointed out that many state statutes describe rape as an act of forcible penile-vaginal penetration; thus, in these states, only females can be the victim of rape. They argue that, like racial minorities, women are targeted due to an immutable characteristic – gender.

Feminist scholars have pointed out the historical use of rape as a tool used to subordinate women (Pendo, 1994). The fear of being raped is instilled in women from a very early age and has been conceptualized as form of social control over women (Riger & Gordon, 1981). The effects of rape are also similar to the effects of hate crime, in that they generate terror not just in the victim, but throughout the victim’s in-group (Carney, 2012). Furthermore, psychological

research has revealed a positive relationship between hostile sexism – the objectification or degradation of women – and likelihood of committing rape (e.g., Masser, Viki, & Power, 2006).

Though controversy about the conceptualization of rape as a hate crime exists, the UCR

(USDOJ, 2014) reports that only 2 of the 79,770 rapes reported in 2013 were motivated by gender bias. Furthermore, the very small number of anti-female gender hate crimes of any kind reported in the UCR (USDOJ, 2014) - just 18 incidents - speaks to the limited likelihood that any offense will be charged as an anti-female hate crime. This area of research and debate is worthy of further exploration but is beyond the scope of the present study.

Hate crimes based on multiple marginalized identities. Recent research (Nadal et al.,

2015) has begun to look at the experience of individuals with multiple or intersectional marginalized identities. Qualitative research (Nadal et al., 2015) has indicated that individuals with intersectional identities have unique experiences which differ from experiences of individuals with a single marginalized identity. For example, being Latino and gay brings with it a certain set of common discriminatory experiences, and being Latina and gay brings with it a different set of experiences. Still, little is known about the frequency of these affronts or their prevalence relative to other forms of discrimination.

UCR data (USDOJ, 2013, 2014) indicates that most racial hate crimes target cisgender men (men who were assigned male at birth) and most anti-LGBT hate crimes target White cisgender men. This would suggest that intersectional identities may not increase risk of hate crime victimization in general. However, a close look at the anti-transgender homicides reported by the Gender Public Advocacy Coalition (Wilchins & Taylor, 2006) suggests that transwomen are at greater risk of bias-motivated homicide than are transmen, and that risk is further magnified for transwomen of color.

An illustrative case of intersectional hate crime is the string of assaults committed by

Tyrelle Shaw in 2015 (Barker, Wright, & Goodman, 2015; Wright, 2015). Shaw, a young Black man, sought out Asian women as his targets, travelling to locate potential victims in areas of

New York City known to have a large Asian population. Comments on Shaw’s social media accounts indicate that he had planned to target Asian women because he developed an unfavorable view of Asian women after being rejected romantically by more than one Asian woman. His blog posts had publicly bemoaned the coupling of Asian women with White men and tracked instances of Asian women spurning his compliments. Ultimately, Shaw, who suffered from untreated mental illness, hung himself and was not tried for the offenses. In this case, the offenses were not motivated only by gender or by race, but by the intersection of the two.

The UCR contains a category for “multiple-bias” hate crime incidents, but this does not appear to capture the phenomenon of intersectional victimization. The UCR reports that there were 6 multiple-bias hate crime incidents reported in 2013, with a total of 12 victims (USDOJ,

2014). This muddies the picture, as it is possible that victims who were victimized in the same incident were from different groups (e.g., a Black person and a Latina/o person assaulted at the same time), rather than each individual possessing multiple marginalized identities.

Furthermore, crimes against lesbian women tend to be categorized as being driven by sexual orientation alone, although it is likely that offenders select gay women in part because they are women or because they defy traditional gender norms in their love-object choice or expression of gender. Intersectional identities are a complicated and understudied aspect of hate crime victimization, and future research should address this issue.

Hate crimes against other groups. Over the last ten years, many states have introduced bills to add homeless persons as a protected class in hate crime legislation (National Coalition for the Homeless [NCH], 2007). Unprovoked homicides of homeless people were reportedly three times more common than other hate crime homicides counted by the FBI between the years 2004 and 2006 (NCH, 2007). Wacholtz (2009) investigated 47 individuals who experienced homelessness in New England. The participants reported frequent encounters with hate speech from passersby. Participants were commonly told that they were worthless and should find employment. They also reported frequent assaults, typically having objects thrown at them while being verbally insulted. One woman reported that a man kicked her in the face when she was out on the sidewalk, and one man reported that a stranger punched him directly in the face after berating him.

The Amish have also been targets of hate crime. Byers and Crider (2002) interviewed 8

White men who engaged in claping, the harassment, intimidation, and victimization of Amish people. The offenders described acts of claping that they had engaged in during adolescence.

The most commonly reported offense was intimidation. Offenders stated that claping was a way for them to combat boredom; driving around in a car or truck with peers for the purpose of targeting the Amish was a customary form of entertainment in the offenders’ communities.

Some respondents considered claping a rite of passage, and most reported that this was socially accepted practice in their communities. These activities were reportedly unplanned and rarely resulted in negative consequences for the offending parties. Respondents’ remarks indicated that they perceived the Amish as being different, inferior, and deserving of punishment due to their distinctive style of dress and rejection of the dominant culture mores.

Psychological effects of hate crime. Hate crimes serve a symbolic function, sending a message to not just victims, but also their communities (Iganski, 2001). Beyond the effects on the immediate victim(s) of the offense, hate crimes also cause humiliation and arouse fears in targeted groups (Garnets, Herek, & Levy, 1990; Jenness & Grattet, 2001). As Grigera (1999) notes, “A violent offense motivated by bigotry can cause a broad ripple of frustration among members of a targeted group; and a violent hate crime can quickly spread feelings of terror through an entire community” (p. 2).

The effects appear to be more severe than are the effects of non-bias crimes (e.g., Herek,

Cogan, & Gillis, 2002; McDevitt, Balboni, & Gu, 2001). Victims of bias-motivated violence are more likely to experience psychosomatic symptoms, such as anxiety, fatigue, anger, and concentration problems (Ehrlich, Larcom, & Purvis, 2003; Herek et al., 2002). These effects reach far beyond the immediate victim. Young (1990) explains:

The oppression of violence consists not only in direct victimization, but in the daily

knowledge shared by all members of oppressed groups that they are liable to violation,

solely on account of their group identity. Just living under such a threat of attack on

oneself or family or friends deprives the oppressed of freedom and dignity, and

needlessly expends their energy (p. 62).

According to Lyons and Roberts’s (2014) investigation of NIBRS data from 2005 to

2010, only 31.6% of bias-motivated incidents are cleared, as compared to 41.4% of non-bias incidents. Some have attributed low clearance rates for hate crime cases to the difficulty of surmounting the burden of proof required to prove that an offender’s behavior was motivated by the victim’s group membership. As Padgett commented in 1982, “racial and religious violence persists in part because existing state legislation and state court systems fail to adequately deter

and punish perpetrators of those crimes” (p. 104-105). Despite many legislative changes, legal scholars (e.g., Morsch, 1992) and LGBTQ scholars (e.g., Bronski, Pellegrini, & Amico, 2013) contend that this is still the case and extends to LGBTQ individuals as well.

Riedel and Jarvis (1998) note that low clearance rates contribute to a variety of negative community outcomes, including distrust of the police, secondary traumatization of victims’ family members, and intensification of fear of victimization. These effects may be particularly deleterious in marginalized communities, for whom these negative states are already a reality.

Furthermore, there is some evidence that clearance rates for hate crimes favors groups that already enjoy societal privilege. Crimes with White victims generally are perceived as more serious and tend to have the highest rates of clearance (Jacobs, Qian, Carmichael, & Kent, 2007), and research by Wilson and Ruback (2003) indicates that, across the state of Pennsylvania, anti-

White hate crime incidents had a higher clearance rate that did anti-Black hate crime incidents, despite their general lack of congruence with perceptions of hate crimes as constituting only attacks on marginalized groups. As Grigera (1999) notes, “Apart from their psychological impact, such bias-motivated crimes continue the oppression of marginalized groups, leaving victims and members of the victims’ communities feeling isolated, vulnerable and unprotected by the law” (p. 2).

Bias-Motivated Homicide

Empirical research about bias-motivated homicides and bias-motivated homicide offenders is severely lacking. Most hate crime samples include a range of violent and nonviolent offenders. Few studies have directly addressed this particular subset of hate crimes.

Prevalence. Homicides appear to make up only a small minority of hate crime incidents

(e.g., Langton & Planty, 2011; USDOJ, 2012, 2014). NCVS data indicate that only 8 bias-

motivated homicides occurred in 2009 (Langton & Planty, 2011), and UCR data indicate that only 5 bias-motivated killings were reported in 2013 (USDOJ, 2014). Between 2005 and 2010, just 14 (0.2%) of the hate crimes reported to NIBRS were categorized as homicides (Lyons &

Roberts, 2014). However, studies that have extracted their samples from open source databases

(Gruenewald, 2011; Gruenewald & Kelley, 2014) have estimated the rates of bias-motivated homicide to be much higher than what is reflected in the UCR.

Offenders. Fisher (2007) investigated the McDevitt, Levin, and Bennett (2002) typology, applying the features they designated to a sample of 91 closed bias-motivated homicides. This sample was further investigated by Fisher and Salfati (2009). Although the authors of the typology did acknowledge that there are overlaps among the three (Levin &

McDevitt, 1993) and then four (McDevitt et al., 2002) categories, Fisher (2007) and Fisher and

Salfati (2009) further illustrated, using an analytic technique known as Smallest Space Analysis

(SSA), that the four categories proposed by McDevitt and colleagues (2002) were not clearly delineated. They also found that the thrill-motivated group described by McDevitt and colleagues might more aptly be divided into two subcategories: one which was concerned with treatment of the body – indicating a sexualized desire for control – and one which appears to be primarily motivated by a general aggressive urge.

The retaliatory bias-motivated homicides were characterized by a quick method of killing the victim, typically in areas that often experience hate crimes or in which the victim was not representative of the general population. Fisher (2007) did not find a discernable subset of crime-scene behaviors associated with mission-motivated hate homicides. Finally, defensive bias murders appear to be characterized by a lack of forensic awareness and planning, the presence of multiple injuries, and the use of blunt or cutting instruments.

Lynching. Turpin-Petrosino (2009b) suggests that the long history of lynching in the

United States has a strong and unacknowledged connection to modern hate crime. Dozier (2002) reported that “[b]etween 1882 and 1919 more than three thousand African Americans were lynched, mostly in the South, an average of almost one person every four days” (p. 29). The lynching of Blacks was such common practice during the post-Civil War era (approximately

1865-1949) that it was impossible to keep an accurate count of the number of offenses

(Perlmutter, 1992; Turpin-Petrosino, 2009b). In 1866, the Ku Klux Klan became particularly active in the South and membership rose to nearly 5 million (Potok, 2001). The Klan is suspected of murdering over 1,500 Black people in the state of Georgia alone during this post- war surge in activity (Berlet & Lyons, 2000).

Lynching has been noted among other marginalized groups as well. An investigation by

Carrigan and Webb (2003) documented at least 597 lynchings of Latinos between 1848 and

1928. The frequency of lynching has reportedly dropped since the 1930s. Individual cases, such as the anti-LGB lynching of Mathew Shepard, indicate that the practice of lynching has continued into modern times and that not all lynchings are racially or ethnically motivated.

Anti-LGBT homicides. Gruenewald and Kelley (2014) reviewed anti-LGBT homicide cases between 1990 and 2010 extracted from the Extremist Crime Database (ECDB), an open- source online database. Their sample size of 121 solved cases includes cases that were not charged as hate crimes and far exceeds the number of anti-LGBT homicides reported in the UCR during that time period. Gruenewald and Kelley (2014) identified two broad categories of anti-

LGBT homicide offenses. Predatory homicides consist of planned acts of violence against members of the LGBT community. These offenses did not involve provocation by the victim.

One subtype of predatory homicides is representative homicide. In representative homicides, the

offenders select victims in order to communicate a message about the community to which the victim belongs. These offenders either stalked their victims prior to the offense or lured their victims to a secluded area to facilitate the offense. Another subtype of predatory homicide is instrumental homicide. These cases exhibited signs of secondary gain, namely monetary or material profit. Many of these cases were not investigated as hate crimes due to this financial aspect; however, the authors perceived that these victims were clearly selected based on their sexual orientation or gender identity.

The other category of anti-LGBT homicide identified by Gruenewald and Kelley (2014) was termed responsive homicide. These offenses lacked planning and were more emotionally- driven. About half of the offenses in this sample were responsive, with offenders finding their victims offensive. One subset of responsive homicides was termed gay bash offenses. Gay bash offenders felt disrespected or threatened by their victims, commonly as the result of a verbal exchange initiated by the offender. The second subset of responsive homicides were undesired romantic or sexual advance offenses. These cases are also known as gay panic or trans panic cases, depending on the identity of the victim. Essentially, the offenders in these cases lashed out violently after their victims made some advance that the offender found threatening. These offenses commonly occurred in private, often with the influence of drugs and/or alcohol on the victim and/or offender. The last subset of responsive homicides were mistaken identity offenses.

This author takes issue with the way in which Gruenewald and Kelley (2014) chose to describe these offenses. They state that “a male offender participated in a sexual encounter with another anatomically male victim who was perceived to be female” (p. 1141). The use of the term

“mistaken identity” denies the victims’ right to identify their gender as they experience their gender and shifts a portion of the blame onto the victim by insinuating that they were deceptive

about their gender and this provoked the offender. That aside, in these cases, when the offenders discovered male genitalia, they felt humiliated and their violence was a response to this humiliation. Most victims in this category were transwomen.

Overall, Gruenewald and Kelley (2014) found that anti-LGBT homicide offenders often acted alone and killed their victims without others present. They used slurs to derogate their victims in at least 26% of cases, but this could not always be determined in the absence of surviving witnesses. About 16% of offenders spoke of their crimes to others prior to arrest, and more than 50% eventually admitted that sexual orientation or gender identity was the impetus for the homicides they committed. The sheer number of cases included in this sample deals a significant blow to the validity of the UCR’s limited anti-LGBT hate crime statistics.

Tomsen’s (2002, 2006, 2009) research on anti-LGBT homicides in Australia, based on interview and archival data, has revealed two general classifications of death scenarios: public and private. In the public scenario, the offender attacks the victim in a public place; in the private scenario, a confrontation between offender and victim occurs in private (such as at the victim’s home), resulting in the offender attacking the victim. Tomsen’s (2002) research also indicates that most anti-LGBT homicides are carried out by young men from socially disadvantaged backgrounds. He postulated that many of these offenders had engaged in same- sex sexual activity prior to their offenses without identifying as gay and noted perpetrators’ exaggerated concerns about their own masculinity. A portion of the homicides were predatory, in which the offender sought out LGBT victims with the purpose of committing violence; these offenses were the most likely to involve multiple offenders. Situational factors were also found to play a considerable role, with elements such as alcohol and drug use and anonymous sexual cruising augmenting the traditional hate motive in many cases (Tomsen, 2002).

The Gender Public Advocacy Coalition asserts that at least 51 transphobic homicides of individuals under the age of 30 occurred in the United States between the years of 1995 and 2005

(Wilchins & Taylor, 2006). Of these victims, the majority were Latina/o or Black MTF (male to female) transgender individuals. Almost all were killed by men under the age of 30. Only 46% of these homicides were cleared, as compared to the 62% clearance rate for all homicides nationally in 2005, the last year included in the study. Many cases had clear indicators of bias motivation. Several were the product of a so-called trans panic situation, in which the victim’s transgender identity was discovered by the offender. Nonetheless, few of these offenses were investigated as hate crimes.

Problems with Existing Hate Crime Data

Large inconsistencies among data sources suggest significant problems with the collection and interpretation of hate crime data. In addition to the U.S. Department of Justice, the Anti-Defamation League (ADL), New York’s Antiviolence Project (AVP), the National

Asian Pacific American Legal Consortium (NAPALC), and the National Gay and Lesbian Task

Force (NGLTF) all independently collect hate crime data. Data reported by these organizations point to significant underreporting of hate crimes by the UCR. For example, in 1994, the UCR

(USDOJ, 1995) reported 211 instances of anti-Asian hate crimes across the precincts reporting across the United States. Meanwhile, NAPALC reported 452 anti-Asian hate crimes – more than twice the FBI’s number. Similarly, in 1997, the UCR (USDOJ, 1998) reported 990 anti-gay hate crimes, while the NGLTF recorded a whopping 2,245 – again, more than twice the number reported to the FBI.

One source of discrepancy is very likely to be variation in definitions of hate crime used by different researchers, organizations, and jurisdictions. While the federal government has

decreed a set of protected categories to be included as viable motives of hate crimes, not all states recognize these same categories, nor do researchers, who may narrow or expand the federal definition to suit their purposes. The federal definition and the groups protected have also changed over time. As Berk, Boyd, and Hamner (1992) have pointed out, these various definitions have made it “difficult to know what is being counted as hate motivated and what is not” (p. 125).

Sampling procedures are also likely to contribute to these discrepancies. Data provided by individual police precincts and by the UCR are likely to be affected by individuals’ failures to report victimization or to report the hate content of the incidents they experience. Research (e.g.,

Herek, 1989; Herek, Gillis, & Cogan, 1999; Langton & Planty, 2011; Wilson, 2014) indicates that more than half of hate crime victims do not notify the police of their victimization. Hate crime victims from certain marginalized groups have pragmatic reasons for not reporting their victimization; for example, Perry (2001) highlighted the fact that many closeted members of the

LGBTQ community avoid contact with not only the police, but also with advocacy organizations or publications that are common recruitment sites for studies of anti-LGBTQ violence. Most anti-LGBTQ hate crimes are not reported (Herek, 1989; Herek et al., 1999, 2002), in part due to high rates of victimization of LGBTQ individuals by police. LGBTQ individuals might also avoid reporting victimization or the hate motive behind victimization to avoid publicizing their sexual orientation or gender identity (Herek et al., 2002). NCAVP data (Langton & Planty,

2011) indicates that many hate crime victims do not report their victimization to the police because they believe that the police cannot or will not help; others were afraid of reprisal.

Additionally, some hate crimes, particularly racial/ethnic crimes, may be gang-related as well as bias-motivated (Umemoto & Mikami, 2000); in these cases, law enforcement may not

acknowledge or record the hate motive, favoring the gang involvement as the more significant motive or the easier motive to argue in court.

Finally, when districts fail to report to the UCR, this can significantly lower the estimated number of hate crimes, as well as skew numbers. For example, there is reason to believe that hate crimes enacted by or against African-Americans may be underestimated due to unrealistic reporting by Mississippi, Louisiana, and Georgia – states with high proportions of African-

American citizens and a potentially lenient attitude toward racially motivated offenses (Levin,

2009; U.S. Census Bureau, 2008). Similarly, the lack of any UCR hate crime data from

Honolulu, Hawaii for 2008, 2009, 2010, 2011, and 2012 (ADL, 2014) may lead to an incomplete or inaccurate understanding of hate crimes involving or affecting Pacific Islanders, Asians, and multiracial individuals, as these groups together comprise the majority of Hawaii’s population

(U.S. Census Bureau, 2014).

Gaps in the Literature

Much of the extant hate crime literature (e.g., Dunbar et al., 2005; Levin & McDevitt,

1993; McDevitt et al., 2002) lumps bias-motivated offenders into a single group, neglecting the possible significance of the type of offense and the identity group targeted by the offender. This presumption of heterogeneity is likely to mask any real effects based on type of offense (e.g., vandalism versus homicide), as well as effects based on victim selection (e.g., Black victim versus gay victim). Furthermore, most psychological research on hate crime offenders has been focused on the offenders’ stable internal traits and attitudes, while external and situational influences have been undervalued. External factors may play a role in hate crime commission, as they do in any other behavior (Ross, 1977). In light of the work of theorists such as Mischel

(1968) and Ross (1977), who espouse the significance of situational factors in determining

human behavior, Craig (2002) pointed out a corresponding weakness in the current hate crime literature: “By focusing exclusively on the deviancy of the perpetrators, one risks underestimating the impact of the situation and the greater cultural forces” (p. 96).

Research indicates that hate crimes are often committed by small groups of friends or associates (e.g., Craig, 2002; Dunbar, 2003). This suggests that socialization may play an important role in explaining hate crimes, but as Blazak (2009) suggests, researchers may be:

spend[ing] too much time focusing on members of organized hate, when the vast majority

of individuals responsible for the day-to-day terror of hate crimes have nothing to do with

groups like the Ku Klux Klan and the National Socialist Movement (p. xiiv).

In addition to understanding offenders’ psychodynamics, forensic psychologists would benefit from a deeper understanding of the social dynamics underlying the commission of hate crimes.

Homicide, in particular, has been theorized to be a “situated transaction” in which the victim plays some role in precipitating his or her own death (e.g., Luckenbill, 1977; Wolfgang,

1957). Indeed, UCR statistics support the idea that homicide generally does not often occur at random; in recent years, the leading cause of murder has been an argument or brawl between the victim and the offender (USDOJ, 2012, 2013, 2014). As research by Alden and Parker (2005) has indicated, macro-level factors are also predictors of anti-LGBT hate crime victimization.

Their research indicated that, for example, areas with less gender equality have less hate crime victimization based on sexual orientation. They also found correlations with education level and racial demographics. These social forces are beyond the scope of this study, but future research should strive to situate bias-motivated incidents in their historical, political, and economic contexts.

Additionally, there does not appear to be any longitudinal or prospective research on hate crime offenders. Until this is ameliorated, it will remain difficult to identify the developmental factors that lead to later hate crime perpetration. This dearth of information also renders it difficult to develop effective intervention and rehabilitation for offenders.

Chapter 3

Current Study

As hate crime scholar Perry (2001) states, hate crime “is a socially situated, dynamic process involving context and actors, structure, and agency” (p. 1). Such a complex phenomenon warrants an in-depth research approach, in which offenses are investigated from multiple angles. While it is true that endorsement of negative stereotypes about a group tends to predict negative or unfriendly behavior toward members of that group (e.g., Dovidio, Kawakami,

& Gaertner, 2002), this alone clearly has not been enough to distinguish bias-motivated homicide offenders from their criminal and noncriminal counterparts. Stereotype endorsement itself may be a necessary precondition of committing bias-motivated homicide, but it is evidently not a sufficient condition of committing such an offense, as research (e.g., Devine, 1989) indicates that most people tend to unconsciously endorse these same negative stereotypes, while bias- motivated homicide remains statistically rare (e.g., Langton & Planty, 2011; USDOJ, 2014).

Looking beyond purely internal factors, Wolfgang (1957) reported that offenders often feel

“provoked” by their victims’ behavior prior to the offense. Similarly, Luckenbill (1977) referred to homicides as “situated transactions.” His review of 70 homicide cases revealed that most homicides were directly or indirectly precipitated by the victim’s words or actions. Furthermore, social psychology research has suggested that there are strong situational triggers for the activation of negative out-group stereotypes, such as threats to self-esteem (Kosic, Mannetti, & Livi,

2014), priming with racially relevant visual stimuli (Bargh & Pietromonaco, 1982; Duncan,

1976; Lepore & Brown, 1997; Sager & Schofield, 1980), and situations requiring quick interpretation of ambiguous stimuli (Devine, 1989). Threats to self-esteem, in particular, have been

associated with an aggressive response in prior research on criminal behavior (e.g., Feshbach,

1964).

While there is a significant body of literature on the origins of discrimination and hate crime in general, there has been little research devoted specifically to bias-motivated homicides. Furthermore, although sociologists and criminologists have provided general explanations for the hate crime phenomenon at the societal level, there is a dearth of literature regarding what may psychologically or situationally predispose specific individuals to commit bias-motivated homicide offenses. This study aims to fill a critical gap in the literature by investigating psychological, situational, and behavioral aspects of these crimes and their offenders. The following goals will be addressed:

1. To develop a profile of the bias-motivated homicide offender, including

demographic, psychological, situational, and crime scene behavioral features;

2. To compare bias-motivated homicide offenders based on group targeted to discern

any differences in demographic, psychological, situational, and crime scene

behavioral features;

3. To evaluate the role of expressive and instrumental behaviors in bias-motivated

homicide offenses;

4. To examine the role of intersectional marginalized identities in bias-motivated

homicide offenses;

5. To evaluate the utility of the McDevitt, Levin, and Bennett (2002) hate crime

typology as it applies to a sample of bias-motivated homicides;

6. To propose a new, historically-informed bias-motivated homicide typology;

7. To extrapolate from these observations any patterns or methods that may enhance the

investigation of bias-motivated homicides; and

8. To suggest interventions that may mitigate risk, in hopes of preventing the

commission of future bias-motivated homicides.

Hypothesis 1. In the United States, crimes against Asians and Latina/os have historically been driven by immigration surges and justified by perceived economic competition (e.g.,

Bankston, 2006; Bronski, 2011; Katel, 2009; Stacey et al., 2011). Crimes against African-

Americans have symbolized efforts to establish boundaries between White and Black society and served to maintain a hierarchical social order in post-slavery America (e.g., Levin, 2009; Perry,

2001). Additionally, male members of marginalized racial and ethnic groups have been the victims of crimes specifically intended to establish boundaries and punish interactions between

White women and men of color (e.g., Bankston, 2006; Bronski, 2011). These crimes have often involved vigilante mobs, and hate groups have been established around the task of keeping people of color in “their place” in the social order (e.g., Turpin-Petrosino, 2009b). In this way, these offenses may have less to do with the particular victim than with the victim’s membership in a particular group.

Crimes against sexual and gender minorities have not historically been driven by this same type of competition, but rather by a drive to reinforce traditional gender norms. Anti-

LGBT offenders use crime to regulate masculine heterosexual norms and demonstrate their own masculine identity, which does not permit same-sex sexual activity (e.g., Franklin, 2000; Kelley

& Gruenewald, 2015; Tomsen, 2002). Victims are most likely to be targeted because of their violation of these norms; therefore, the offense may be more personal in nature.

As a result, it is reasonable to expect that crimes against people of color and crimes against sexual and gender minorities will differ in meaningful ways, including the following:

A. Racial/ethnic bias-motivated homicides will, on average, involve more offenders and

more victims as compared to anti-LGBT bias-motivated homicides.

B. Racial/ethnic bias-motivated homicides will be more likely to involve offenders who are

associated with a group organized around out-group prejudice as compared to anti-LGBT

bias-motivated homicides.

C. Anti-LGBT bias-motivated homicides will exhibit more expressive violence than will

racial/ethnic bias-motivated homicides.

Hypothesis 2. If bias-motivated homicides differ significantly based on the group targeted, then it logically follows that this factor – often easily observed from the crime scene or gathered from witnesses – should be included in any typology designed to capture the nature of bias-motivated homicide offenses. The Levin and McDevitt (1993) and McDevitt et al. (2002) typologies fail to reflect the significance of victim identity – a feature which drives the offender’s victim selection. Furthermore, previous research has determined that most bias- motivated crimes, such as those used to build the leading hate crime typology, are low-level offenses (e.g., Garafalo & Martin, 1993); bias-motivated homicides are, in fact, exceedingly rare and therefore were likely to have comprised only a small portion of the McDevitt et al. (2002) sample.

Additionally, when other researchers have systematically applied the existing typology to other samples of bias-motivated offenses, the typology has come up short. This was aptly demonstrated in Phillips’s (2009) study of bias-motivated offenses in New Jersey, in which it was found that the representative body of offenses studied was predominated by the Thrill type

(43.3%) with a much smaller portion of Phillips’s sample fitting this type’s definition than in the original sample (66%; McDevitt et al., 2002). Furthermore, 36.6% of cases in Phillips’s (2009) study were found to be “Unclassifiable” using the typology, and the rate of interrater agreement for her study was 73% (although the author did not report the method used to assess interrater agreement). Therefore, the McDevitt et al. (2002) typology is not expected to be a valid and reliable tool for the categorization of bias-motivated homicides, as demonstrated by poor fit to the data and poor interrater reliability.

Hypothesis 3. Very little literature has addressed the role of the expressive-instrumental spectrum in bias-motivated offenses, let alone bias-motivated homicides. Although many researchers (e.g., Alvarez Cussin, 2017; Last & Fritzon, 2005; Salfati & Canter, 1999; Trojan &

Krull, 2012) have demonstrated a relationship between expressive violence and victim-offender relationship, this has not been sufficiently examined in the context of bias-motivated homicide.

Bias-motivated crime is symbolic in nature and typically does not target known subjects; nonetheless, Bell and Vila (1996) found a significantly higher incidence of overkill among gay male homicide victims as opposed to straight male homicide victims, regardless of victim- offender relationship. Fisher (2007) looked at one sample of bias-motivated homicides and also found variations in expressive and instrumental violence that appeared to be untethered from the victim-offender relationship, but there was no psychological explanation offered for this phenomenon. It is, therefore, predicted that expressive crime scene behaviors in bias-motivated homicides will not be predictive of a prior victim-offender relationship, though this is contrary to what has been demonstrated in other types of homicide offenses (e.g., sexual homicide).

Hypothesis 4. The history of post-immigration bias-motivated violence shows that bias- motivated offenders have often victimized people with whom they have had no prior interaction

– marginalized individuals who are simply in the wrong place at the wrong time. Individual victims have been attacked by entire mobs of people, despite the fact that it is quite unlikely that an individual who does not speak English could somehow provoke an entire crowd of English- speaking Americans. From a psychological perspective, we know that bias-motivated offenders have been found to engage in cognitive distortions, such that any member of a target group is

“offensive” or “provocative” by their mere presence and thus a potential target of violence (e.g.,

Byers, Crider, & Biggers, 1999; Sun, 2006; Sykes & Matza, 1957). Therefore, it appears that the nature and perception of provocation in bias-motivated offenses may be different from other crimes. Building on Hypothesis 3, expressive crime scene behaviors in bias-motivated homicides will not be positively associated with provocation by the victim, despite what has been demonstrated in other types of homicide offenses (e.g., domestic homicide).

Hypothesis 5. Anecdotally, cases such as the murder of Kerrice Lewis, a young Black lesbian woman who was shot 15 times and burned alive while trapped in the trunk of her car in

December 2017, suggest the possibility that victims with multiple marginalized identities might experience higher or more excessive levels of bias-motivated violence than those victims without multiple marginalized identities (Hermann & Bui, 2018). Lewis’s murderer allegedly shot and killed a young Black heterosexual man just hours prior to murdering Lewis. Both victims were apparently acquaintances of the murderer; however, in the earlier offense, fewer shots were fired and the victim was not burned. The excessive, sadistic violence of Lewis’s murder suggests a level of animosity that went above and beyond that which this particular offender had demonstrated in other offenses.

Some research has suggested that individuals who possess more than one marginalized identity (e.g., both Black and lesbian) report more frequent instances of everyday discrimination

in the form of microaggressions. For example, Nadal, Mazzula, Rivera, and Fujii-Doe (2014) found that Latina women reported more frequent microaggressive experiences in school and in the workplace than did Latino men. Though the topic of intersectional identities has been largely ignored in the hate crime literature, one study (Wilchins & Taylor, 2006) has suggested that transwomen of color are at particularly high risk of being the victim of bias-motivated homicide as compared to transmen and White transwomen. Furthermore, Meyer’s (2010) study indicated that LGBT hate crime survivors with additional marginalizing identities (e.g., low-income, person of color) experienced higher levels of bias-motivated violence than their White, middle- class LGBT counterparts, whose victimizations were less violent overall. Based on these findings, it is expected that there will be more expressive violence evident in bias-motivated homicides in which the victim identifies with more than one marginalized identity as compared to bias-motivated homicides in which the victim identifies with one or no marginalized identities.

Hypothesis 6. The leading typology largely ignores the identity of the victim and the crime scene behaviors, two of the most evident features of a bias-motivated homicide crime scene. It may be more appropriate to include these variables as the major determiners of a functional bias-motivated homicide typology. Therefore, a new typology is proposed, and a preliminary analysis conducted, which acknowledges the roles of victim identity, provocation, and expressive violence in differentiating bias-motivated homicide offenses and predicting the offender’s identity.

Chapter 4

Methodology

Procedure

This archival study was reviewed by the Institutional Review Boards of the FBI and the

John Jay College of Criminal Justice and found exempt. Cases were obtained from a non- random national sample of closed, fully adjudicated case files provided by the FBI’s Behavioral

Analysis Unit for research purposes. All identifiers have been removed, and only aggregate data are reported in order to protect the anonymity of victims, offenders, witnesses, and family members.

Information was drawn from a variety of resources within the cases files, including police reports, autopsy reports, crime scene photos, witness statements, psychological assessments, and offender statements. According to Maxfield and Babbie (2005), one advantage of utilizing secondary or archival data is that it is “cheaper and faster than collecting original data” (p.

347). One limitation of using secondary data, however, is that this data is sometimes not collected in a consistent and systematic fashion. However, as Salfati (2000) reports, when variables are coded dichotomously (i.e., as either present or absent), police files are suitable for research purposes. When appropriate, variables of interest have been coded dichotomously; this method has been suggested by Canter and Heritage (1990) as providing the greatest level of consistency when dealing with similar data. Exceptions include victim age, offender age, number of victims, and number of offenders, which have been recorded as continuous variables.

The data for this study were collected by the Principal Investigator (PI) and a master’s level research assistant. Both researchers involved in the study have completed graduate-level coursework on assessment methods under the supervision of a licensed clinical forensic

psychologist. The research assistant was trained by the PI in the data collection method used in previous studies (e.g., Davis, 2011). Researchers read each item in a case file and coded variables based on official statements, unequivocal evidence (e.g., autopsy photos), and inter- source agreement (e.g., consistency among witness statements). Researchers were conservative in their interpretation of the data; if a variable was not explicitly addressed in the case file or there was a lack of agreement among sources within the file, the variable was coded as

“Unknown.” Cases coded by the research assistant were reviewed by the PI to ensure accuracy and consistency. Discrepancies were discussed, and consensus was reached prior to the final recording of data.

A standardized coding sheet was created by the PI to systematize the data collection (see

Appendix A). Operational definitions for variables of interest are included in Tables 1 through 3. Basic demographic information (e.g., age, race, gender) was collected on offenders (see Table 1) and victims (see Table 2). Offender psychological variables investigated include but are not limited to: history of substance abuse, education level, and history of childhood abuse (see Table 1). Situational variables include but are not limited to: circumstances immediately prior to the crime, location of the crime, relationship between victim and offender, and offender intoxication at the time of the offense (see Table 3).

Measures

Data were collected using the standardized coding sheet created by this author for this study (see Appendix A). This coding sheet was based on the coding sheet used by this author for previous studies of homicide offenses (e.g., Davis, 2011). The PI provided the research assistant with didactics and supervision for the coding of these instruments. Two ad-hoc scales of expressive and instrumental features were created after review of the relevant research; these two

scores are also recorded as continuous variables, and the items comprising the scales can be found in Appendix B.

Sample

The study investigates a non-random sample of cases occurring across the United States.

Sample size was limited by the number of available cases in the archive that fit the study criteria.

Cases were compared to one another to ensure that no cases were duplicated in the dataset.

First, cases were selected for inclusion in the sample based on the aforementioned definition of hate crime used by the FBI: “criminal offenses motivated, in whole or in part, by the offender’s bias against a race, religion, disability, sexual orientation, ethnicity, gender, or gender identity” (USDOJ, 2015, p. 4). The FBI has acknowledged difficulties in determining an offender’s motivation; therefore, following their guidelines, this study includes those cases in which “investigation reveal[ed] sufficient objective facts to lead a reasonable and prudent person to conclude that the offender’s actions were motivated, in whole or in part, by bias” (USDOJ,

2015, p. 4). An offense was considered bias-motivated if it involved one or more of the following behavioral indicators: statements made by the offender attesting to bias motive prior to, during, or after the commission of the offense; the use of slurs or derogatory language by the offender in describing his victim(s) prior to, during, or after the commission of the offense; and emblems of hate at the scene of the crime. While many of the offenses in the sample were tried and prosecuted as bias-motivated offenses, this sample is expanded to include cases that meet the most current USDOJ criteria but may not have been tried or prosecuted as bias-motivated, due to differences in hate crime statutes by jurisdiction and over time. A sample of the bias indicators used to make this determination appears in Appendix C.

Second, only those bias-motivated offenses that caused the death of one or more individuals were included in the sample. Cases in which there were additional offenses or damages in the course of the homicide (e.g., robbery) were not excluded from the sample. Attempted homicides were excluded due to the inability to retrospectively discern the offender’s intent to kill from the available data.

Fifty-eight incidents of bias-motivated homicide with a total of 64 victims and 95 offenders comprise the sample. Offenses occurred between the years 1987 and 2003. The sample represents offenses occurring in at least 46 different zip codes within the United

States. The sample was evenly split between anti-LGBT offenses (n = 29; 50.0%) and racial/ethnic offenses (n = 29; 50.0%).

For the purposes of this study, one offender was designated as the “primary offender” for each case in order to avoid oversampling data from those cases with multiple offenders. In cases with multiple offenders, an offender was designated as primary if: 1. he or she was determined by law enforcement to have played the most lethal or instrumental role in the offense, or 2. he or she was the offender about whom the case file contained the most information (typically due to overlap with the first criterion). It should also be noted that the offenders working in concert were most often demographically similar (as has been reported previously in the relevant literature [e.g., Fisher, 2007]). As with the cases with multiple offenders, in cases with multiple homicide victims, one victim was selected as the primary victim, to avoid oversampling of the crimes of multiple-victim offenders.

Statistical Analyses

Basic descriptive statistics and frequency tables were used to generate a comprehensive description of the bias-motivated homicide offender based on the full sample. The sample was

divided by type of bias (i.e., anti-LGBT or racial/ethnic), and descriptive statistics (frequencies and distributions) were analyzed to create more specific profiles by target group. For between- groups comparisons of homicides by type of bias, Chi-square analyses were used to analyze dichotomous variables, with Fisher’s Exact Test used as conservative test of significance to address the small subsample sizes. Independent samples t-tests and Analyses of Variance

(ANOVA) were used to evaluate differences in the quantitative variables. The simplicity and clarity of these statistics make them amenable to communication of results to audiences beyond the psychological academe. Furthermore, the small sample size and missing data in this dataset violate the assumptions of many more sophisticated statistical analyses that might otherwise be applicable. Between-groups analyses were also conducted to compare offenses with provocation to offenses without provocation, offenses with victims of multiple intersecting marginal identities to offenses with victims without intersecting marginal identities, and offenses in which the victim and offender had a previous relationship to offenses in which the victim and offender were not known to one another. Interrater reliability of the Levin, McDevitt, and Bennett (2002) typology was evaluated using Cohen’s Kappa.

Chapter 5

Results

Total Sample

The 58 offenses recorded in the sample occurred between 1987 and 2003. Thirty-four cases (58.6%) involved a single known offender working alone. Twenty-four cases (41.4%) involved two or more known offenders working in concert. Eleven cases (19.0%) involved three or more known offenders. Two cases (3.4%) involved four or more known offenders. When offenders worked together, accomplices were of the same gender as the primary offender 95.8% of the time (n = 23) and the same race as the primary offender 83.3% of the time (n = 20).

Offender characteristics. The mean age of the primary offenders was 25.89 years (n =

55; SD = 9.01). The youngest primary offender was 15 years old at the time of the offense; the oldest primary offender was 53 years old. Juveniles under the age of majority (18 years) accounted for 8.6% (n = 5) of the primary offenders identified. Accomplices were, on average, younger than the primary offenders. When more than one accomplice was identified, the accomplices were typically close in age to one another. In cases where abetting offenders were identified, the mean age of the accomplices (n = 34) was 21.91 years.

In 46.6% of cases sampled (n = 27), the primary offender was identified as White or

Caucasian. In 29.3% of cases sampled (n = 17), the primary offender was identified as Black or

African-American. In 19.0% of cases sampled (n = 11), the primary offender was identified as

Hispanic or Latina/o. In 1.7% of cases (n = 1), the primary offender was identified as Asian. In

1.7% of cases (n = 1), the primary offender was identified as multiracial. One case file (1.7%) did not report the race or ethnicity of the offender.

All but one of the primary offenders were identified as male (n = 57; 98.3%), with the remaining primary offender identified as female (1.7%). In cases in which more than one offender participated, all but one of the accomplices were identified as male (n = 36; 97.3%).

About three-quarters (n = 43; 74.1%) of offenders were identified as heterosexual. One offender in the sample (1.7%) was identified as gay. No sexual orientation was identified for 24.1% (n =

14) of offenders in the sample.

Only four offenders’ religious affiliations were available (6.9%); these offenders were all identified as Christian. Intelligence level was not reported for most offenders in the sample; one offender was identified as functioning in the Average range (1.7%), and one offender was identified as functioning in the Above Average range (1.7%). Three offenders (5.2%) were reported to have a learning disability.

Eight offenders (13.8%) were identified as being undomiciled at the time of their offenses. Thirteen offenses (22.4%) were led by an offender known to be affiliated with a street gang or White Supremacist organization (e.g., Aryan Nation). At least 15.5% (n = 9) of offenders experienced a dysfunctional family environment during their youth, as defined by a traumatic loss or disrupted home life (e.g., death of a close family member, parent with substance abuse). At least four offenders (6.9%) were known to have a history of childhood abuse or neglect. At least three offenders (5.1%) were removed from the custody of their biological parent(s) during childhood. Two offenders (3.4%) were exposed to maternal substance abuse in their youth.

Relationship status at the time of the offense was available for 28 offenders (48.3%). Of these, half (n = 14) were in a romantic relationship, and half (n = 14) were not. Four offenders

were identified as being married (6.9%), and two offenders were separated from their spouses

(3.4%).

Eleven offenders (19.0%) had dropped out of high school, and one offender had stopped attending school prior to high school (1.7%). Seven offenders (12.1%) had notable disciplinary infractions in their educational histories. At the time of their offenses, 17.2% (n = 10) were legally employed; 13.8% (n = 8) were inconsistently employed; 15.5% (n = 9) were unemployed; and 8.6% (n = 5) were surviving only on illegal sources of income (e.g., sex work, check fraud, fencing stolen property). Three offenders (45.2%) were high school students. The employment status of the remaining 39.7% (n = 23) is unknown. All offenders with legal employment were employed as manual laborers or other blue-collar workers.

Five offenders demonstrated clinically significant paranoid symptoms prior to the commission of their offenses (8.6%). Four offenders had a history of emotional dysregulation characterized by unstable mood and behavior (6.9%). Three demonstrated clinically significant symptoms of depression (5.2%). Twenty-three offenders (39.7%) were known to have a substance abuse problem, with 24.1% (n = 14) abusing alcohol, 12.1% (n = 7) abusing marijuana; 6.9% (n = 4) abusing crack or cocaine; and 1.7% abusing methamphetamines (n = 1).

For 60.3% of the sample (n = 35), no substance abuse history was available.

Twenty-six offenders had committed prior violent offenses (44.8%), while thirteen offenders (22.4%) had no violent priors. Three offenders (5.2%) had a history of committing sexual offenses. Twenty-one offenders (36.2%) had a history of property offenses. Eleven offenders (19.0%) had a history of drug-related offenses. Four offenders (6.9%) were known to have been involved in bias-motivated offenses in the past, although none had been formally charged with a hate crime. Two offenders (3.4%) were known to have warrants out for their

arrest at the time they committed their homicide offenses. Eleven offenders (19.0%) had criminal backgrounds that meet Hare’s (1991) criteria for “criminal versatility” (i.e., six or more classes of offenses).

Many cases included evidence that the offender’s biases were made known to others prior to the commission of the homicide offense. Twenty-one offenders (36.2%) had demonstrated racial or ethnic biases; ten offenders (17.2%) had demonstrated anti-gay or anti-transgender biases. In 12 cases (20.7%), witnesses or law enforcement officials reported that the offender had been known to use racial or ethnic slurs or had used them in referring to the victim; in 10 cases (17.2%), witnesses reported that the offender had been known to use anti-gay or anti- transgender slurs or had used them in referring to the victim. Two offenders (3.4%) had openly expressed both racial and anti-LGBT animus. Four (6.8%) offenders were in possession of racist hate literature or paraphernalia. Three offenders (5.2%) had tattoos indicating their affiliation with a White Supremacist group, and two offenders (3.4%) had made statements prior to their offenses indicating that they intended to earn such a tattoo through their actions.

Offense characteristics. In 48.3% (n = 28) of cases sampled, the victim was targeted, in whole or in part, due to the offender’s perception of their race or ethnicity. In 51.7% (n = 30) of cases sampled, the victim was targeted, in whole or in part, due to the offender’s perception of their sexual orientation or gender identity.

In 27.6% (n = 16) of cases, a prior relationship between the victim and offender was documented. In 58.6% of cases (n = 34), the victim and offender were reported to have no relationship prior to the offense. In 13.8% of cases sampled (n = 8), the relationship between victim and offender was unknown or not reported.

In 41.4% of cases (n = 24), it was alleged that the victim played a role in inciting their demise. In nine cases (15.5%), the offender alleged that the victim made an unwelcome sexual advance prior to the homicide offense. In six cases (10.3%), the offender or witnesses reported that the victim had made disparaging racial remarks to the offender prior to the homicide offense.

In nine cases (15.5%), the homicide offense was preceded by some other argument or acute conflict. An ongoing conflict (e.g., long-standing grudge) preceded three homicide offenses

(5.2%). In two cases (3.4%), the offender became aware of the victim’s transgender identity immediately prior to the homicide offense. In two cases (3.4%), the offender intended to only rob the victim but then wound up killing them. Eight victims (13.8%) were intentionally misled or lured into a trap by the offender(s). Two victims (3.4%) were killed during the course of an attempted robbery. In twelve cases (20.7%), available evidence indicates the offender committed a blitz attack on an unsuspecting victim. In 19 cases (32.8%), there was no information available regarding the circumstances preceding the homicide.

Offenses took place in a variety of locations, including the victim’s residence (n = 18;

24.1%); a road or street (n = 18; 31.0%); another public outdoor space (n = 8; 13.8%); a secluded location, such as a wooded area (n = 9; 15.5%); a motel room (n = 2; 3.4%); the offender’s workplace (n = 3; 5.2%); and a vehicle (n = 2; 3.4%). In two cases (3.4%), the location of the offense was not reported.

Causes of death include: gunshot wound (n = 23; 39.7%); blunt force trauma (n = 15;

25.9%); stabbing (n = 15; 25.9%); strangulation (n = 2; 3.4%); vehicular death (n = 2; 3.4%); and smoke inhalation caused by arson (n = 1; 1.7%). Multiple forms of violence were used in 13 offenses (22.4%). The primary weapons (i.e., those used to inflict the most serious injury to the victim) include: firearms (n = 23; 39.7%); knives (n = 15; 25.9%); blunt instruments (n = 7;

12.0%); hands (n = 14; 24.1%); motor vehicles (n = 3; 5.2%;); and fires (n = 2; 3.4%). A weapon found at the crime scene was used in 31.0% of cases (n = 18). Facial trauma was observed in 50.0% (n = 29) of cases sampled, as indicated by victim photos and/or Medical

Examiner reports. Overkill, defined as the use of violence beyond what is required to complete the murder, was reported or observed in 17.2% (n = 10) of cases. In 24 cases (41.4%), there were multiple wounds to a single area (e.g., six stab wounds to the chest). Six victims (10.3%) were found with their genitals exposed. One offender (1.7%) described his offense as sexually gratifying during police interviews.

Over half of the offenses sampled were characterized by one or more features associated with expressive violence (n = 33; 56.9%). The mean number of expressive features per offense was 2.26 (SD = 1.94). Over half of the offenses sampled were characterized by one or more features associated with instrumental violence (n = 34; 58.6%). The mean number of instrumental features per offense was 0.65 (SD = 0.58).

In many cases, there was evidence that the offender was under the influence of a substance or multiple substances at the time of the offense. In 18 cases (31.0%), the offender had consumed excessive alcohol prior to the offense. In two cases (3.4%), the offender had smoked marijuana and consumed alcohol prior to the offense. In one case (1.7%), the offender had smoked marijuana only. In one case (1.7%), the offender had used cocaine prior to the offense.

Only 29.3% (n = 17) of cases presented with clear evidence of pre-offense planning (e.g., offender’s statements indicated planning, offense shows forethought in location and method, witnesses or codefendants report knowledge of a plan). Post-offense behavior varied widely.

Staging, defined as the rearrangement of a crime scene in an attempt to direct law enforcement

suspicion away from the offender (e.g., using arson to cover a murder) was reported or observed in three cases (5.2%). Five offenders (8.6%) attempted to dispose of the victim’s body by transporting it to a second location, and one offender (1.7%) dismembered the body prior to disposal. Evidence of bias-motivated vandalism was present at two crime scenes (3.4%), both of which were motivated by anti-LGBT bias and contained homophobic slurs. Fourteen offenders

(24.1%) stole property or money from their victims before leaving the crime scene. Three offenders (5.2%) remained at the scene of the crime and were apprehended by law enforcement at the scene. Three offenders (5.2%) committed suicide at the scene of the crime prior to being apprehended by law enforcement; two offenders (3.4%) died of self-inflicted gunshot wounds, and one offender (1.7%) died of blunt force trauma after jumping from a window.

A full confession of criminal responsibility was produced by the primary offender in at least 22.4% (n = 13) of cases. Ten offenders (17.2%) persisted in denying responsibility for their offenses. Two offenders (3.4%) admitted responsibility for the victim’s death but claimed to have acted out of self-defense; these two offenders made claims of a “homosexual panic” defense, in which the offender claims his violence is justified due to an unwanted sexual advance by the victim. Only three offenders (5.2%) made explicit statements to law enforcement indicating that their offenses were bias-motivated and unprovoked.

Judicial outcomes were available in 22 cases (37.9%). Fifteen offenders (25.9%) were convicted of murder in the first degree or capital murder. Four offenders (6.9%) were convicted of murder in the second degree. Three offenders were convicted of manslaughter (5.2%).

Sentencing determinations were available in 32.8% of cases (n = 19). Seven offenders (12.1%) were sentenced to life in prison. Three offenders (5.2%) were sentenced to death. One offender

(1.7%) received a prison sentence of over 40 years; six offenders (10.3%) received a prison

sentence of 20 to 40 years; one offender (1.7%) received a sentence of 10 to 20 years. One juvenile offender (1.7%) was sentenced to rehabilitation through the juvenile justice system; two juvenile offenders (3.4%) were tried and sentenced as adults.

Victim characteristics. A total of 64 homicide victims comprise the victim sample.

While some offenses included multiple victims, only those murdered were included in the sample; surviving victims were excluded, as many survived with minor injuries, and the offenders’ intent could not be presumed from the available data. Victims ranged in age from 15 to 74, with a mean age of 33.3 years (SD = 12.87). Just over half (n = 34; 53.1%) of victims were identified as White/Caucasian; 26.6% (n = 17) of victims were identified as Black/African-

American; 4.1%% (n = 9) were identified as Hispanic/Latino; and 6.3% (n = 4) were identified as Asian. One victim (n = 1.7%) was identified as Jewish.

Almost all the victims in the sample (n = 59; 92.2%) were identified as cisgender males.

Three victims (4.7%) were identified as cisgender females; one of these victims (1.6%) had a gender nonconforming physical presentation but identified as female. Two victims (3.1%) were identified as transwomen (assigned male at birth). Cisgender female victims were most often part of a multiple-victim offense (n = 2; 66.6%). Transgender females (n = 2; 100%) and cisgender male victims (n = 54; 91.5%) were most often alone with the offender at the time of their death.

Information on sexual orientation was available for 41 victims. Of these, 41.5% (n = 17) were identified as heterosexual or straight; 58.5% (n = 24) were identified as homosexual, gay, lesbian, or bisexual. Ten victims (17.2%) were identified from the available data members of more than one marginalized identity group (e.g., gay and Latino).

Some victims in the sample exhibited vulnerabilities known to be associated with victim risk. One victim (1.7%) was identified as deaf, and one victim (1.7%) had a physical disability.

One victim was identified as undomiciled (1.7%), and two victims (3.4%) were known to engage in sex work as their primary source of income.

Typology data. Utilizing the Levin, McDevitt, and Bennett (2002) typology (Table 4), one coder found that 6 cases (10.3%) would be classified as thrill offenses; 17 cases (29.3%) would be classified as reactive/defensive offenses; 23 cases (39.7%) would be classified as mission offenses; and 7 cases (12.1%) would be classified as retaliatory offenses. In 5 cases

(8.6%), there was no clear classification. This coder rated the goodness-of-fit as high in 21 cases

(36.2%); moderate in 17 cases (29.3%); and low in 15 cases (25.9%). The other coder (PI) found that 19 cases (32.8%) would be classified as thrill offenses; 24 cases (41.4%) would be classified as reactive/defensive offenses; 10 cases (17.2%) would be classified as mission offenses; and 2 cases (3.4%) would be classified as retaliatory offenses. This coder rated the goodness-of-fit as high in 12 cases (20.7%); moderate in 36 cases (62.1%); and low in 8 cases (14.3%).

Interrater reliability was evaluated using Cohen’s Kappa. The interrater reliability for the two raters was found to be ĸ = 0.28 (95% CI, 0.131, 0.437), p < .001. This result is considered a

“fair” level of agreement, per Landis and Kock (1997).

Under the proposed typology (Table 5), 13 cases (22.4%) would be classified as Anti-

LGBT without Provocation; 15 cases (25.9%) would be classified as Anti-LGBT with

Provocation; 10 cases (17.2%) would be classified as Racial/Ethnic without Provocation; and 18 cases (31.0%) would be classified as Racial/Ethnic with Provocation. The remaining case

(1.7%) could not be categorized because there was insufficient data regarding the circumstances preceding the offense to make a determination regarding provocation.

Comparing Anti-LGBT and Racially/Ethnically Motivated Offenses

For all dichotomous variables, contingency tables were created using SPSS. Due to the small sample size, cell sizes were frequently smaller than five cases; therefore, Fisher’s exact test

(two-tailed) was used to determine significance levels, and all statistics were evaluated at an alpha level of .05. Further, all percentages noted herein reflect the number of valid cases per variable, in order to avoid underestimating prevalence on the basis of insufficient information within the case files.

Offender characteristics. Anti-LGBT offenders were statistically significantly less likely than racial/ethnic offenders to have multiple offenders present at the scene (17.2% vs.

55.2%, p = .006, Fisher’s exact test). A paired-samples t-test was conducted to compare the mean age of offenders involved in anti-LGBT versus racial/ethnic offenses. There was not a statistically significant difference between the mean age of anti-LGBT offenders (M = 25.50; SD

= 7.61) versus the mean age of racial/ethnic offenders (M = 26.30; SD = 10.40); t(53) = .325, p

= .111. Furthermore, when offenders were stratified by age group, anti-LGBT offenses were no more likely to be committed by juveniles than were racial/ethnic offenses (7.4% vs. 11.1%, p =

1.000, Fisher’s exact test).

Anti-LGBT offenders were not statistically less likely than racial/ethnic offenders to be identified as White/Caucasian (p = .599, Fisher’s exact test). Anti-LGBT offenders were identified as White in 51.7% of cases, Black in 31.0% of cases, and Hispanic in 17.2% of cases.

Racial/ethnic offenders were identified as White in 42.9% of cases, Black in 28.6% of cases,

Hispanic in 21.4% of cases, and Asian in 3.6% of cases.

Anti-LGBT offenders were no more likely than racial/ethnic offenders to be cisgender males (100% vs. 96.4%, p = .483, Fisher’s exact test). Anti-LGBT offenders were no less likely

than racial/ethnic offenders to be gay or lesbian (100% vs. 95.7%, p = 1.000, Fisher’s exact test).

Three of the anti-LGBT offenders were identified as Christian, while one of the racial/ethnic offenders was identified as Christian. Statistical comparison was not possible, as these were the only religious identifications reported in the sample.

Anti-LGBT offenders were no more likely than racial/ethnic offenders to be experiencing homelessness at the time of their offenses (55.6% vs. 37.5%, p = .637, Fisher’s exact test). Anti-

LGBT offenders were not statistically less likely than racial/ethnic offenders to be members of gangs or White Supremacist groups (16.7% vs. 28.6%, p = .352, Fisher’s exact test). Anti-

LGBT offenders were no more likely than racial/ethnic offenders to be in a romantic relationship at the time of their offenses (35.7% vs. 64.3%, p = .257, Fisher’s exact test).

Anti-LGBT offenders were statistically significantly less likely to have a steady, legal source of employment as compared to racial/ethnic offenders (10.0% vs. 53.3%, p = .008,

Fisher’s exact test). Anti-LGBT offenders were not statistically significantly more likely than racial/ethnic offenders to be criminally versatile prior to their homicide offense (34.6% vs.

15.0%, p = .183, Fisher’s exact test). Anti-LGBT offenders were not more likely than racial/ethnic offenders to have a prior violent criminal history (58.3% vs. 80.0%, p = .295,

Fisher’s exact test). Anti-LGBT offenders were not more likely than racial/ethnic offenders to have a prior sexual criminal history (9.1% vs. 7.1%, p = 1.000, Fisher’s exact test). Anti-LGBT offenders were not more likely than racial/ethnic offenders to have a prior history of bias- motivated crime, although the difference in frequency may suggest a trend towards racial/ethnic offenders having more priors (4.2% vs. 21.4%, p = .132, Fisher’s exact test). Anti-LGBT offenders were not more likely than racial/ethnic offenders to have a prior history of drug-related offenses (63.6% vs. 36.4%, p = 1.000, Fisher’s exact test). Anti-LGBT offenders were not more

likely than racial/ethnic offenders to have a prior history of property offenses (62.5% vs. 42.9%, p = .318, Fisher’s exact test).

Offense characteristics. In anti-LGBT offenses, the victims’ bodies were statistically significantly less likely to be found outdoors than they were in racial/ethnic offenses (56.0% vs.

87.5%, p = .025, Fisher’s exact test). Anti-LGBT offenders were no more likely than racial/ethnic offenders to target an individual who was already known to them prior to the offense (66.7% vs. 69.6%, p = 1.000, Fisher’s exact test). Anti-LGBT offenders were not statistically more likely than racial/ethnic offenders to lure or mislead their victims (23.1% vs.

8.0%, p = .248, Fisher’s exact test). Anti-LGBT offenses were statistically significantly more likely than racial/ethnic offenses to be preceded by a sexual proposition or advance by either the victim or the offender as compared to racial/ethnic offenses (53.8% vs. 0.0%, p < .001, Fisher’s exact test), but they were not statistically more likely than racial/ethnic offenses to show significant evidence of planning (27.6% vs. 33.3%, p = .773, Fisher’s exact test). Meanwhile, anti-LGBT offenses were nearly statistically significantly less likely to involve a blitz-style attack as compared to racial/ethnic offenses (11.5% vs. 36.0%, p = .052, Fisher’s exact test).

The crime scenes of anti-LGBT offenses were not statistically more likely than the crime scenes of racial/ethnic offenses to show signs of staging (10.3% vs. 0.0%, p = .237, Fisher’s exact test).

Anti-LGBT offenders were not statistically more likely than racial/ethnic offenders to dispose of their weapon after committing the offense (36.4% vs. 10.5%, p = .075, Fisher’s exact test). Anti-

LGBT offenders were not statistically more likely than racial/ethnic offenders to brag about their offenses to others after committing their crimes (16.7% vs. 38.9%, p = .159, Fisher’s exact test).

Anti-LGBT offenses were statistically significantly less likely than racial/ethnic offenses to involve wounding by gunshot (13.3% vs. 67.9%, p <.001, Fisher’s exact test). The cause of

death was statistically significantly more likely to be blunt force trauma in anti-LGBT offenses as opposed to racial/ethnic offenses (40.0% vs. 10.7%, p = .016, Fisher’s exact test). Anti-LGBT offenses were not statistically significantly more likely than racial/ethnic offenses to involve stab wounds, although the difference in frequency and the statistically significant difference may suggest a trend such that stab wounds are more common in anti-LGBT offenses than racial/ethnic offenses (36.7% vs. 14.3%, p = .073, Fisher’s exact test).

There was not a statistically significant difference between anti-LGBT offenses and racial/ethnic offenses in terms of frequency of injuries to the head (23.3% vs. 29.6%, p = .764,

Fisher’s exact test). There was not a statistically significant difference between anti-LGBT offenses and racial/ethnic offenses in terms of frequency of injuries to the chest (44.4% vs. 56.7, p = .431, Fisher’s exact test). There was not a statistically significant difference in the frequency of wounding to a variety of body parts in anti-LGBT offenses as compared to racial/ethnic offenses (20.0% vs. 25.9%, p = .754, Fisher’s exact test).

Anti-LGBT offenders were statistically significantly more likely to use a weapon from the crime scene than were racial/ethnic offenders (50.0% vs. 17.2%, p = .020, Fisher’s exact test). Anti-LGBT offenses were not statistically more likely than racial/ethnic offenses to demonstrate excessive wounding (41.1% vs. 23.1%, p = .116, Fisher’s exact test). Anti-LGBT victims were not statistically more likely than racial/ethnic victims to display facial wounding

(55.2% vs. 48.1%, p = .789, Fisher’s exact test). Anti-LGBT offenses were not statistically more likely than racial/ethnic offenses to include multiple wounds to the same area of the body (60.0% vs. 36.0%, p = .156, Fisher’s exact test). Racial/ethnic offenses were statistically significantly more likely to be enacted by pairs or groups of offenders than were anti-LGBT offenses (57.1% vs. 16.7%, p = .002, Fisher’s exact test). Racial/ethnic offenses were also statistically

significantly more likely to involve the deaths of multiple victims (32.1%) as compared to anti-

LGBT offenses (0.0% [p = .001, Fisher’s exact test]).

Anti-LGBT offenses were statistically significantly more likely than racial/ethnic offenses to involve a theft of the victim’s belongings, regardless of whether this was the original intent of the offense (44.8% vs. 3.6%, p <.001, Fisher’s exact test). The victims in anti-LGBT offenses were statistically significantly more likely than the victims in racial/ethnic offenses to be left naked or partially exposed at the crime scene (20.7% vs. 0.0%, p = .024, Fisher’s exact test).

Anti-LGBT offenses (M = 3.13; SD = 1.77) featured significantly more expressive behaviors than racial/ethnic offenses (M = 1.39; SD = 1.75), t(44) = -3.35, p = .002. There was no significant difference between the two groups in terms of number of instrumental behaviors (p

= .327). Anti-LGBT offenses featured a mean of 0.57 instrumental behaviors per offense (SD =

0.69); racial/ethnic offenses featured a mean of 0.72 instrumental behaviors per offense (SD =

0.45). Additional comparisons appear in Table 8.

Victim characteristics. A paired-samples t-test was conducted to compare the mean victim age for anti-LGBT versus racial/ethnic offenses. There was not a statistically significant difference between the mean age of victims of anti-LGBT offenses (M = 36.83; SD = 14.62) and the victims of racial/ethnic offenses (M = 30.29; SD = 11.06); t(56) = -1.91, p = .211. Anti-

LGBT offenses were significantly more likely than racial/ethnic offenses to target a victim with intersecting marginalized identities (30.0% vs. 3.6%, p = .012, Fisher’s exact test). Anti-LGBT offenses were not statistically more likely to target sex workers than were racial/ethnic offenses

(6.7% vs. 0.0%, p = .494, Fisher’s exact test). White/Caucasian victims constituted a statistically

significantly larger portion of the victims in anti-LGBT offenses than in racial/ethnic offenses

(76.7% vs. 28.6%, p = <.001, Fisher’s exact test).

Intersectionality & Expressed Emotion

Few variables were found to be associated with offenses targeting intersectional identities. The majority of victims with intersectional marginalized identities were attacked due to anti-LGBT bias, rather than racial or ethnic bias (90.0% vs. 43.8%, p = .008; Fisher’s exact test). In murders of victims with intersectional marginalized identities, the attack was statistically significantly more likely to have been preceded by a sexual advance by the victim than in non-intersectional offenses (62.5% vs. 20.9%, p = .028, Fisher’s exact test).

There was no significant difference between the two groups in terms of number of expressive behaviors (p = .146). Intersectional offenses featured a mean of 3.11 expressive behaviors per offense (SD = 1.96); non-intersectional offenses featured a mean of 2.05 expressive behaviors per offense (SD = 0.45). There was no significant difference between the two groups in terms of number of instrumental behaviors (p = .327). Intersectional offenses featured a mean of 0.33 instrumental behaviors per offense (SD = 0.71); non-intersectional offenses featured a mean of 0.71 instrumental behaviors per offense (SD = 0.54). Additional comparisons that did not produce statistically significant results can be found in Table 6.

Victim-Offender Relationship & Expressed Emotion

Few variables were found to be associated with a prior relationship between the victim and offender. In stranger offenses, the victim’s body was typically found outdoors (86.7%); whereas, in offenses in which the victim and offender were previously known to one another, the victim’s body was only found outdoors less than half of the time (41.7%), p = .006, Fisher’s

exact test. Stranger offenses were also significantly more likely to be blitz attacks than were non-stranger offenses (34.5 vs. 6.3%; p = .035, Fisher’s exact test).

There was no significant difference between the two groups in terms of number of expressive behaviors (p = .266). Stranger offenses featured a mean of 2.11 expressive behaviors per offense (SD = 1.85); non-stranger offenses featured a mean of 2.85 expressive behaviors per offense (SD = 2.15). There was no significant difference between the two groups in terms of number of instrumental behaviors (p = .937). Stranger offenses featured a mean of 0.58 instrumental behaviors per offense (SD = 0.56); non-stranger offenses featured a mean of 0.56 instrumental behaviors per offense (SD = 0.51). Additional comparisons that did not produce statistically significant results can be found in Table 7.

Provocation & Expressed Emotion

Few variables were found to be associated with provocation by the victim. Offenders who felt provoked by their victims or acted in response to a threat or insult by the victim were statistically significantly more likely to use a weapon from the scene than were offenders who did not claim provocation (50.0% vs. 21.1%; p = .038, Fisher’s exact test). Offenders who felt provoked by their victims were statistically significantly less likely to brag about their offenses than were offenders who did not claim provocation (10.5% vs. 38.1%; p = .048, Fisher’s exact test).

instrumental behaviors per offense (SD = 0.56); non-stranger offenses featured a mean of 0.56 instrumental behaviors per offense (SD = 0.51). Additional comparisons that did not produce statistically significant results can be found in Table 8.

Intergroup Differences in the Proposed Typology

Given the many statistically significant differences between the anti-LGBT and racial/ethnic offenses, a typology was proposed that differentiates cases by the type of bias motivating the crime and the situational precursors to the crime. The four resulting types are hereafter referred to as Type 1 (Anti-LGBT Homicides with Provocation: n =15; 25.9%); Type 2

(Anti-LGBT Homicides without Provocation: n = 13; 22.4%); Type 3 (Racial/Ethnic Homicides with Provocation: n = 18; 31.0%); and Type 4 (Racial/Ethnic Homicides with Provocation: n =

10; 17.2%). Additional description of these categories can be found in Table 5. These four types were then compared to one another; only statistically significant differences at the p < .05 level are reported below. Additional comparisons that did not yield statistically significant differences can be found in Table 9.

Offender characteristics. There was a statistically significant difference among the groups in the presence of multiple offenders at the crime scene (p < .05), such that Type 1 (n =

11; 84.6%) and Type 2 (n = 12; 80.0%) offenses rarely involved multiple offenders, whereas roughly half of Type 3 (n = 5; 50.0%) and Type 4 (n = 10; 55.6%) offenses involved multiple offenders. There was a statistically significant difference among the groups in the involvement of multiple homicides (p < .05). Type 1 and Type 2 crimes never involved multiple homicides, whereas 30% (n = 3) of Type 3 and 27.8% (n = 5) of Type 4 crimes involved the death of multiple victims.

Most Type 3 offenders were non-White (n = 9; 90%), while the other groups were about half White and half non-White. The victims of Type 4 offenses were almost all non-White (n =

16; 88.9%), whereas most Type 1 (n = 11; 84.6%) and Type 2 (n = 11; 73.3%) victims were

White. Type 3 victims were White in 60% of cases (n = 6).

There was a statistically significant difference between Type 1 offenses and other offenses in terms of the percentage of cases in which the victim’s body was found outdoors (p

< .05). All of the Type 3 offenders left their victim’s body outdoors. This was also the trend for

Type 2 (n = 8; 66.7%) and Type 4 (n = 13; 81.3%) offenses. On the other hand, Type 1 offenders left their victim’s body indoors more often than not (n = 6; 54.5%).

There was a statistically significant effect such that a blitz attack is used more commonly in Type 4 offenses (p < .01). There was a statistically significant difference among groups in their likelihood of involving a gunshot wound to the victim (p < .01). Most Type 1 (n = 12;

92.3%) and Type 2 (n = 13; 86.7%) victims did not die from a gunshot wound. Most Type 3 (n

= 7; 70%) and Type 4 (n = 12; 66.7%) victims died by gunshot wound. There was also a statistically significant difference in the prevalence of use of a weapon from the crime scene (p

= .028). In Type 1 crimes, a weapon from the crime scene was used more often than not (n = 8;

66.7%). In Type 2, Type 3, and Type 4 crimes, it was less common for the offender to use a weapon from the scene.

Victim characteristics. Type 4 cases were statistically significantly more likely than

Type 1, 2, and 3 cases to have a Black victim (p < .01). More than half (n = 11; 61.1%) of Type

4 cases were Black, while White victims were the most common in Type 1 (n = 11; 84.6%);

Type 2 (n = 11; 73.3%); and Type 3 (n = 6; 60.0%).

Offense characteristics. Type 1 offenders were statistically significantly more likely to use a weapon from the crime scene (n = 9; 75.0%) than were any other type of offender (p < .05).

Type 3 (n = 7; 70.7%) and Type 4 (n = 14; 77.8%) offenders typically brought weapons with them to the scene. Type 2 offenders used a weapon from the scene in almost half of cases (n = 6;

42.9%).

There was a statistically significant difference among the four types in terms of the total number of expressive features per offense, F(3, 41) = 3.380; p = .027. Type 1 offenses exhibited an average of 3.20 expressive features per offense (SD = 2.04). Type 2 offenses exhibited an average of 3.08 expressive features per offense (SD = 1.61). Type 3 offenses exhibited an average of 1.29 expressive features per offense (SD = 1.60). Type 4 offenses exhibited an average of 1.47 expressive features per offense (SD = 1.92). There was no statistically significant difference among the four types in terms of the total number of instrumental features per offense (p = .852). Type 1 offenses exhibited an average of 0.54 instrumental features per offense (SD = 0.66). Type 2 offenses exhibited an average of 0.64 instrumental features per offense (SD = 0.74). Type 3 offenses exhibited an average of 0.70 instrumental features per offense (SD = 0.48). Type 4 offenses exhibited an average of 0.72 instrumental features per offense (SD = 0.46).

100

Chapter 6

Discussion

Bias-Motivated Homicides

Though few samples have focused specifically on bias-motivated homicide offenses in the past, the present study reinforces many of the ideas presented in previous studies of bias- motivated crimes.

Offenders. In many ways, this sample replicates Hamm’s (1993) discussion of young

American Skinheads in showing that offenders are often working-class individuals who have or are heading toward blue-collar employment, have exposure to White-Power-related media, believe in the morality of vengeance, have exposure and access to weapons, bond with others with similar backgrounds and ideas, become disinhibited under the influence of substances

(particularly beer), and engage in terroristic violence.

Fewer than half of the offenders sampled had a record of violent priors, but over one- third of offenders had committed property offenses. This, coupled with the high rate of post- homicide theft and unemployment, suggests that many of these offenses are motivated, at least in part, by the potential for financial gain. Particularly among those offenses targeting gay men, it occurred to most offenders to rob the victim either prior to or after the commission of the offense. This warrants further investigation, as the appearance of a financial motive can overshadow the bias-related aspects of an offense when assessing a crime scene.

Three offenders (4.8%) were known to have been involved in bias-motivated offenses in the past, although none had been formally charged with a hate crime. This number is likely an underestimate, as hate crime laws have evolved over time to include classes that were not included at the time these offenses were charged (e.g., LGBT). Interestingly, two offenders had

101

histories of involvement in racialized violence that did not result in arrest: one law enforcement officer who had several brutality complaints filed against him by people of color and one soldier who had previously incited racial violence on his military base. Their homicidal offenses may be seen as escalations of their prejudice-driven aggression. Given the inculcation of violence in these professions, military and law enforcement officials might consider monitoring these incidents and individuals more closely.

Offenders’ psychological processes. Many researchers (e.g., Byers et al., 1999; Levin &

McDevitt, 1993; Sun, 2006; Sykes & Matza, 1957) have attempted to explain the neutralization techniques that offenders use to rationalize their criminal behavior and their victim selection in hate crime. For example, Byers et al. (1999) reported that many of the Pennsylvania youth who offended against the local Amish endorsed negative stereotypes about the Amish, suggested that their victims deserved the punishment they had been dealt, denied their victims’ human-ness, or described their behavior as acts of in-group loyalty rather than out-group hatred.

Many offenders in the current sample made remarks indicative of such processes. In one case, the offender left the phrase “AIDS SPREADER” scrawled on the wall of the victim’s apartment, suggesting the offender’s endorsement of the negative perception of gay men as sexually promiscuous and responsible for perpetuating the spread of HIV and AIDS. Another offender, who murdered a gay man with whom he had been casually drinking and playing pool, stated, “We don’t have to worry about that f—t anymore,” as if to position himself as a hero and suggest that the victim had posed some threat that justified the use of violence to subdue him.

Several offenders admitted to planning the murder a Black person for the purpose of gaining a spiderweb tattoo, a symbol associated with hate group membership, thus minimizing the victim to an inhuman target in a game – a means of solidifying their own in-group membership.

102

Additionally, although many offenders alleged that their victim’s behavior somehow justified the homicidal violence committed against them, more than half of the offenders sampled had openly exhibited racial, ethnic, homophobic, or transphobic biases prior to the commission of their offenses, suggesting the victims’ behavior was not the sole source of the offenders’ violence.

It has also been proposed that isolation, depression, and shame can lead individuals to commit hate offenses in an attempt to restore their sense of power and self-efficacy in an otherwise unremarkable life (Anderson et al., 2002; Gadd & Dixon, 2009; Ray et al., 1994).

Appropriately, offenders in this sample tended to have unstable or unhappy childhoods, had minimal academic success, or had exhibited acting out behaviors in school. While there was limited mental health information available about most of the offenders in this sample, symptoms of paranoia and depression were common, as were substance abuse problems. Taken together, this paints a picture of the bias-motivated homicide offender as a repeat “loser in life,” someone who believes himself to be a victim of unfair circumstances, who uses substances and violence to mask and assuage his shame.

Hate groups. Hate groups or gangs organized around racial or ethnic identity may play a key role in the escalation of hate violence to the extreme of homicide. Prior research on hate crime (e.g., Dunbar et al., 2005; Perry, 2009b) has indicated that a very small portion (16% and

5%, respectively) of hate crime offenders are associated with hate groups; however, in the current sample, roughly one quarter of homicide offenders were associated with a hate group or racial/ethnic gang. Given the social psychology research on the influence of groups on decision- making processes, it seems that involvement in a hate group may, in part, encourage hate violence to escalate to homicide.

103

Specifically, the term groupthink refers to “the mode of thinking that persons engage in when concurrence-seeking becomes so dominant in a cohesive ingroup that it tends to override realistic appraisal of alternative courses of action” (Janis, 1971, p. 84). Based on case studies,

Janis (1972) identified four antecedents common among group decision-making debacles. The first, cohesion, is a somewhat vague term that refers to the degree of closeness of group members and the desire to maintain harmony among members of the decision-making body. The second, insulation, refers to the group being shielded from the opinions of outsiders. Insulation may also entail isolation, which may have physical and psychological distancing components. The third, lack of impartial leadership, refers to the involvement of leaders who have preconceptions or personal agendas that affect their leadership style in a way that may communicate to group members that new ideas are not welcome. The fourth, lack of methodical decision-making procedures, refers to the haphazard manner in which some groups reach conclusions, which may include disregarding or carelessly misinterpreting relevant data. These qualities commonly apply to hate groups and gangs (e.g., Chermak, Freilich, & Suttmoeller, 2013; Hamm, 1993;

Sanders, 1994/2017). Symptoms of groupthink include a sense of invulnerability of the group, rationalization of decisions, belief in the morality of the group, endorsement of stereotypes of outgroup members and leaders, and pressure to conform to group norms. The outcomes associated with groupthink are sometimes catastrophic; similarly, a number of victims in this sample were killed for no reason other than an offender’s desire to conform to violent in-group norms and punish out-group members at random.

Victims. This particular sample of victims was predominated by White, Black, and

Latina/o victims, with most of the White victims identifying either as gay or as vocal members of a White Supremacy organization. The prevalence of White victims in the sample may be

104

surprising to those who view hate crimes as crimes that are enacted only against marginalized groups; however, most hate crime legislation merely states that the offender’s act or victim selection is motivated in whole or in part by the victim’s identity – whether or not that identity is one that has historically been subject to persecution. While the gay victims sampled were overwhelmingly White, a sizable portion of the racially motivated offenses also targeted White victims. These were less likely to be predatory-type offenses and were more commonly reactive, in that a White individual may have exchanged bigoted words with a person of color and therefore become a target of violence.

It is worth noting that victims were deceased and unable to self-identify; therefore, these identity labels were supplied by the victims’ family and friends or inferred by law enforcement officials. The use of the term “transvestite” in police files was most likely erroneous, and it is likely that some transgender individuals were incorrectly labeled as “homosexual” due to a limited understanding of transgender identity as distinct from sexual orientation.

Offenses. Just over half of the homicides in this sample were committed by a single offender acting alone. This differs from reports of non-homicidal hate offenses (e.g., Craig,

2002) which have indicated lower rates of single-offender hate crimes and higher rates of multiple-offender hate crimes. One explanation may be the make-up of this particular sample, which featured a fairly high rate of anti-LGBT homicides preceded by an interpersonal provocation situation. These events, which comprised roughly one quarter of the sample, typically involved private interactions in which only the victim and the offender were present prior to and during the commission of the offense.

For the most part, the homicides in this sample occurred in locations that would not be considered particularly “high-risk” for other types of offenses. Nearly half of the offenses

105

occurred in a public, outdoor space, where others might have readily observed the altercation.

This is somewhat consistent with the idea of hate crime victims being “in the wrong place at the wrong time.” However, nearly one-quarter of the offenses took place in the victim’s home, and in most of these cases, the offender had been granted entry by the victim. Three racial/ethnic offenses took place in the victim’s workplace. Taken together, this suggests that bias-motivated homicides often occur in locations where the victim would otherwise feel safe. As a result, interventions aimed at avoiding “dangerous” areas might be of limited value for the prevention of such offenses and may place undue blame on the victim for putting themselves in harm’s way.

Furthermore, the concept of planning in bias-motivated homicide appears to be quite different than in many other offenses. In many of the homicides in the present sample, the offender(s) had a plan to offend but did not have a specific victim in mind. These offenders were prepared to find a victim to satisfy their goals. Many of these offenders were associated with hate groups, particularly White Supremacist groups (e.g., White Aryan Resistance). The other type of planning observed in this sample was of a short-term nature and followed provocation by the victim or individuals accompanying the victim. In several racially motivated homicides, the perpetrator was provoked by remarks or behaviors; went to acquire a weapon, vehicle, and/or back-up; and returned to the scene to avenge the previous remarks or offense. As a result, it is likely that different individuals viewing the same case might come to different conclusions about whether or not the offense was “planned.”

Types of Bias and Victim Identity

Despite previous research making preliminary claims indicating that anti-LGBT offenses and racial/ethnic offenses do not differ qualitatively (e.g., Fisher, 2007) or are not significant to offender typology (e.g., Levin & McDevitt, 1993; McDevitt, Levin, & Bennett, 2002), this study

106

provides some justification for the inclusion of victim identity or type of bias as an important factor in the presentation, and therefore the investigation, of bias-motivated homicides.

Significant differences between anti-LGBT and racial/ethnic offenses emerged in this sample.

For example, the number of offenders involved in the commission of the offense was significantly different between these two groups. While anti-LGBT homicides were typically committed in a one-on-one fashion, the presence of multiple offenders was more indicative of a racially or ethnically motivated offense. Previous research (Craig, 2002) has indicated that the presence of multiple offenders at a homicide scene is sometimes correlated with a higher number of victim injuries or a variety in the types of injuries sustained, as multiple offenders may be wielding multiple weapons. Other crime scene observations (e.g., boot prints of different sizes, cigarette butts of varying brands) may guide law enforcement toward the understanding that a homicide was committed by multiple offenders rather than just one; therefore, this knowledge may be helpful in determining the motive of a racial/ethnic homicide when coupled with other crime scene features. Especially in the murder of an LGBT person of color, the presence of multiple offenders might lead law enforcement to better understand if one aspect of the victim’s identity (i.e., race) was driving the offense, rather than another aspect (i.e., sexual orientation).

Nonetheless, it is clear that many of the gay male victims were murdered by parasitic offenders who first asked for something from their victim and then took more. Several offenders had been given temporary housing by their unsuspecting victims. Most of the gay male victims were not in committed romantic relationships at the time they were killed, and most would not have been permitted to marry a same-sex partner at the time, as the offenses in this sample all occurred prior to the legalization of same-sex marriage in Massachusetts in 2004. The gay victims were often characterized by friends and family as affable, yet lonely; some were reported

107

to have engaged in substance abuse and sexually risky behavior. Due to the fact that the victims’ voices were squelched by these homicides, it is impossible to know the intentions of the victim in providing housing; however, it is clear that in many cases, the victim’s inability to testify opened the door for the offender to make false or exaggerated claims regarding the victim’s pre- offense behavior.

The anti-LGBT homicides in this sample exhibited several distinguishing features that suggest a link with sexuality. First, anti-LGBT homicides were more likely than racial/ethnic homicides to be preceded by a sexual situation of some kind. Many offenders claimed that their acts of violence were provoked when their victim(s) made a romantic or sexual advance toward them. The offenders reported these advances as unwanted, although many of them had gone home alone with a man that they knew to be gay, which calls into question their intentions and sexual attitudes; their violence calls to mind the Freudian concept of reaction formation (Freud,

1917/1977). These offenders were less likely to have been brazenly public with their homophobia prior to their offense as compared to those who openly went out in search of gay victims to attack; two such offenders exhibited ambivalence about homosexuality prior to their offenses, with their words and actions in conflict with one another.

Significant differences between anti-LGBT and racial/ethnic homicides also emerged in the use of weapons and violence. Homicides motivated by racial or ethnic bias were most often caused by gunshot wound, whereas homicides motivated by anti-LGBT biases were more commonly cause by stabbing or blunt force trauma. Accordingly, anti-LGBT homicide offenders were more likely to use a weapon of convenience that was found at the scene; this is consistent with the use of knives and blunt objects, which can be typically found in any home.

Meanwhile, most racial/ethnic homicide offenders brought a weapon with them to the crime

108

scene, typically a firearm. The average number of expressive features at the crime scene differed significantly between the two groups, with anti-LGBT crime scenes showing more expressive indicators.

The role of intersectionality. Although previous research has suggested that individuals with intersectional marginalized identities are likely to experience more frequent, intense, and specific forms of discrimination (e.g., Nadal, Mazzula, et al., 2014) and that hate crimes against victims with multiple marginalized identities may be more severe or brutal in nature (Meyer,

2010), this sample demonstrated no significant differences between the nature of violence in intersectional and non-intersectional cases. The nearly significant difference for stabbing (p

= .069) suggests that intersectional victims may be more likely to be stabbed, but this may be an artifact of the significant difference reported above indicating the same behavior is more prevalent in anti-LGBT homicides overall, as opposed to racial or ethnic homicides.

Intersectional victims were more likely to have been involved in a sexual situation prior to their offense (namely a sexual or romantic advance or revelation of gender identity) than were non-intersectional victims. Nearly significant differences for victim nudity (p = .063) are reasonable given this observation. They were more likely to have been attacked due to homophobic or transphobic reasons than to have been attacked for racist or xenophobic reasons.

Given the very small number of intersectional victims, further investigation of this hypothesis using a larger sample is warranted. This hypothesis, in particular, suffers from the lack of statistical power afforded by the available sample.

The Role of Provocation

The nature of provocation in anti-LGBT offenses differed from the nature of provocation in racial/ethnic offenses. Many of the anti-LGBT offenses were prefaced with an unwanted

109

sexual advance from the offender. This is consistent with the higher frequency of the use of a weapon of convenience from the crime scene. Meanwhile, many of the racial/ethnic offenses were incited by an exchange of racist language in which one or both parties may have been complicit.

It is, of course, important to keep in mind that the homicidal nature of these offenses left the victims unable to give their own reports of the events preceding the offense. While it is likely that some offenders fabricated or embellished their victims’ role in provoking violence – especially in those cases in which the victim and offender were alone together without witnesses at the time of the offense – some between-group differences regarding provocation were revealed in this sample. This may suggest that these offender fabrications are rare, or at least too rare to significantly skew the group statistics; alternatively, if the majority of those claiming provocation are falsifying their reports, the type of offender who would do so might be systematically different from offenders who do not cite provocation as an excuse for their behavior.

Among the cases without provocation, many of the victims were lured by the offender under some false pretense. For example, in more than one anti-LGBT offense, the offender pretended to have a sexual or romantic interest in the victim in order to gain access to his home or lead him to a more secluded area where the offense could be completed without witnesses.

Similarly, several racial/ethnic offenses were preceded by the offender offering a ride to an unsuspecting victim. Conversely, the rate of blitz attack was higher in racial/ethnic offenses.

The Role Expressive and Instrumental Crime Scene Behaviors

This study serves to further unpack observations made by Fisher (2007) and others that bias-motivated homicides almost always include some expressive aspects and may or may not

110

include some instrumental aspects. In this sample, there was no conclusive evidence of any offender having sexual activity with the victim at the time of the offense, but there were many crimes in which the offender stole from the victim’s person or home prior to or after the homicide. While many of the offenses were planned around the premise of committing a robbery, others resulted in thefts that were not premeditated.

Even those offenders who were explicit about the instrumental, financial motivation for their crimes (e.g., “to roll” a member of the target group) often committed crimes with excessive levels of violence. For example, victims who were intentionally lured or misled by the offender

– thus demonstrating the offender’s predatory style – still demonstrated expressive crime scene features. In particular, homicides by offenders affiliated with White Supremacist groups were often characterized by excessive violence using multiple methods of violence, despite a lack of provocation or emotional connection with the individual victim. Hamm (1993) reported many similar cases committed by American Skinheads in the 1980s, such as stomping a victim to death or beating a victim with multiple blunt objects. The admixture of expressive and instrumental behaviors may be influential in the way these crimes are investigated and prosecuted, due to the prevailing understanding of expressive violence as indicative of a pre-existing interpersonal relationship between victim and offender. As a result, these crimes may be less likely to be prosecuted as hate offenses; however, this hypothesis is beyond the scope of the present study.

Utility of the McDevitt et al. (2002) Typology

The application McDevitt et al.’s (2002) hate crime typology to this sample of bias- motivated homicides was problematic. Overall, agreement between the two raters was poor.

There was a higher degree of inter-rater agreement in cases classified as Reactive/Defensive or

Mission, suggesting that these types may have the most consistently recognizable features. In

111

only one case did both coders agree that the offense was Thrill type, and in only one case did both coders agree that the offense was Retaliatory type. In more than 50% of cases, however, the two coders did not agree on which classification best fit the case. This typology has been frequently used in training for law enforcement officers (e.g., Phillips, 2009). Its validity is, therefore, of great importance. Its utility, however, is called into question by the very low Kappa statistic.

Furthermore, there were few significant between-group differences when looking at either rater’s application of the typology to the bias-motivated homicides in this sample. The four types only differed in the likelihood that the victim was lured (most common in mission and thrill offenses), the likelihood of blitz attack (more likely in mission and thrill), and likelihood that the offender used a weapon of convenience from the scene to commit the crime (more likely in reactive and retaliatory offenses). These same variables have already been linked to provocation (or lack of provocation), both in this sample and elsewhere in the literature (e.g.,

Fox & Allen, 2014); therefore, provocation alone may be driving this effect.

Additionally, law enforcement officials often must rely on the crime scene evidence and the victim’s identity and personal history and work backwards to find the offender. The

McDevitt et al. (2002) typology is based more on offender variables, meaning it can only be useful in narrowing down the list of probable offenders if the offender is among the more obvious suspects. This severely limits its utility, given the large portion of bias-motivated homicide offenders who had no prior relationship to their victims.

Proposed Typology

The proposed typology appears to hold some promise as a new instrument to guide criminal investigation. Significant between-group differences were found for a variety of

112

offense characteristics, including the location of the body, the use of a blitz-style attack, the circumstances preceding the offense, the use of a gun to inflict injury, the use of a weapon of convenience from the scene to inflict injury, the theft of the victim’s belongings, the presence of multiple offenders at the scene, the number of expressive behaviors evident at the crime scene, the number of victims murdered at the scene, and the race of the victim(s). Significant between- group differences were also found for a variety of offender characteristics, including education level, relationship status, gang or hate group involvement, and race of the offender. Combining this data to form an offender typology may allow law enforcement to more effectively connect their crime scene observations to probable offender characteristics to aid them in identifying the proper offender(s).

Type 1: Anti-LGBT with Provocation. Type 1 crime scenes were characterized by a high frequency of post-offense theft (46.2%). Most of these offenders (66.7%) used a weapon from the scene, and many (46.7%) inflicted blunt force trauma. Gunshot wounds were rare

(7.7%). Most Type 1 offenses were committed by a single offender acting alone (84.6%).

Most Type 1 offenders had dropped out of school before completing high school

(83.3%). These offenders were rarely in romantic relationship at the time of their offenses

(22.2%). Most of these offenders (83.3%) had presented signs of homophobic attitudes prior to the commission of their offenses. These offenders were also most likely to confess to their offenses, although they did so less than half of the time (45.5%). Most of these offenders

(61.5%) were over 25 years old, and very few had a steady form of legal employment (14.3%).

Most of these offenders were apprehended within one month of their offense (87.5%), but very few were apprehended within 24 hours of their offense (12.5%), as many fled the area immediately following the offense.

113

Type 2: Anti-LGBT without Provocation. Type 2 crime scenes were characterized by a relatively high frequency of post-offense theft (50.0%). Gunshot wounds were rarely present in Type 2 cases (13.3%). Most Type 2 offenses were committed by a single offender acting alone (80.0%).

Most Type 2 offenders had dropped out before completing high school (80.0%). Most were in romantic relationships at the time they committed the offense (75%). Most of these offenders (83.3%) had presented signs of homophobic attitudes prior to the commission of their offenses. They commonly had prior histories of violent offenses (80.0%), but none of these offenders had prior bias-motivated offenses on record. These offenders were quite unlikely to confess to their offenses; only 13.3% confessed in full, and 6.7% admitted responsibility but claimed self-defense. Most were 25 years old or younger (61.5%), and very few had a steady form of legal employment (8.3%). These offenders went longer without being apprehended by law enforcement as compared to the other groups; 42.9% were not apprehended within one month of the offense, and none were apprehended within 24 hours of the offense.

Type 3: Racial/Ethnic with Provocation. Type 3 crime scenes were characterized by the absence of post-offense theft (0.0%). All Type 3 offenses occurred outdoors, and all Type 3 offenders left the victim’s body outdoors (100.0%). These offenses were more likely to involve multiple victims (30.0%) than Type 1 and Type 2 offenses. Gunshot wound was the leading cause of death in this group of offenses (70.0%). Half (50.0%) of Type 3 offenses were committed by multiple offenders working in concert; half (50.0%) were committed by a single offender working alone.

This offender group was the only type to be predominantly non-White (90.0%). Type 3 offenders were most often involved in a romantic relationship at the time of the offense (83.3%).

114

None of these offenders had criminally versatile backgrounds, and none had prior bias-motivated offenses on record. Consistent with the lack of post-offense theft in Type 3 cases, only one Type

3 offender had a history of committing theft or robbery or of drug-related offenses (which are often correlated with theft or robbery because of the need for money to support substance abuse).

Most were 25 years old or younger (70.0%). Most of these offenders (66.7%) were apprehended by law enforcement within 24 hours of committing their offense, and all were apprehended within one month.

Type 4: Racial/Ethnic without Provocation. Type 4 crime scenes were characterized by the absence of post-offense theft (5.6%). Most of these offenses took place outdoors, and most

Type 4 offenders left the victim’s body outdoors (81.3%). These offenses were more likely to involve multiple victims (27.8%) than Type 1 and Type 2 offenses. It was very uncommon for the victims of Type 4 offenses to be White (11.1%), because most racial/ethnic offenses with

White victims involved provocation – most commonly the utterance of racial slurs. Gunshot wounds were the leading cause of death in this group of offenses (66.7%). Just over half

(55.6%) of Type 4 offenses were committed by multiple offenders working in concert.

Most Type 4 offenders were affiliated with White Supremacist hate groups or racially/ethnically-identified gangs (72.7%) with known dislike of the victim’s in-group. Unlike

Type 3 offenders, all of the Type 4 offenders had been vocal about their racial or ethnic biases prior to their offenses (100.0%). Type 4 offenders commonly had prior histories of violent offenses (90.0%), but only 30.0% had previously committed bias-motivated offenses. Most were

25 years old or younger (64.7%). Most (90.0%) of these offenders were known to have had substance abuse problems. Most of these offenders were apprehended within one month of their offense (70.0%), but few were apprehended within 24 hours of their offense (20.0%).

115

Implications for Prevention and Rehabilitation

The high prevalence of substance abuse problems (39.7%) and substance use prior to the commission of these offenses (37.9%) demonstrates the potential utility of substance abuse interventions – particularly among gun owners and individuals who freely use racial and homophobic slurs – as a means of preventing bias-motivated homicide. The national 12-month prevalence of alcohol use disorders in the United States is estimated at 13.9% (Grant et al.,

2015), and the 12-month prevalence of drug use disorders in the United States is only about 3.9%

(Grant et al., 2016). These numbers are far lower than the prevalence in this sample of bias- motivated homicide offenders.

The National Epidemiologic Survey on Alcohol and Related Conditions III (NESARC-

III) indicates that those most vulnerable to developing substance use disorders are White and

Native American men, particularly those who are young, unmarried, less educated, and of lower socioeconomic status (Grant et al., 2015; Grant et al. 2016). This sample of bias-motivated homicide offenders mostly mirrors that demographic: nearly half were White men, more than half were adolescents or young adults, few were married, 20% did not complete high school, and most lacked steady legal employment. The link between substance abuse and violent crime has been studied extensively, but not in the bias-motivated homicide offender population; however, this relationship was detected by Hamm (1993) in his in-depth study of American Skinhead culture. He cited the disinhibiting effect of alcohol as the last step in a chain reaction that leads to the development of terroristic violence by young White Supremacist males.

Unfortunately, the prevalence of predatory acts of extreme violence, bragging, and criminal versatility in this sample, along with the infrequency of confessions, suggests that many of these offenders may meet the criteria for psychopathy. It is possible that many also would

116

meet the diagnostic criteria for Antisocial Personality Disorder (APD); however, although most criminally-involved individuals with psychopathy also meet criteria for APD, this diagnosis requires sufficient evidence that a pattern of destructive, deceitful, and abusive behavior began prior to the age of 15 (thus meeting criteria for Conduct Disorder). With mostly data on adult behavior, no assumptions regarding Conduct Disorder can be attempted. Nonetheless, despite many indicators of shallow affect, deceitfulness, parasitic lifestyle, etc., due to gaps in the information in this dataset, a thorough evaluation of psychopathy was not possible to conduct.

Several offenders, for whom substantial background information was available, appeared to preliminarily meet the threshold for psychopathy as measured by the PI using the Hare

Psychopathy Checklist-Revised (Hare, 1991).

Bell (1978), a psychoanalyst, explored a possible connection between racism and narcissism, which he observed in his treatment of white male patients. Bell (1978) compares racists to “murderers, child abusers, child molesters, and sadists” in their dehumanization of their victims and lack of respect for human life (p. 90). He states that racists are “only attentive to those characteristics (real or imagined) which are important to them and pay little attention to other attributes which the minority may possess” (Bell, 1978, p. 90). Bell (1978) picked up on a psychopathic tendency among the racists he has encountered in analysis. He observes:

“It is this lack of experience with empathic linkage which is characteristic of the racists I

have treated, and which has been traced to the original paradigm of interpersonal

relatedness, i.e., the relationship of the child with the mother. One does unto others what

has been done unto him” (Bell, 1978, p. 90).

He differentiates the narcissistic form of racism from racism that results from a more universal, cultural indoctrination, suggesting that the narcissist’s hostility is greater in intensity. It might

117

follow from this supposition that these narcissistic racists may be more prone to aggression and may, therefore, be those who become bias-motivated offenders. He suggests that the cultural racist is more likely to be ignorant, and therefore his racism can be tempered by education and exposure. The narcissistic racist, however, must experience a deeper healing of his core narcissistic wound in order to recover, suggesting the necessity of intensive, long-term psychotherapy for the rehabilitation of the racist offender.

Implications for Law Enforcement

It is important for law enforcement agencies to realize that the majority of hate crime victims, both in this sample and at the national level, are members of marginalized communities that have historically had strained relationships with the police. Understanding hate crime offender psychology is, therefore, especially important. NCVAC data (Langton & Planty, 2011) indicate that one reason that hate crime survivors choose not to report their victimization to law enforcement is because they believe that the police cannot or will not help them. In the period from 2003 to 2006, about 14% of survivors who did not report stated that this was their primary reason for not reporting; this proportion rose to 24% for the period from 2007 to 2011, indicating that law enforcement’s relationship with marginalized communities has been getting worse.

Increased public awareness of arrest-related deaths is likely to contribute to poor cooperation from communities of color, as the majority of victims who have died in police custody have been Black and Hispanic males (Burch, 2011). Furthermore, racial disparities in the use of deadly force by police officers have been documented consistently for decades (e.g.,

Fyfe, 1982; Goldkamp, 1976). Research (e.g., Weitzer & Tuch, 2004) has demonstrated that

Black and Hispanic community members report being exposed to more police misconduct and

118

are more likely to believe that police officers routinely engage in inappropriate behavior while on the job.

Previous research has suggested that, compared to other types of homicide, clearance rates for bias-motivated homicides are unusually low (e.g., Wilchins & Taylor, 2006). When hate crimes go unsolved and bias-motivated offenders go unpunished, it may send the message that this behavior is acceptable and that the prosecution of these crimes is not a priority, further marginalizing victims and their communities. For example, Riedel and Jarvis (1998) have noted that low clearance rates may contribute to secondary traumatization of victims’ family members and intensification of fear within victims’ communities. Furthermore, prejudices and stereotypes are strongly ingrained and resistant to change (e.g., Devine, 1989), which suggests that a bias- motivated offender may continue to hold views that could incite future acts of violence, either in the inmate population or in the community. It has also been suggested (McDevitt, 1989) that when bias-motivated offenders are not brought to justice, this empowers offenders and encourages future offending. It is, therefore, crucial that the body of knowledge on bias- motivated homicide be further developed and utilized by law enforcement officials and forensic clinicians.

Police departments and prosecutors appear reluctant to attach a hate crime status to an offense when Murder in the First Degree or Capital Murder can be easily asserted via other aspects of the offense (e.g., multiple deaths at one crime scene). In this sample, it was extremely rare that a case file noted the presence of physical evidence directly indicating bias, with the exception of those offenders associated with a hate group, who were frequently found to be in possession of hate-related paraphernalia upon search of the offender’s suspect, home, and vehicle.

119

Limitations

This data set cannot be used to extrapolate the prevalence of bias-motivated homicides nor the distribution of these offenses across the four proposed offense types, as the sample from which the data was derived was non-random and not necessarily nationally representative. This study also suffers from lack of statistical power due to small sample size. As a result, some effects may have been concealed by alpha levels just over the acceptable range. The cases themselves present some limitations, including missing data (especially about offender history) and a lack of offenses based on religion, disability, or other biases. Conclusions regarding homicides motivated by these other biases cannot be assumed to follow the patterns described herein. Furthermore, the sample is limited to cases prior to 2004; more recent cases may display different patterns as American attitudes about race, ethnicity, sexual orientation, and gender identity have continued to change.

Strengths

The present study provides preliminary evidence of the potential usefulness of a new typology to organize and categorize bias-motivated homicides. The study benefits from direct access to police files which include enough information for the researchers to confirm data through multiple complementary sources (e.g., crime scene photos and corroborating witness statements), as well as permitting the researchers to make their own determinations regarding crime scene features such as overkill (e.g., by viewing the number of injuries reported in the

Medical Examiner’s report).

A unique feature of this study is its ability to provide a closer look at the circumstances preceding bias-motivated homicides. Though jury research indicates that the public perception of hate crime is founded on cases in which a White offender appears to attack a person of color

120

(Marcus-Newhall, Blake, & Blake, 2002), the stories told by this sample suggest that the events leading up the bias-motivated homicide may be quite varied. While a portion of the offenders showed a predatory style – luring, tricking, or hunting their victims – another large portion of offenders saw themselves as justifiably reacting to a real or perceived threat in their environment. This additional information provides insight into the offenders’ mindsets and may lead the way to appropriate interventions for offender rehabilitation.

Future Directions

There remains much to be explored in the field of bias-motivated homicide. The prevention, intervention, and investigation of hate crimes will benefit from studies based on larger, nationally representative samples, and those that permit the observation of changes over time. As many of the offenders in this sample share characteristics with other types of offenders

(e.g., mass shooters), further exploration of similarities and differences between bias-motivated homicide offenders and other types of homicide offenders may be enlightening.

121

Table 1

Operational Definitions for Offender Variables

Variable Definition Offender Age Offender’s age in years at time of offense Race Offender’s race (White, Black, Latina/o, Asian, Other, or Unknown) Gender Offender’s gender (Male or Female) Sexual Orientation Offender’s sexual orientation (Heterosexual, LGB, or Unknown) Religion Offender’s religious affiliation Group Affiliation Evidence of offender affiliation with a gang or hate group at time of offense Disability Status Physical or psychological disability reported IQ Offender’s officially recorded IQ range Employment Offender’s employment status at time of offense (Full- time, Part-time, Inconsistent Employment, Illegal Income, or Unemployed) Field of Employment Offender’s field of employment (White collar or Blue collar) Marital Status Offender’s marital status at time of offense (Married, Single, or Divorced) Childhood Dysfunction Evidence of parental separation, domestic violence, illegal activity, or substance abuse in childhood living environment History of Abuse Evidence that offender experienced psychological, physical, or sexual abuse during youth Educational Difficulties Evidence of significant disciplinary or educational issues, including dropping out Mental/Emotional Instability Evidence of a history of psychiatric problems or severe emotional instability (e.g., firesetting) History of Substance Abuse Evidence of substance abuse history (Alcohol, Drugs, Both, or None) Indications of Bias Evidence of bias against target group in offender’s history (prior to offense), including membership in a hate organization and possession of hate paraphernalia Criminal Record Offender’s criminal history (Violent, Property, Sexual, Bias-Motivated, Drug-Related, or No Prior Offenses)

122

Table 2

Operational Definitions for Victim Variables

Variable Definition Age Victim’s age in years at time of offense Race Victim’s race (White, Black, Latina/o, Asian, Multiracial, or Unknown) Gender Victim’s gender (Male, Female, or Transgender) Sexual Orientation Victim’s sexual orientation, if noted (Heterosexual, LGB, or Unknown) Religion Victim’s religious affiliation Disability Status Physical or intellectual disability reported Sex Worker Evidence of victim history of engaging in sex work

123

Table 3 Operational Definitions of Situational Variables Variable Definition Circumstances Situation occurring immediately prior to offense (e.g., sexual advance, robbery, exchange of racial slurs) Location of Offense Location where homicide occurred (e.g., secluded area, victim’s residence) Victim Known by Offender Evidence of a prior relationship between victim and offender (i.e., had met previously) Offender Intoxicated Evidence that offender had been intoxicated at the time of the offense (e.g., alcohol use, marijuana use, cocaine use) Provocation Offender and/or witnesses allege that the victim did something to provoke a violent response from the offender Number of Offenders Number of perpetrators present at scene, per police records Number of Victims Number of victims murdered at scene, per police records

124

Table 4

McDevitt, Levin, & Bennett (2002) Typology

Expected Rater 1 Rater 2 Type Description Frequency Frequency Frequency Motivated by thrill- seeking; interest in social n = 19 n = 6 Thrill status 66% (32.8%) (10.3%)

Intended to send a message to the target’s group, to protect the n = 24 n = 17 Reactive/Defensive offender's turf 25% (41.4%) (29.3%)

Motivated by a personal ideology; offenders often hate group members or n = 10 n = 23 Mission suffering from paranoia <1% (17.2%) (39.7%)

Intended to restore honor after a real or perceived bias-motivated attack by the victim or members of n = 2 n = 7 Retaliatory the victim’s group 8% (3.4%) (12.1%)

Did not exhibit a clear n = 3 n = 5 Unclassifiable motivation 0% (5.2%) (8.6%)

125

Table 5

Proposed Bias-Motivated Homicide Typology

Type Description Example Frequency Crime targeting an individual Type 1: Anti- perceived to be LGBT w/ Offender kills gay man LGBT w/ indication of prior provocation after an unwanted sexual n = 15 Provocation or conflict advance (25.9%) Crime targeting an individual Type 2: Anti- perceived to be LGBT w/o LGBT w/o indication of prior provocation Offender intends to find n = 13 Provocation or conflict a gay man to rob (22.4%)

Crime targeting an individual Type 3: based on their perceived race Offender kills white Racial/Ethnic w/ or ethnicity w/ indication of man after he hurls racial n = 18 Provocation prior provocation or conflict epithets (31.0%)

Crime targeting an individual Offender intends to Type 4: based on their perceived race locate a person of color Racial/Ethnic or ethnicity w/o indication of to kill for hate group n = 10 w/o Provocation prior provocation or conflict initiation (17.2%)

126

Table 6 Intersectionality & Offense Variables Variable Valid Cases Intersectional Non-intersectional p Lured Victim n = 51 (87.9%) n = 2 (25.0%) n = 6 (14.0%) ns Body Left Outdoors n = 49 (84.5%) n = 7 (77.8%) n = 28 (70.0%) ns Blitz Attack n = 51 (87.9%) n = 1 (12.5%) n = 11 (25.6%) ns Sexual Situation n = 51 (87.9%) n = 5 (62.5%) n = 9 (20.9%) .028 Gunshot Wound n = 58 (100.0%) n = 2 (20.0%) n = 21 (43.8%) ns Stabbing n = 58 (100.0%) n = 5 (50.0%) n = 10 (20.8%) .069 Blunt Force Trauma n = 58 (100.0%) n = 2 (20.0%) n = 13 (27.1%) ns Injury by Vehicle n = 58 (100.0%) n = 0 (0.0%) n = 2 (4.2%) ns Primary Injury to Head n = 57 (98.3%) n = 1 (10.0%) n = 14 (29.8%) ns Primary Injury to Chest n = 57 (98.3%) n = 6 (60.0%) n = 23 (48.9%) ns Injury to Various Body Parts n = 57 (98.3%) n = 3 (30.0%) n = 10 (21.3%) ns Partial or Full Nudity n = 56 (96.6%) n = 3 (30.0%) n = 3 (6.5%) .063 Provocation n = 55 (94.8%) n = 3 (33.3%) n = 20 (43.5%) ns Weapon of Convenience n = 55 (94.8%) n = 2 (22.2%) n = 16 (34.8%) ns Overkill n = 55 (94.8%) n = 4 (44.4%) n = 14 (31.8%) ns Facial Trauma n = 56 (96.6%) n = 7 (70.0%) n = 22 (47.8%) ns Multiple Injuries to One Part n = 50 (86.2%) n = 6 (60.0%) n = 18 (45.0%) ns Manual Violence n = 57 (98.3%) n = 4 (40.0%) n = 10 (21.3%) ns Post-offense Theft n = 57 (98.3%) n = 1 (11.1%) n = 13 (27.1%) ns Staging n = 57 (98.3%) n = 0 (0.0%) n = 3 (6.3%) ns Planning n = 56 (96.6%) n = 4 (40.0%) n = 13 (28.3%) ns Disposal of Body n = 58 (100.0%) n = 1 (10.0%) n = 4 (8.3%) ns Disposal of Weapon n = 41 (70.7%) n = 3 (42.9%) n = 7 (20.6%) ns Post-offense Bragging n = 57 (98.3%) n = 1 (11.1%) n = 13 (27.1%) ns Victim Known by Offender n = 50 (86.2%) n = 2 (20.0%) n = 14 (35.0%) ns

127

Table 7 Victim-Offender Relationship & Offense Variables Variable Valid Cases Relationship No Relationship p Lured Victim n = 45 (77.6%) n = 2 (12.5%) n = 4 (13.8%) ns Body Left Outdoors n = 42 (72.4%) n = 5 (41.7%) n = 26 (86.7%) .006 Blitz Attack n = 45 (77.6%) n = 1 (6.3%) n = 10 (34.5%) .035 Sexual Situation n = 45 (77.6%) n = 7 (46.7%) n = 6 (20.0%) .086 Gunshot Wound n = 50 (86.2%) n = 5 (31.3%) n = 13 (38.2%) ns Stabbing n = 50 (86.2%) n = 4 (25.0%) n = 10 (29.4%) ns Blunt Force Trauma n = 50 (86.2%) n = 6 (37.5%) n = 7 (20.6%) ns Injury by Vehicle n = 50 (86.2%) n = 0 (0.0%) n = 2 (5.9%) ns Primary Injury to Head n = 50 (86.2%) n = 3 (18.8%) n = 9 (26.5%) ns Primary Injury to Chest n = 50 (86.2%) n = 8 (50.0%) n = 19 (55.9%) ns Injury to Various Body Parts n = 50 (86.2%) n = 5 (31.3%) n = 6 (17.6%) ns Partial or Full Nudity n = 48 (82.8%) n = 2 (13.3%) n = 4 (12.1%) ns Provocation n = 47 (81.0%) n = 8 (50.0%) n = 14 (45.2%) ns Weapon of Convenience n = 47 (81.0%) n = 8 (50.0%) n = 11 (35.5%) ns Overkill n = 48 (82.8%) n = 8 (53.3%) n = 9 (27.3%) .078 Facial Trauma n = 49 (84.5%) n = 9 (60.0%) n = 16 (47.1%) ns Multiple Injuries to One Part n = 44 (75.9%) n = 7 (53.8%) n = 15 (48.4%) ns Manual Violence n = 49 (84.5%) n = 4 (25.0%) n = 8 (24.8%) ns Post-offense Theft n = 49 (84.5%) n = 4 (25.0%) n = 6 (18.2%) ns Staging n = 49 (84.5%) n = 2 (12.5%) n = 1 (3.0%) ns Planning n = 49 (84.5%) n = 5 (33.3%) n = 9 (26.5%) ns Disposal of Body n = 50 (86.2%) n = 1 (6.3%) n = 3 (8.8%) ns Disposal of Weapon n = 34 (58.6%) n = 1 (9.1%) n = 8 (34.8%) ns Post-offense Bragging n = 36 (62.1%) n = 1 (7.1%) n = 8 (36.4%) .062 LGBT Victim n = 50 (86.2%) n = 9 (56.3%) n = 18 (52.9%) ns

128

Table 8 Bias Type & Offense Variables Variable Valid Cases Racial/Ethnic Anti-LGBT p Lured Victim n = 51 (87.9%) n = 2 (7.7%) n = 6 (24.0%) ns Body Left Outdoors n = 49 (84.5%) n = 22 (89.0%) n = 13 (54.2%) .012 Blitz Attack n = 51 (87.9%) n = 9 (34.6%) n = 3 (12.0%) .097 Sexual Situation n = 51 (87.9%) n = 0 (0.0%) n = 56 (11.0%) <.001 Gunshot Wound n = 58 (100.0%) n = 20 (69.0%) n = 3 (10.3%) <.001 Stabbing n = 58 (100.0%) n = 4 (13.8%) n = 11 (37.9%) .036 Blunt Force Trauma n = 58 (100.0%) n = 3 (10.3%) n = 12 (41.4%) .015 Injury by Vehicle n = 58 (100.0%) n = 2 (6.9%) n = 0 (0.0%) ns Primary Injury to Head n = 57 (98.3%) n = 8 (28.6%) n = 7 (24.1%) ns Primary Injury to Chest n = 57 (98.3%) n = 13 (46.4%) n = 16 (55.2%) ns Injury to Various Body Parts n = 57 (98.3%) n = 7 (25.0%) n = 6 (20.7%) ns Partial or Full Nudity n = 56 (96.6%) n = 0 (0.0%) n = 6 (21.4%) .023 Provocation n = 55 (94.8%) n = 8 (28.6%) n = 13 (48.1%) .112 Weapon of Convenience n = 55 (94.8%) n = 5 (17.2%) n = 13 (50.0%) .020 Overkill n = 55 (94.8%) n = 6 (22.2%) n = 12 (42.9%) ns Facial Trauma n = 56 (96.6%) n = 13 (46.4%) n = 16 (57.1%) ns Multiple Injuries to One Part n = 50 (86.2%) n = 9 (36.0%) n = 15 (60.0%) ns Manual Violence n = 57 (98.3%) n = 6 (20.7%) n = 8 (28.6%) ns Post-offense Theft n = 57 (98.3%) n = 1 (3.4%) n = 13 (46.4%) <.001 Staging n = 57 (98.3%) n = 0 (0.0%) n = 3 (10.7%) ns Planning n = 56 (96.6%) n = 9 (32.1%) n = 8 (28.6%) ns Disposal of Body n = 58 (100.0%) n = 2 (6.9%) n = 3 (10.3%) ns Disposal of Weapon n = 41 (70.7%) n = 3 (15.0%) n = 7 (33.3%) ns Post-offense Bragging n = 42 (72.4%) n = 7 (38.9%) n = 4 (16.7%) ns Victim Known by Offender n = 50 (86.2%) n = 7 (29.2%) n = 9 (34.6%) ns Multiple Offenders n = 58 (100.0%) n = 16 (55.2%) n = 5 (17.2%) .006

129

Table 9 Provocation & Offense Variables

Variable Valid Cases Provocation No Provocation p Lured Victim n = 50 (86.2%) n = 0 (0.0%) n = 8 (28.6%) .006 Body Left Outdoors n = 47 (81.0%) n = 12 (63.2%) n = 22 (78.6%) ns Blitz Attack n = 50 (86.2%) n = 0 (0.0%) n = 12 (42.9%) <.001 Sexual Situation n = 49 (84.5%) n = 11 (50.0%) n = 3 (11.1%) .004 Gunshot Wound n = 54 (93.1%) n = 6 (26.1%) n = 16 (51.6%) .093 Stabbing n = 54 (93.1%) n = 8 (34.8%) n = 5 (16.1%) ns Blunt Force Trauma n = 54 (93.1%) n = 5 (21.7%) n = 9 (29.0%) ns Injury by Vehicle n = 54 (93.1%) n = 1 (4.3%) n = 1 (3.2%) ns Primary Injury to Head n = 53 (91.4%) n = 6 (26.1%) n = 8 (26.7%) ns Primary Injury to Chest n = 53 (91.4%) n = 14 (60.9%) n = 12 (40.0%) ns Injury to Various Parts n = 53 (91.4%) n = 3 (13.0%) n = 10 (33.3%) ns Partial or Full Nudity n = 52 (89.7%) n = 3 (13.6%) n = 1 (3.3%) ns Weapon of Convenience n = 53 (91.4%) n = 10 (50.0%) n = 7 (21.2%) .038 Overkill n = 51 (87.9%) n = 6 (28.6%) n = 11 (36.7%) ns Facial Trauma n = 52 (89.7%) n = 13 (56.5%) n = 15 (51.7%) ns Multiple Injuries to One Part n = 47 (81.0%) n = 9 (45.0%) n = 12 (44.4%) ns Manual Violence n = 53 (91.4%) n = 8 (36.4%) n = 6 (19.4%) ns Post-offense Theft n = 53 (91.4%) n = 5 (21.7%) n = 7 (23.2%) ns Staging n = 54 (93.1%) n = 2 (8.7%) n = 1 (3.2%) ns Planning n = 52 (89.7%) n = 5 (22.7%) n = 12 (40.0%) ns Disposal of Body n = 54 (93.1%) n = 2 (8.7%) n = 3 (9.7%) ns Disposal of Weapon n = 38 (65.5%) n = 3 (16.7%) n = 4 (20.0%) ns Post-offense Bragging n = 40 (69.0%) n = 2 (10.5%) n = 8 (38.1%) .048 LGBT Victim n = 54 (93.1%) n = 14 (60.9%) n = 12 (38.7%) ns Victim Known by Offender n = 46 (79.3%) n = 9 (40.9%) n = 7 (29.2%) ns

130

Table 10

Proposed Bias-Motivated Homicide Typology & Offense Variables

Variable Type 1 Type 2 Type 3 Type 4 p n = 1 n = 5 n = 0 n = 2 Lured Victim (8.3%) (38.5%) (0.0%) (12.5%) .064 n = 5 n = 8 n = 8 n = 13 Body Left Outdoors (45.5%) (66.7%) (100.0%) (81.3%) .049 n = 0 n = 3 n = 0 n = 8 Blitz Attack (0.0%) (23.1%) (0.0%) (50.0%) .004 n = 8 n = 6 n = 0 n = 0 Sexual Situation (66.7%) (46.2%) (0.0%) (0.0%) <.001 n = 1 n = 2 n = 7 n = 12 Gunshot Wound (7.7%) (13.3%) (70.0%) (66.7%) <.001 n = 5 n = 5 n = 1 n = 3 Stabbing (38.5%) (33.3%) (10.0%) (16.7%) ns n = 5 n = 7 n = 1 n = 2 Blunt Force Trauma (38.5%) (46.7%) (10.0%) (11.1%) .055 n = 0 n = 0 n = 1 n = 1 Injury by Vehicle (0.0%) (0.0%) (10.0%) (5.6%) ns n = 5 n = 2 n = 3 n = 4 Primary Injury to Head (38.5%) (13.3%) (30.0%) (23.5%) ns n = 7 n = 8 n = 5 n = 8 Primary Injury to Chest (53.8%) (53.3%) (50.0%) (47.1%) ns n = 1 n = 5 n = 2 n = 5 Injury to Various Parts (7.7%) (33.3%) (20.0%) (29.4%) ns n = 2 n = 3 n = 0 n = 0 Partial or Full Nudity (15.4%) (21.4%) (0.0%) (0.0%) ns n = 8 n = 5 n = 2 n = 3 Weapon of Convenience (66.7%) (35.7%) (20.0%) (16.7%) .028 n = 4 n = 8 n = 1 n = 5 Overkill (33.3%) (53.3%) (11.1%) (29.4%) ns n = 8 n = 8 n = 4 n = 8 Facial Trauma (61.5%) (57.1%) (40.0%) (47.1%) ns n = 6 n = 8 n = 3 n = 6 Multiple Injuries to One Part (54.5%) (61.5%) (37.5%) (37.5%) ns n = 3 n = 5 n = 3 n = 3 Manual Violence (25.0%) (33.3%) (30.0%) (16.7%) ns n = 6 n = 7 n = 0 n = 1 Post-offense Theft (46.2%) (50.0%) (0.0%) (5.6%) .002 n = 1 n = 2 n = 0 n = 0 Staging (7.7%) (13.3%) (0.0%) (0.0%) ns n = 2 n = 6 n = 3 n = 6 Planning (15.4%) (42.9%) (30.0%) (35.3%) ns

131

n = 2 n = 1 n = 0 n = 2 Disposal of Body (15.4%) (6.7%) (0.0%) (11.1%) ns n = 3 n = 4 n = 1 n = 2 Disposal of Weapon (30.0%) (36.4%) (12.5%) (16.7%) ns n =2 n = 2 n = 1 n = 6 Post-offense Bragging (16.7%) (16.7%) (16.7%) (50.0%) ns n =5 n = 4 n = 2 n = 5 Victim Known by Offender (41.7%) (30.8%) (22.2%) (33.3%) ns

132

Appendix A Data Collection Sheet

133

134

Appendix B

Ad Hoc Expressive-Instrumental Scales

Expressive Variables (0 to 6) 1. Facial Violence: Injury to the victim’s face 2. Stabbing: Use of a knife to stab the victim 3. Blunt Force Trauma: Use of a blunt object to beat or knock victim unconscious 4. Weapon of Convenience: Use of an object found at the scene of the crime as a weapon 5. Multiple Wounds to Same Area of Body: Repeated injury to a single area of the victim’s body 6. Manual Violence: Use of hands as a weapon (e.g., to beat or strangle) the victim

Instrumental Variables (0 to 2) 1. Sexual Activity with Victim: Offender attempts or completes sexual activity with the victim 2. Theft or Robbery: Offender takes money, car, keys, etc. from the victim prior to or after death

135

Appendix C

Sample Indicators of Offender Bias

Anti-LGBT Offender left graffiti stating: “All f---s die” Offender stated he planned to go “f---bashing” Offender approached victim asking, “Do you want a piece of me, f----?” Offender told friend he killed victim “because he was a f--”

Racial/Ethnic Offender known Skinhead with symbolic spiderweb tattoo indicating prior racial murder(s) Offender stated reason for offense was “because I don’t like Mexicans” Offender had prior complaints of violence toward members of victim’s racial group Offender owned Mein Kampf and told neighbors “I’ll kill all you n---s”

136

References

Abraham, N. (1994). Anti-Arab racism and violence in the United States. In E. McCarus (Ed.), The development of Arab-American identity (pp. 155-214). Ann Arbor: University of Michigan Press. Abu-Raiya, H., Pargament, K. I., & Mahoney, A. (2011). Examining coping methods with stressful interpersonal events experienced by Muslims living in the United States following the 9/11 attacks. Psychology of Religion and Spirituality, 3(1), 1-14. doi: 10.1037/a0020034 Abu-Ras, W. M., & Suarez, Z. E. (2009). Muslim men and women’s perception of discrimination, hate crimes, and PTSD symptoms post 9/11. Traumatology, 15(3), 48-63. doi: 10.1177/1534765609342281 Adams, H., Wright, L.W., & Lohr, B. (1996). Is homophobia associated with homosexual arousal? Journal of Abnormal Psychology, 105(3), 440-445. doi: 10.1037/0021- 843X.105.3.440 Alden, H., & Parker, K. (2005). Gender role ideology, homophobia and hate crime: Linking attitudes to macro-level anti-gay and lesbian hate crimes. Deviant Behavior, 26(4), 321- 343. doi: 10.1080/016396290931614 Alvarez Cussen, S. L. (2017). Patterns of injury in homicide relationships: Clinical, psychological, and investigative implications. New York: CUNY Academic Works. Anderson, J. F., Dyson, L., & Brooks, W. (2002). Preventing hate crime and profiling hate crime offenders. Western Journal of Black Studies, 26(3), 140-148. Anti-Defamation League (2014). ADL Global 100: An index of Anti-Semitism. New York: Author. Retrieved from http://www.global100.adl.org Anti-Defamation League (2015). Audit: In 2014 anti-Semitic incidents rose 21 percent across the U.S. in a “particularly violent year for Jews.” New York: Author. Retrieved from http://www.adl.org/press-center/press-releases/anti-semitism-usa/adl-audit-in-2014-anti- semitic-incidents.html Arab-American Anti-Discrimination Committee (1997). 1996-1997 Report on Hate Crimes and Discrimination against Arab Americans. Washington, DC: ADC Research Institute. Arrigo, B.A. (2006). Criminal behavior: A systems approach. Boston, MA: Pearson. Avery, A., Chase, J., Johannson, L., Litvak, S., Montero, D., & Wydra, M. (2007). America’s changing attitudes toward homosexuality, civil unions, and same-gender marriage: 1977- 2004. Social Work, 51(1), 71-79. doi: 10.1093/sw/52.1.71 Baker, J. G., & Fishbein, H. D. (1998). The development of prejudice toward gays and lesbians by adolescents. Journal of Homosexuality, 36, 89-100. doi: 10.1300/J082v36n01_06 Baladerian, N. (1991). Sexual abuse of people with developmental disabilities. Sexuality and Disability, 9, 323-335. Bankston, C. L. (2006). Filipino Americans. In P.G. Min (Ed.), Asian Americans: Contemporary trends and issues (2nd ed.). Thousand Oaks, CA: Pine Forge Press. Bargh, J. A., & Pietromonaco, P. (1982). Automatic information processing and social perception: The influence of trait information presented outside of conscious awareness on impression formation. Journal of Personality and Social Psychology, 43(3), 437-449. doi: 10.1037/0022-3514.43.3.437 Barker, K., Wright, C., & Goodman, D. (2015, June 29). How a life that showed promise veered into violence against Asian women. The New York Times. Retrieved from

137

http://www.nytimes.com/ Basow, S. A., & Johnson, K. (2000). Predictors of homophobia in female college students. Sex Roles, 42(5-6), 391-404. doi: 10.1023/A:1007098221316 Beirich, H., & Potok, M. (2009). USA: Hate groups, radical-right violence, on the rise. Policing, 3(3), 255-263. doi: 10.1093/police/pap020 Bell, C. (1978). Racism, narcissism, and integrity. Journal of the National Medical Association, 70(2), 89-92. Bell, M. D., & Vila, R. I. (1996). Homicide in homosexual victims: A study of 67 cases from the Broward County, Florida, Medical Examiner's Office (1982-1992), with special emphasis on “overkill.” The American Journal of Forensic Medicine and Pathology, 17(1), 65-69. Bergmann, W., & Wetzel, J. (2003). Manifestations of anti-Semitism in the European Union. Vienna: The European Monitoring Centre on Racism and Xenophobia. Berk, R. A., Boyd, E. A., & Hamner, K. (2003). Thinking more clearly about hate-motivated crimes. In B. Perry (Ed.), Hate and bias crime (pp. 49-60). New York: Routledge. Berlet, C. & Lyons, M. N. (2000). Right-wing populism in America: Too close for comfort. New York: Guilford Press. Berrill, K. (Ed.). (1992). Hate crimes: Confronting violence against lesbians and gay men. Thousand Oaks, CA: Sage Publications. Berrill, K. (1993). Anti-gay violence: Causes, consequences, and responses. In R. J. Kelly (Ed.), Bias crime: American law enforcement and legal responses (pp. 151- 164). Chicago: University of Illinois at Chicago Press. Black, H. C., & Nolan, J. R. (n.d./1993). Black's law dictionary: Definitions of the terms and phrases of American and English jurisprudence ancient and modern [with pronunciations]. Retrieved from https://thelawdictionary.org Blalock, H. M. (1967). Toward a theory of minority-group relations. New York: Wiley. Blazak, R. (2009). Introduction. In B. Perry & R. Blazak (Eds.), Hate crimes: Hate crime offenders (Vol. 4, pp. xiii-xvii). Westport, CT: Praeger. Blee, K. M. (1996). Becoming a racist: Women in contemporary Ku Klux Klan and Neo-Nazi groups. Gender and Society, 10, 685-697. doi: 10.1177/089124396010006002 Bobo, L., & Hutchings, V. L. (1996). Perceptions of racial group competition: Extending Blumer’s theory of group position to a multiracial social context. American Sociological Review, 61, 951-972. Retrieved from http://www.jstor.org/stable/2096302 Bouton, R. A., Gallaher, P. E., Garlinghouse, P. A., Leal, T., Rosenstein, L. D., & Young, R. K. (1987). Scales for measuring fear of AIDS and homophobia. Journal of Personality Assessment, 51(4), 606-614. doi: 10.1207/s15327752jpa5104_13 Bronski, M. (2011). A queer history of the United States. Boston, MA: Beacon Press. Bronski, M., Pellegrini, A., & Amico, M. (2013). “You can tell just by looking” and 20 other myths about LGBT life and people. Boston, MA: Beacon Press. Brownmiller, S. (1975). Against our will: Men, women, and rape. New York: Bantam Books. Bufkin, J. L. (1999). Bias crime as gendered behavior. Social Justice, 26(1), 155-176. Retrieved from http://www.jstor.org/stable/29767117 Burch, A. M. (2011, November 17). Arrest-related deaths, 2003-2009 – Statistical tables. Washington, DC: Bureau of Justice Statistics. Retrieved from http://www.bjs.gov Burgdorf, R. L. (2000). Assisted suicide: A disability perspective. In B. T. McMahon & L. R. Shaw (Eds.), Enabling lives (pp. 199-228). Boca Raton, FL: CRC Press.

138

Byers, B. D., & Crider, B. W. (2002). Hate crimes against the Amish: A qualitative analysis of bias motivation using routine activities theory. Deviant Behavior, 23(2), 115-148. doi: 10.1080/016396202753424529 Byers, B., Crider, B. W., & Biggers, G. K. (1999). Bias crime motivation: A study of hate crime and offender neutralization techniques used against the Amish. Journal of Contemporary Criminal Justice, 15(1), 78-96. doi: 10.1177/1043986299015001006 Campo-Engelstein, L. (2016). Rape as a hate crime: An analysis of New York law. Hypatia, 31(1), 91-106. Caputi, J., & Russell, D. E. H. (1992). Femicide: Sexist terrorism against women. New York: Twayne Publishers. Cardenas, G. (1975). United States immigration policy toward Mexico: An historical perspective. Chicana/o Latina/o Law Review, 2, 66-91. Retrieved from https://escholarship.org/uc/item/0fh8773n Carney, K. M. (2012). Rape: The paradigmatic hate crime. St. John’s Law Review, 75(2), 315-356. Retrieved from http://scholarship.law.stjohns.edu/lawreview/vol75/iss2/19 Carrigan, W. D., & Webb, C. (2003). The lynching of persons of Mexican origin or descent in the United States, 1848 to 1928. Journal of Social History, 37(2), 411-438. doi: 10.1353/jsh.2003.0169 Castle, T. L. (2009). Female-perpetrated hate: A content analysis of hate incidents. In B. Perry & R. Blazak (Eds.), Hate crimes: Hate Crime Offenders (Vol. 4, pp. 85-101). Westport, CT: Praeger. Center for the Study of Hate and Extremism (2017). Final U.S. status report: Hate crime analysis & forecast for 2016/2017. Santa Barbara, CA: Author. Retrieved from: https://csbs.csusb.edu/hate-and-extremism-center/data-reports/hate-crime-data-and- reports Center for Women’s Policy Studies (1991). Violence against women as biased motivated hate crime: Defining the issues. Washington, DC: Author. Chalmers, D. M. (1981). Hooded Americanism. New York: Franklin Watts. Cheng, W., Ickes, W., & Kenworthy, J. B. (2013). The phenomenon of hate crimes in the United States. Journal of Applied Social Psychology, 43(4), 761-794. doi: 10.1111/jasp.12004 Chermak, S., Freilich, J., & Suttmoeller., M. (2013). The organizational dynamics of far-right hate groups in the United States: Comparing violent to nonviolent organizations. Studies in Conflict & Terrorism, 36(3), 193-218. doi: 10.1080/1057610X.2013.755912 Chicago Police Department (2014). 2011 Chicago murder analysis. Chicago, IL: Author. Chinese Railroad Workers in North America Project (2015). Frequently asked questions. Stanford, CA: Stanford University. Retrieved from http://web.stanford.edu/group/chineserailroad/cgi-bin/wordpress/faqs/ Civil Rights Act of 1968, P. L. 90–284, 82 Stat. 73 (2013). Retrieved from http://legcounsel.house.gov/Comps/civil68.pdf Clements-Nolle, K., Marx, R., & Katz, M. (2006). Attempted suicide among transgender persons: The influence of gender-based discrimination and victimization. Journal of Homosexuality, 51(3), 53-69. doi: 10.1300/J082v51n03_04 Cornell, D. G., Warren, J., Hawk, G., Stafford, E., Oram, G., & Pine, D. (1996). Psychopathy in instrumental and reactive violent offenders. Journal of Consulting and Clinical Psychology, 64(4), 783–790. doi: 10.1037/0022-006X.64.4.783 Cotton, P. (1992). Attacks on homosexual persons may be increasing, but many ‘bashings’ still

139

aren’t reported. The Journal of the American Medical Association, 267, 2999-3001. doi: 10.1001/jama.1992.03480220017004 Council on American-Islamic Relations (2006). American public opinion about Islam and Muslims. Washington, DC: Author. Retrieved from www.cair.com Council on American-Islamic Relations (2007). The presumption of guilt. Washington, DC: Author. Retrieved from www.cair.com Council on American-Islamic Relations (2008). Without fear of discrimination. Washington, DC: Author. Retrieved from www.cair.com Cowan, G., & Hodge, C. (1996). Judgments of hate speech: The effects of target group, publicness, and behavioral responses of the target. Journal of Applied Social Psychology, 26, 355-374. doi: 10.1111/j.1559-1816.1996.tb01854.x Craig, K. (2002). Examining hate-motivated aggression: A review of the social-psychology literature on hate crimes as a distinct form of aggression. Aggression & Violent Behavior, 7, 85-99. doi: 10.1016/S1359-1789(00)00039-2 Daly, M., & Wilson, M. (1988). Evolutionary social psychology and family homicide. Science, 242(4878), 519-524. doi: 10.1126/science.3175672 Davis, L. S. (2011). Victim-offender relationships and crime scene behavior correlates in serial and single-victim sexual homicide (Unpublished master’s thesis). John Jay College of Criminal Justice, New York. Davis, L. S., & Schlesinger, L. B. (2012/2016). Animal cruelty, firesetting, and homicide. In M. P. Brewster & C. L. Reyes (Eds.), Animal cruelty and the criminal justice system. Durham, NC: Carolina Academic Press. Devine, P. (1989). Stereotypes and prejudice: Their automatic and controlled components. Journal of Personality and Social Psychology, 56(1), 5-18. District of Columbia Public Schools (2007). Youth Risk Behavior Survey sexual minority baseline fact sheet: Senior high school YRBS 2007 baseline findings for GLBQ items. Washington, DC: District of Columbia Public Schools HIV/AIDS Education Program. Douglass, J. E., Burgess, A. W., Burgess, A. G., & Ressler, R. K. (1992/2013). Crime classification manual. New York: Lexington Books. Dollard, J. (1937). Caste and class in a Southern town. New Haven, CT: Yale University Press. Dovidio, J. F., Kawakami, K., & Gaertner, S. L. (2002). Implicit and explicit prejudice and interracial interaction. Journal of Personality and Social Psychology, 82(1), 62-68. Dovidio, J. F., Mann, J., & Gaertner, S. L. (1989). Resistance to affirmative action: The implications of aversive racism. In Affirmative action in perspective (pp. 83-102). New York: Springer. Dozier, Jr., R. (2002). Why we hate. New York: McGraw-Hill. Dunbar, E. (2003). Symbolic, relational, and ideological signifiers of bias-motivated offenders: Toward a strategy of assessment. American Journal of Orthopsychiatry, 73(2), 203-211. doi: 10.1037/0002-9432.73.2.203 Dunbar, E., Quinones, J., & Crevecoeur, D. A. (2005). Assessment of hate crime offenders: The role of bias intent in examining violence risk. Journal of Forensic Psychology Practice, 5(1), 1-19. doi: 10.1300/J158v05n01_01 Duncan, B. L. (1976). Differential social perception and attribution of intergroup violence: Testing the lower limits of stereotyping of blacks. Journal of Personality and Social Psychology, 34, 590-598. Ehrlich, H., Larcom, B. E., & Purvis, R. D. (2003). The traumatic effects of ethnoviolence. In

140

B. Perry (Ed.), Hate and bias crime (pp. 153-217). New York: Routledge. Eronen, M., Hakola, P., & Tiihonen, J. (1996). Factors associated with homicide recidivism in a 13-year sample of homicide offenders in Finland. Psychiatric Services, 40(4), 403-406. doi: 10.1177/0886260513517302 Fazel, S., & Grann, M. (2004). Psychiatric morbidity among homicide offenders: A Swedish population study. The American Journal of Psychiatry, 161(11), 2129-2131. doi: 10.1176/appi.ajp.161.11.2129 Feshbach, S. (1964). The function of aggression and the regulation of aggressive drive. Psychological Review, 71(4), 257-272. Felthous, A. R., Hempel, A. G., Heredia, A., Freeman, E., Goodness, K., Holzer, C., ... & Korndorffer, W. E. (2001). Combined homicide-suicide in Galveston County. Journal of Forensic Sciences, 46(3), 586-592. doi: 10.1520/JFS15007J Fisher, C. (2007). Extreme prejudice: A behavioral analysis of bias-motivated homicides. Ann Arbor, MI: UMI Dissertations Publishing. Fisher, C., & Salfati, C. G. (2009). Behavior or motivation: Typologies of hate-motivated offenders. In B. Perry & R. Blazak (Eds.), Hate crimes: Hate crime offenders (Vol. 4; pp. 103-135). Westport, CT: Praeger. Fox, K. A., & Allen, T. (2014). Examining the instrumental–expressive continuum of homicides: Incorporating the effects of gender, victim–offender relationships, and weapon choice. Homicide Studies, 18(3), 298-317. doi: 10.1177/1088767913493420 Franklin, K. (1998). Unassuming motivations: Contextualizing the narratives of antigay assailants. In G. M. Herek (Ed.), Stigma and sexual orientation: Understanding prejudice against lesbians, gay men, and bisexuals (pp. 1-23). Thousand Oaks, CA: Sage Publications. Franklin, K. (2000). Antigay behaviors among young adults: Prevalence, patterns, and motivators in a noncriminal population. Journal of Interpersonal Violence, 15(4), 339- 362. doi: 10.1177/088626000015004001 Freud, S. (1917/1977). Introductory lectures on psychoanalysis: The standard edition. New York: Norton. Fyfe, J. J. (1982). Blind justice: Police shootings in Memphis. Journal of Criminal Law & Criminology, 73(2), 707-722. Gadd, D., & Dixon, B. (2009). Posing the “why” question: Understanding the perpetration of racially motivated violence and harassment. In B. Perry & B. Levin (Eds.), Hate crimes: Understanding and defining hate crime (Vol. 1, pp. 77-94). Westport, CT: Praeger. Garofalo, J., & Martin, S. E. (1993). Bias-motivated crimes: Their characteristics and the law enforcement response (Final report to the National Institute of Justice). Carbondale, IL: Southern Illinois University, Center for the Study of Crime, Delinquency and Corrections. Garland, J. (2011). Difficulty in defining hate crime victimization. International Review of Victimology, 18(1), 25-37. doi: 10.1177/0269758011422473 Garnets, L., Herek, G. M., & Levy, B. (1990). Violence and victimization of lesbians and gay men: Mental health consequences. Journal of Interpersonal Violence, 5(3), 366-383. doi: 10.1177/088626090005003010 Gibson, R. (2006). From zero to 24-7: Images of sexual minorities on television. In L. Castaneda & S. B. Campbell (Eds.), News and sexuality: Media portraits of diversity (pp. 257-278). Thousand Oaks, CA: Sage.

141

Goldblum, P., Testa, R. J., Pflum, S., Hendricks, M. L., Bradford, J., & Bongar, B. (2012). The relationship between gender-based victimization and suicide attempts in transgender people. Professional Psychology: Research and Practice, 43(5), 468-475. doi: 10.1037/a0029605 Goldkamp, J. S. (1976). Minorities as victims of police shootings: Interpretations of racial disproportionality and police use of deadly force. The Justice System Journal, 2(2), 169- 183. Goldscheid, J. (1999). Gender motivated violence: Developing a meaningful paradigm for civil rights enforcement. Harvard Women’s Law Journal, 123, 130-132. Grant, B. F., Goldstein, R. B., Saha, T. D., et al. (2015). Epidemiology of DSM-5 alcohol use disorder: Results from the National Epidemiologic Survey on Alcohol and Related Conditions III. JAMA Psychiatry, 72(8), 757–766. doi: 10.1001/jamapsychiatry.2015.0584 Grant, B. F., Saha, T. D., Ruan, W. J., et al. (2016). Epidemiology of DSM-5 drug use disorder: Results from the National Epidemiologic Survey on Alcohol and Related Conditions– III. JAMA Psychiatry, 73(1), 39–47. doi: 10.1001/jamapsychiatry.2015.2132 Grant, J. M., Mottet, L. A., Tanis, J., Harrison, J., Herman, J. L., & Keisling, M. (2011). Injustice at every turn: A report of the National Transgender Discrimination Survey. Washington, DC: National Center for Transgender Equality and National Gay and Lesbian Task Force. Grattet, R., & Jenness, V. (2001). Examining the boundaries of hate crime law: Disabilities and the dilemma of difference. Journal of Criminal Law and Criminology, 91(3), 653-698. doi: 10.2307/1144301 Green, C. M. (1981). Matricide by sons. Medicine, Science and the Law, 21(3), 207-214. Green, D., Glaser, J., & Rich, A. (1998). From lynchings to gay bashing: The elusive connection between economic conditions and hate crimes. Journal of Personality and Social Psychology, 75(1), 82-92. doi: 10.1037/0022-3514.75.1.82 Green, D. P., Strolovitch, D. Z., & Wong, J. S. (1998). Defended neighborhoods, integration, and racially motivated crime. American Journal of Sociology, 104(2), 372-403. doi: 10.1086/210042 Grigera, E. (1999). Hate crimes: State and federal responses to bias-motivated violence. Corrections Today, 61(5), 68-80. Grimes, W. (2017, March 22). George Weinberg dies at 87; Coined ‘homophobia’ after seeing fear of gays. The New York Times. Retrieved from: https://www.nytimes.com/2017/03/22/us/george-weinberg-dead-coined- homophobia.html Gruenewald, J. (2011). A comparative examination of homicides perpetrated by far-right extremists. Homicide Studies, 15(2), 177-203. doi: 10.1177/1088767911408029 Gruenewald, J., & Kelley, K. (2014). Exploring anti-LGBT homicide by mode of victim selection. Criminal Justice and Behavior, 41(9), 1130-1152. doi: 10.1177/0093854814541259 Hamm, M. S. (1993). American skinheads: The criminology and control of hate crime. Westport, CT: Praeger. Haney, C., Banks, W. C., & Zimbardo, P. G. (1973). A study of prisoners and guards in a simulated prison. Naval Research Review, 30, 4-17. Hansen, A. L. (2007). School-based support for GLBT students: A review of three levels of

142

research. Psychology in the Schools, 44(8), 839-848. doi: 10.1002/pits.20269 Hare, R. D. (1991). Manual for the Hare Psychopathy Checklist - Revised. Toronto: Multi- Health Systems. Harlow, C. W. (2005). Hate crime reported by victims and police. Washington, DC: Bureau of Justice Statistics. Hate Crime Sentencing Enhancement Act, 28 U.S.C. § 534 (1990). Hatterer, L. (1970). Changing homosexuality in the male. New York: McGraw-Hill. Hazelwood, R. R., & Douglas, J. E. (1980). The lust murderer. FBI Law Enforcement Bulletin, 49(3), 18-22. Hegerty, P., Pratto, F., & Lemieux, A. F. (2004). Heterosexist ambivalence and heterocentric norms: Drinking in intergroup discomfort. Group Processes and Intergroup Relations, 7, 119-130. doi: 10.1177/1368430204041399 Henry, J. S. (2009). Hate crime laws: A critical assessment. In B. Perry & B. Levin (Eds.), Hate crimes: Understanding and defining hate crime (Vol. 1, pp. 163-182). Westport, CT: Praeger. Herek, G. M. (1984). Beyond “homophobia”: A social psychological perspective on attitudes toward lesbians and gay men. Journal of Homosexuality, 10, 39-51. doi: 10.1300/J082v10n01_01 Herek, G. M. (1986). On heterosexual masculinity: Some psychical consequences of the social construction of gender and sexuality. American Behavioral Scientist, 29, 563-577. doi: 000276486029005005 Herek, G. M. (1988). Heterosexuals’ attitudes toward lesbians and gay men: Correlates and gender differences. Journal of Sex Research, 25, 451-477. doi: 10.1080/00224498809551476 Herek, G. M. (1989). Hate crimes against lesbians and gay men: Issues for research and policy. American Psychologist, 44(6), 948-955. Herek, G. M. (2000). The psychology of sexual prejudice. Current Directions in Psychological Science, 9, 19-22. doi: 10.1111/1467-8721.00051 Herek, G. M. (2002). Gender gaps in public opinion about lesbians and gay men. Public Opinion Quarterly, 66, 40-66. doi: 10.1086/338409 Herek, G. M. (2004). Beyond “homophobia”: Thinking about sexual prejudice and stigma in the twenty-first century. Sexuality Research and Social Policy, 1(2), 6-24. doi: 10.1525/srsp.2004.1.2.6 Herek, G. M., & Capitanio, J. P. (1996). "Some of my best friends": Intergroup contact, concealable stigma, and heterosexuals' attitudes toward gay men and lesbians. Personality and Social Psychology Bulletin, 22(4), 412-424. Herek, G. M., Gillis, R. J.., & Cogan, J. C. (1999). Psychological sequelae of hate-crime victimization among lesbian, gay, and bisexual adults. Journal of Consulting and Clinical Psychology, 67, 945-951. doi: 10.1037/0022-006X.67.6.945 Herek, G., Cogan, J., & Gillis, R. (2002). Victim experiences in hate crimes based on sexual orientation. Journal of Social Issues, 58, 319-339. doi: 10.1111/1540-4560.00263 Herrick, R. (2010). Legislators’ positions on gay and lesbian rights: The person and political. Journal of Homosexuality, 57, 928-943. doi: 10.1080/00918369.2010.493449 Hermann, P., & Bui, L. (2018, January 5). Three friends were killed on a single day in the D.C. area: Police think the cases may be linked. The Washington Post. Retrieved from www.washingtonpost.com

143

Hertl, J., & Sinclair, H. C. (2008, June). Application of prototype theory to perceptions of gender-motivated bias crimes. Poster presented at the annual meeting of the Society for the Psychological Study of Social Issues, Chicago, IL. Holmes, R. M., & Holmes, S. T. (2001). Murder in America. Thousand Oaks, CA: Sage Publications. Horn, S. S. (2006). Heterosexual adolescents’ and young adults’ beliefs and attitudes about homosexuality and gay and lesbian peers. Cognitive Development, 2(14), 420-440. doi: 10.1016/j.cogdev.2006.06.007 Ibish, H., & Stewart, A. (2003). Report on hate crimes against Arab Americans: The post- September 11 backlash. Washington, DC: American-Arab Anti-Discrimination Committee. Iganski, P. (2001). Hate crimes hurt more. American Behavioral Scientist, 45(4), 626-638. doi: 10.1177/00027640121957394 Ismael, T. Y., & Measor, J. (2003). Racism and the North American media following September 11: The Canadian setting. Arab Studies Quarterly, 25(1), 101-136. Ituarte, S. (2009). Legitimized anti-Latino sentiment: Breeding the prejudice that perpetuates violence. In B. Perry (Ed.), Hate crime: The victims of hate crime (pp. 45-64). Westport, CT: Praeger. Jacobs, D., Qian, Z., Carmichael, J., & Kent, S. (2007). Who survives on death row? An individual and contextual analysis. American Sociological Review, 72, 610-632. doi: 10.1177/000312240707200406 Janis, I. L. (1971). Groupthink. Psychology Today, 5(6), 84-90. Jenness, V., & Grattet, R. (2001). Making hate a crime: From social movement to law enforcement. New York: Russell Sage Foundation. Jennings, M. E. (2015). Involuntary sterilization of the mentally challenged. Journal of Ethics in Mental Health. Retrieved from: https://www.jemh.ca/issues/v9/JEMHVol92014- 2016.html Kang, J. (1993). Racial violence against Asian Americans. Harvard Law Review, 106, 1926- 1943. Kaplan, J. (2006). Islamophobia in America: September 11 and Islamophobic hate crime. Terrorism and Political Violence, 18(1), 1-33. doi: 10.1080/09546550500383209 Katel, P. (2009). Hate groups. CQ Researcher, 19, 421-448. Retrieved from http://library.cqpress.com Keppel, R. D., & Bimes, W. J. (2009). Serial violence: Analysis of modus operandi and signature characteristics of killers. Boca Raton: Taylor & Francis. Kilgour, D., Millar, S., & O’Neill, J. (2002). Strength under siege: Canadian civil society post- September 11th. In K. Kassam, G. Melnyk, & L. Parras (Eds.), Canada and September 11th: Impact and responses (pp. 151-161). Calgary, Canada: Detselig Enterprises. Kilianski, S. E. (2003). Explaining heterosexual men’s attitudes toward women and gay men: The theory of exclusively masculine identity. Psychology of Men and Masculinity, 4, 37- 56. doi: 10.1037/1524-9220.4.1.37 Kite, M. E., & Whitley, B. E. (1998). Do heterosexual women and men differ in their attitudes toward homosexuality? A conceptual and methodological analysis. In G. M. Herek (Ed.), Stigma and sexual orientation: Understanding prejudice against lesbians, gay men, and bisexuals (pp. 39-61). Thousand Oaks, CA: Sage. Kittrie, O. F. (2006). Federalism, deportation, and crime victims afraid to call the police. Iowa

144

Law Review, 91, 1449-1508. Kosciw, J., Greytak, E., Bartkiewicz, M., Boesen, M., & Palmer, N. (2012). The 2011 national school climate survey. New York: The Gay, Lesbian & Straight Education Network (GLSEN). Retrieved from http://www.glsen.org Kosic, A., Mannetti, L., & Livi, S. (2014). Forming impressions of in-group and out-group members under self-esteem threat: The moderating role of the need for cognitive closure and prejudice. International Journal of Intercultural Relations, 40, 1-10. doi: 10.1016/j.ijintrel.2014.01.004 Koss, M., Goodman, L., Browne, A., Fitzgerald, L., Keita, G., & Russo, N. (1994). Male violence against women at home, at work, and in the community. Washington, DC: American Psychological Association. Laajasalo, T., & Hakkanen, H. (2006). Excessive violence and psychotic symptomology among homicide offenders with schizophrenia. Criminal Behaviour and Mental Health, 16, 242- 253. doi: 10.1002/cbm.635 Lane, F. J., Shaw, L. R., & Kim, M. (2009). Hate crimes committed against persons with disabilities. In. B. Perry (Ed.), Hate crimes: The victims of hate crime (Vol. 3, pp. 173- 197). Westport, CT: Praeger. Langton, L., & Planty, M. (2011). Hate Crime, 2003-2009. Washington, DC: U.S. Department of Justice, Bureau of Justice Statistics. Last, S. K., & Fritzon, K. (2005). Investigating the nature of expressiveness in stranger, acquaintance, and intrafamilial homicides. Journal of Investigative Psychology and Offender Profiling, 2, 179-193. Lawrence, F. M. (1999). Punishing hate: Bias crimes under American law. Cambridge, MA: Harvard University Press. Lepore, L., & Brown, R. (1997). Category and stereotype activation: Is prejudice inevitable? Journal of Personality and Social Psychology, 72(2), 275–287. Levin, B. (1999). Hate crime: Worse by definition. Journal of Contemporary Criminal Justice, 15, 6-21. doi: 10.1177/1043986299015001002 Levin, B. (2009). The long arc of justice: Race, violence, and the emergence of hate crime law. In B. Perry & B. Levin (Eds.), Hate crimes: Understanding and defining hate crime (Vol. 1, pp. 1-22). Westport, CT: Praeger. Levin, B., & Fein, B. (1998, November 1). Does America need a federal hate crime law? Insight on the News, 24-25. Levin, J. (2002). The violence of hate: Confronting racism, anti-Semitism, and other forms of bigotry. Boston: Allyn & Bacon. Levin, L., & McDevitt, J. (1993). Hate crimes: The rising tide of bigotry & bloodshed. New York: Plenum. Lindqvist, P. (1986). Criminal homicide in northern Sweden 1970–1981: Alcohol intoxication, alcohol abuse and mental disease. International Journal of Law and Psychiatry, 8(1), 19- 37. doi: 10.1016/0160-2527(86)90081-6 Lombardi, E. L., Wilchins, R. A., Priesing, D., & Malouf, D. (2002). Gender violence: Transgender experiences with violence and discrimination. Journal of Homosexuality, 42(1), 89-101. doi: 10.1300/J082v42n01_05 Long, W. & Millsap, C. A. (2008). Fear of AIDS and Homophobia Scales in an ethnic population of university students. The Journal of Social Psychology, 148(5), 637-640. doi: 10.3200/SOCP.148.5.637-640

145

López, M. P. (2012). Examining the murder of Luis Ramirez and the emergence of hate crimes against Latino immigrants in the United States. Arizona State Law Journal, 44, 155-173. Luckenbill, D. F. (1977). Criminal homicide as a situated transaction. Social Problems, 25(2), 176-186. doi: 10.1037/0022-3514.72.2.275 Lyons, C. J., & Roberts, A. (2014). The difference “hate” makes in clearing crime: An event history analysis of incident factors. Journal of Contemporary Criminal Justice, 30(3), 268-289. doi: 10.1177/1043986214536663 MacFarquhar, N. (1999, February 17). Eight are charged in tormenting of learning-disabled man. The New York Times. Retrieved from http://www.nytimes.com MacKinnon, C. A. (1991). Pornography as defamation and discrimination. Boston University Law Review, 71, 793-808. Mahan, V. J. (2002). 1943 – One page from Mexican American history: A psychological analysis of oppression and resistance. Journal of Hispanic Higher Education, 1(4), 283-297. doi: 10.1177/153819202236973 Maier, H. W. (1912). Katathyme wahlbildung und paranoia [On the subject of catathymic delusions and paranoia]. Zeitschrift fur die Gesamte Neurologie und Psychiatrie, 13, 555-610. Malmquist, C. P. (1981). Psychiatric aspects of familicide. Bulletin of the American Academy of Psychiatry and Law, 8, 298-304. Mass, R. L., Prakash, R., Hollender, M. H., & Regan, W. M. (1984). Double parricide— matricide and patricide: A comparison with other schizophrenic murders. Psychiatric Quarterly, 56(4), 286-290. doi: 10.1007/BF01064474 Masser, B., Viki, G. T., & Power, C. (2006). Hostile sexism and rape proclivity amongst men. Sex Roles, 54(7-8), 565-574. doi: 10.1007/s11199-006-9022-2 Mathias, C. (2017, September 17). Exclusive: New report offers proof of US hate crime rise in the Trump era. Huffington Post. Retrieved from: https://www.huffingtonpost.com/entry/hate-crime-rise-2016-united-states- trump_us_59becac8e4b086432b07fed8 Maxwell, C., & Maxwell, S. R. (1995). Youth participation in hate-motivated crimes: Research and policy implications. Boulder, CO: Center for the Study and Prevention of Violence, Institute for Behavioral Sciences. McDevitt, J., Balboni, J., Garcia, L., & Gu, J. (2001). Consequences for victims: A comparison of bias- and non-bias-motivated assaults. American Behavioral Scientist, 45(4), 697-713. doi: 10.1177/00027640121957321 McDevitt, J., Levin, J., & Bennett, S. (2002). Hate crime offenders: An expanded typology. Journal of Social Issues, 58, 303-317. doi: 10.1111/1540-4560.00262 McMahon, B. T., West, S. L., Lewis, A. N., Armstrong, A. J., & Conway, J. P. (2004). Hate crimes and disability in America. Rehabilitation Counseling Bulletin, 47(2), 66-75. doi: 10.1177/00343552030470020101 McNeil, J. M., & Binette, J. (2001). Prevalence of disabilities and associated health conditions among adults. Journal of the American Medical Association, 285(12), 1571-1572. Meloy, J. R. (1992). Violent attachments. Northvale, NJ: Aronson. Meloy, J. R. (2000). The nature and dynamics of sexual homicide: An integrative review. Aggression and Violent Behavior, 5, 1–22. doi: 10.1016/S1359-1789(99)00006-3 Meloy, J. R. (2004). Indirect personality assessment of the violent true believer. Journal of Personality Assessment, 82, 138-146. doi: 10.1207/s15327752jpa8202_2

146

Merton, R. (1957). Social theory and social structure. New York: Free Press. Messner, D., McHugh, S., & Felson, B. (2004). Distinctive characteristics of assaults motivated by bias. Criminology, 42, 585-618. doi: 10.1111/j.1745-9125.2004.tb00530.x Meyer, D. (2010). Evaluating the severity of hate-motivated violence: Intersectional differences among LGBT hate crime victims. Sociology, 44(5), 980-995. doi: 10.1177%2F0038038510375737 Milgram, S. (1963). Behavioral study of obedience. Journal of Abnormal and Social Psychology, 67, 371-378. Mischel, W. (1968). Personality and assessment. New York: Wiley. Mitchell, S. A., & Black, M. J. (1995). Freud and beyond: A history of modern psychoanalytic thought. New York: Basic Books. Morsch, J. (1992). The problem of motive in hate crime: The argument against presumptions of racial motivation. The Journal of Criminal Law and Criminology, 82(1), 659-689. doi: 10.2307/1143748 Nadal, K. L., Davidoff, K. C., Davis, L. S., & Wong, Y. (2014). Emotional, behavioral, and cognitive reactions to microaggressions: Transgender perspectives. Psychology of Sexual Orientation and Gender Diversity, 1(1), 72-81. doi: 10.1037/sgd0000011 Nadal, K. L., Davidoff, K. C., Davis, L. S., Wong, Y., Marshall, D., & McKenzie, V. (2015). Intersectional identities and microaggressions: Influences of race, ethnicity, gender, sexuality, and religion. Qualitative Psychology, 2(2), 147–163. doi: 10.1037/qup0000026 Nadal, K. L., Issa, M., Leon, J., Meterko, V., Wideman, M., & Wong, Y. (2011). Sexual orientation microaggressions: "Death by a thousand cuts" for lesbian, gay, and bisexual youth. Journal of LGBT Youth, 8(3), 1-26. doi: 10.1080/15538605.2011.554606 Nadal, K. L., Mazzula, S. L., Rivera, D. P., & Fujii-Doe, W. (2014). Microaggressions and Latina/o Americans: An analysis of nativity, gender, and ethnicity. Journal of Latina/o Psychology, 2(2), 67-78. Nadal, K. L., Wong, Y., Issa, M. A., Meterko, V., Leon, J., & Wideman, M. (2011). Sexual orientation microaggressions: Processes and coping mechanisms for lesbian, gay, and bisexual individuals. Journal of LGBT Issues in Counseling, 5(1), 21-46. doi: 10.1080/15538605.2011.554606 National Asian and Pacific American Legal Consortium (1996). Audit of violence against Asian and Pacific Americans: The consequences of intolerance in America. Washington, DC: Author. National Coalition for the Homeless (2007). Hate, violence and death on Main Street: A report on hate crimes and violence against people experiencing homelessness, 2006. Washington, DC: Author. National Coalition of Anti-Violence Programs (2013). Lesbian, gay, bisexual, transgender, queer and HIV-affect hate violence in 2012. Washington, DC: Author. Retrieved from: https://avp.org National LGBTQ Task Force (2013). Hate crimes laws map. Washington, DC: Author. Retrieved from: http://www.thetaskforce.org/hate-crimes-laws-map/ National Organization on Disability (2000). The Harris Survey of Americans with Disabilities. Retrieved from: www.nod.org New York Police Department (2016). Supplementary Homicide Report. New York: Author. Retrieved from: www1.nyc.gov

147

New York Police Department (2017). Supplementary Homicide Report. New York: Author. Retrieved from: www1.nyc.gov Nielsen, M. (1996). Contextualization for Native American crime and justice. In M. Nielsen & R. Silverman (Eds.), Native Americans, crime and justice (pp. 10-19). Boulder, CO: Westview. Nielsen, M. (2000). Stolen lands, stolen lives: Native Americans and criminal justice. In Criminal Justice Collective (Ed.), Investigating difference: Human and cultural relations in criminal justice (pp. 45-58). Needham Heights, MA: Allyn & Bacon. Nielssen, O., & Large, M. (2010). Rates of homicide during the first episode of psychosis and after treatment: A systematic review and meta-analysis. Schizophrenia Bulletin, 36(4), 702-712. doi: 10.1093/schbul/sbn144 Novis, A. (2010). Snap shot report of targeted hostility towards disabled people in the U.K. London: United Kingdom Disabled People’s Council. Olson, L. R., Cadge, W., & Harrison, J. T. (2006). Religion and public opinion about same‐sex marriage. Social Science Quarterly, 87(2), 340-360. doi: 10.1111/j.1540- 6237.2006.00384.x Padgett, G. L. (1982). Racially-motivated violence and intimidation: Inadequate state enforcement and federal civil rights remedies. Journal of Criminal Law and Criminology, 75(1), 103-138. Paige, J. M. (1970). Changing patterns of anti‐White attitudes among Blacks. Journal of Social Issues, 26(4), 69-86. Parrott, D. J., & Peterson, J. L. (2008). What motivates hate crimes based on sexual orientation? Mediating effects of anger on antigay aggression. Aggressive Behavior, 34(3), 306-318. doi: 10.1002/ab.20239 Parrott, D. J., & Zeichner, A. (2005). Effects of sexual prejudice and anger on physical aggression toward gay and heterosexual men. Psychology of Men and Masculinity, 6, 3- 17. doi: 10.1037/1524-9220.6.1.3 Parrott, D. J., Adams, H. E., & Zeichner, A. (2002). Homophobia: Personality and attitudinal correlates. Personality and Individual Differences, 32, 1269-1278. doi: 10.1016/S0191- 8869(01)00117-9 Patel, S., Long, T. E., McCammon, S. L., & Wuensch, K. L. (1995). Personality and emotional correlated of self-reported antigay behaviors. Journal of Interpersonal Violence, 10, 354- 366. doi: 10.1177/088626095010003008 Perlmutter, P. (1992). Divided we fall: A history of ethnic, religious, and racial prejudice in America. Ames, IA: Iowa State University Press. Pendo, E. A. (1994). Recognizing violence against women: Gender and the Hate Crime Statistics Act. Harvard Women’s Law Journal, 17, 157-185. Perry, B. (2001). In the name of hate: Understanding hate crimes. New York: Routledge. Perry, B. (2002). Defending the color line: Racially and ethnically motivated hate crime. American Behavioral Scientist, 46(1), 72-92. doi: 10.1177/0002764202046001006 Perry, B. (2003). Hate and bias crime: A reader. New York: Psychology Press. Perry, B. (2009a). ‘There’s just places ya’ don’t wanna go’: The segregating impact of hate crime against Native Americans. Contemporary Justice Review, 12(4), 401-418. doi: 10.1080/10282580903342888 Perry, B. (2009b). Anti-Muslim violence in the post-9/11 era: Motive forces. In B. Perry & R. Blazak (Eds.), Hate crimes: Hate crime offenders (Vol. 4, pp. 171-188). Westport, CT:

148

Praeger. Perry, B. (2009c). Introduction. In B. Perry & B. Levin (Eds.), Hate crimes: Understanding and defining hate crime (Vol. 2, pp. xvii-xxi). Westport, CT: Praeger. Perry, B. (2009d). Racist violence against Native Americans. In B. Perry & P. Iganski (Eds.), Hate crimes: The consequences of hate crime (Vol. 2, pp. 1-17). Westport, CT: Praeger. Perry, B. (2009e). Set introduction. In B. Perry & B. Levin (Eds.), Hate crimes: Understanding and defining hate crime (Vol. 1, pp. xi-xv). Westport, CT: Praeger. Perry, B. (2009f). The sociology of hate: Theoretical approaches. In B. Perry & B. Levin (Eds.), Hate crimes: Understanding and defining hate crime (Vol. 1, pp. 55-75). Petersen, M. L., & Farrington, D. P. (2007). Cruelty to animals and violence to people. Victims and Offenders, 2(1), 21-43. doi: 10.1080/15564880600934187 Pew Research Center (2010). Public remains conflicted over Islam. Washington, DC: Author. Retrieved from http://www.pewforum.org Pew Research Center (2013). The global divide on homosexuality. Washington, DC: Author. Retrieved from http://www.pewglobal.org/2013/06/04/the-global-divide-on- homosexuality/ Pew Research Center (2017). Support for same-sex marriage grows, even among groups that had been skeptical. Washington, DC: Author. Retrieved from: www.pewresearch.org Phillips, N. D. (2009). The prosecution of hate crimes: The limitations of the hate crime typology. Journal of Interpersonal Violence, 24, 883-905. doi: 10.1177/08862608317190. Poteat, V. P., & Espelage, D. L. (2005). Exploring the relation between bullying and homophobic verbal content: The homophobic content agent target (HCAT) scale. Violence and Victims, 20(5), 513-528. Potok, M. (2001). The new internationalism. Intelligence Report. Montgomery, AL: Southern Poverty Law Center. Retrieved from https://www.splcenter.org Poynting, S. (2006). What caused the Cronulla Riot? Race and Class, 48(1), 85-92. doi: 10.1177/030639680604800116 Ray, L., Smith, D., & Wastell, L. (2004). Shame, rage and racist violence. British Journal of Criminology, 44, 350-368. doi: 10.1093/bjc/azh022 Reasons, C. E., & Hughson, Q. (2000). Violence against gays and lesbians. Journal of Offender Rehabilitation, 30(1-2), 137-159. doi: 10.1300/J076v30n01_09 Reaves, B. A. (2006). Special report: State court processing statistics, 1990-2002, Violent felons in large urban counties. Washington, DC: Bureau of Justice Statistics. Retrieved from http://www.bjs.gov/content/pub/ascii/vfluc.txt Ressler, R., Burgess, A., & Douglas, J. (1988). Sexual homicide: Patterns and motives. Lexington, MA: Lexington Books. Ressler, R. K., Burgess, A. W., Hartman, C. R., Douglas, J. E., & McCormack, A. (1986). Murderers who rape and mutilate. Journal of Interpersonal Violence, 1(3), 273-287. doi: 10.1177/088626086001003002 Revitch, E. (1977). Classification of offenders for prognostic and dispositional evaluation. Bulletin of the American Academy of Psychiatry and Law, 5, 41–50. Revitch, E., & Schlesinger, L. B. (1978). Murder: Evaluation, classification, and predicting. In I. L. Kutash, S. B. Kutash, & L. B. Schlesinger (Eds.), Violence: Perspectives on murder and aggression (pp. 138–164). San Francisco: Jossey-Bass. Revitch, E., & Schlesinger, L. B. (1981). Psychopathology of homicide. Springfield, IL: Charles C.

149

Thomas. Riedel, M., & Jarvis, J. (1998). The decline of arrest clearances for criminal homicide: Causes, correlates, and third parties. Criminal Justice Policy Review, 9, 279-306. doi: 10.1177/088740349900900302 Riger, S., & Gordon, M. T. (1981). The fear of rape: A study in social control. Journal of Social Issues, 37(4), 71-92. doi: 10.1111/j.1540-4560.1981.tb01071.x Robin, L., Brener, N. D., Donahue, S. F., Hack, T., Hale, K., & Goodenow, C. (2002). Association between health risk behaviors and opposite-, same-, and both-sex sexual partners in representative samples of Vermont and Massachusetts high school students. Archives of Pediatrics and Adolescent Medicine, 156(4), 349-355. doi: 10.1001/archpedi.156.4.349 Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. Advances in Experimental Social Psychology, 10, 173-220. Rothschild, E. (1993). Recognizing another face of hate crime: Rape as a gender-bias crime. Maryland Journal of Contemporary Legal Issues, 4(2), 231-285. Russell, S. T. (2002). Queer in America: Citizenship for sexual minority youth. Applied Developmental Science, 6(4), 258-263. doi: 10.1207/S1532480XADS0604_13 Russell, S. T., Franz, B. T., & Driscoll, A. K. (2001). Same-sex romantic attraction and experiences of violence in adolescence. American Journal of Public Health, 91(6), 903- 906. Ryan, R. M., & Ryan, W. S. (2012, April 27). Homophobic? Maybe you’re gay. The New York Times. Retrieved from http://www.nytimes.com Sager, H. A., & Schofield, J. W. (1980). Racial and behavioral cues in Black and White children's perceptions of ambiguously aggressive acts. Journal of Personality and Social Psychology, 39, 590-598. Salfati, C. G., James, A. R., & Ferguson, L (2008). Prostitute homicides. Journal of Interpersonal Violence, 23(4), 505-543. Salfati, C. G. (2003). Offender interaction with victims in homicide: A multidimensional analysis of frequencies in crime scene behaviors. Journal of Interpersonal Violence, 18, 490-512. Salfati, C. G. (2000). The nature of expressiveness and instrumentality in homicide: Implications for offender profiling. Homicide Studies, 4, 265-293. Salfati, C. G., & Canter, D. V. (1999). Differentiating stranger murders: Profiling offender characteristics from behavioral styles. Behavioral Sciences and the Law, 17, 391-406. Sanders, W. B. (1998). Gangbangs and drive-bys: Grounded culture and juvenile gang violence. New York: Aldine de Gruyter. Saucier, D. A., Brown, T. L., Mitchell, R. C., & Cawman, A. J. (2006). Effects of victims’ characteristics on attitudes toward hate crimes. Journal of Interpersonal Violence, 21, 890-909. doi: 10.1177/0886260506288936 Schanda, H., Knecht, G., Schreinzer, D., Stompe, T., Ortwein-Swoboda, G., & Waldhoer, T. (2004). Homicide and major mental disorders: A 25-year study. Acta Psychiatrica Scandinavica, 110(2), 98-107. doi: 10.1111/j.1600-0047.2004.00305.x Schlesinger, L. B. (2001). The potential sex murderer: Ominous signs, risk assessment. Journal of Threat Assessment, 1, 47–72. doi: 10.1300/J177v01n01_05 Schlesinger, L. B. (2004). Classification of antisocial behavior for prognostic purposes: Study the motivation, not the crime. Journal of Psychiatry and Law, 32, 191–219. Schlesinger, L. B. (2007). Sexual homicide: Differentiating catathymic and compulsive murders.

150

Aggression and Violent Behavior, 12, 242–256. doi: 10.1016/j.avb.2006.09.007 Schlesinger, L. B. (2008). Compulsive-repetitive offenders: Behavioral patterns, motivational dynamics. In R. N. Kocsis (Ed.), Serial murder and the psychology of violent crimes (pp. 15–33). Totowa, NJ: Humana Press. Schlesinger, L. B., Kassen. M., Mesa, V. B., & Pinizzotto, A. J. (2010). Ritual and signature in serial sexual homicide. Journal of the American Academy of Psychiatry and Law, 38, 239– 246. Shaw, J., Hunt, I. M., Flynn, S., Meehan, J., Robinson, J. O., Bickley, H., ... & Appleby, L. (2006). Rates of mental disorder in people convicted of homicide. The British Journal of Psychiatry, 188(2), 143-147. doi: 10.1192/bjp.188.2.143 Sheffield, C. (1995). Hate violence. In P. Rotherberg (Ed.), Race, class, and gender in the United States (pp. 432-441). New York: St. Martin’s Press. Sheridan, D. J., & Nash, K. R. (2007). Acute injury patterns of intimate partner violence victims. Trauma, Violence, and Abuse, 8, 281-289. Sibbitt, R. (1997). The perpetrators of racial harassment and racial violence. London: London Home Office. Sinclair, H. C., & Hertl, J. T. (2010). Gender-motivated bias crimes: Examining why situational variables are important in the labeling of hate crimes. In C. T. Lockhardt (Ed.), Psychology of hate (pp. 1-34). Hauppauge, NY: Nova Science. Sinn, J. S. (1997). The predictive and discriminant validity of masculinity ideology. Journal of Research in Personality, 31, 117-135. doi: 10.1006/jrpe.1997.2172 Sirin, S. R., & Fine, M. (2008). Muslim American youth: Understanding hyphenated identities through multiple methods. New York: NYU Press. Smart, J. F. (2001). Disability, society, and the individual. Austin, TX: Pro Ed. Sobsey, D. (1994). Sexual abuse of individuals with intellectual disability. In A. Craft (Ed.), Practice issues in sexuality and learning disabilities (pp. 93-115). New York: Routledge. Sobsey, D., & Doe, T. (1991). Patterns of sexual abuse and assault. Sexuality and Disability, 9(3), 243-259. doi: 10.1007/BF01102395 Southern Poverty Law Center (2015). Intelligence report. Washington, DC: Author. Retrieved from http://www.splcenter.org/ Southern Poverty Law Center (2014). Hate map. Washington, DC: Author. Retrieved from http://www.splcenter.org/get-informed/hate-map Stacey, M., Carbone-Lopez, K., & Rosenfeld, R. (2011). Demographic change and ethnically motivated crime: The impact of immigration on anti-Hispanic hate crime in the United States. Journal of Contemporary Criminal Justice, 27(3), 278-298. doi: 10.1177/1043986211412560 Stiffarm, L., & Lane, P. (1992). The demography of Native North America. In A. Jaimes (Ed.), The state of Native America: Genocide, colonization, and resistance (pp. 23-54). Boston: South End Press. Stotzer, R. L. (2008). Gender identity and hate crimes: Violence against transgender people in Los Angeles County. Sexuality Research & Social Policy, 5(1), 43-52. doi: 10.1525/srsp.2008.5.1.43 Strom, K. J. (2001). Hate crimes reported in NIBRS, 1997-99: Special report. Washington, DC: Bureau of Justice Statistics Special Report. Sun, K. (2006). The legal definition of hate crime and the hate offender's distorted cognitions. Issues in Mental Health Nursing, 27(6), 597-604. doi:10.1080/01612840600642877

151

Suttles, G. D. (1972). The social construction of communities. Chicago, IL: University of Chicago Press. Sykes, G. M., & Matza, D. (1957). Techniques of neutralization. American Sociological Review, 22, 664-670. doi: 10.2307/2089195 Takaki, R. (1994). Journey to Gold Mountain: The Chinese in 19th-century America. New York: Chelsea House. Taylor, P. J., Leese, M., Williams, D., Butwell, M., Daly, R., & Larkin, E. (1998). Mental disorder and violence: A special (high security) hospital study. British Journal of Psychiatry, 172, 477-484. doi: 10.1177/0964663906066616 Tomsen, S. (2002). Victims, perpetrators and fatal scenarios: A research note on anti- homosexual male homicides. International Review of Victimology, 9(3), 253-271. doi: 10.1177/026975800200900302 Tomsen, S. (2006). Homophobic violence, cultural essentialism and shifting sexual identities. Social & Legal Studies, 15(3), 389-407. doi: 10.1177/0964663906066616 Tomsen, S. (2009). Victimhood, ‘sexual deceit’ and the social origins of the criminalization of HIV transmission. In M. Segrave (Ed.), Australia & New Zealand Critical Criminology Conference Proceedings 2009 (pp. 286-305). Melbourne, AU: Monash University. Retrieved from www.researchgate.net Torres, S. (1999). Hate crimes against African Americans: The extent of the problem. Journal of Contemporary Criminal Justice, 15(1), 48-63. doi: 10.1177/1043986299015001004 Toth, J. (1991, February 7). Hate crimes increase since the start of the war. The LA Times. Retrieved from www.latimes.com Transgender Community Health Project (1999). HIV-InSite. San Francisco, CA: University of California. Retrieved from: http://hivinsite.ucsf.edu Trojan, C., & Krull, A. C. (2012). Variations in wounding by relationship intimacy in homicide cases. Journal of Interpersonal Violence, 27, 2869-2888. Tsai, S. S. H. (1986). The Chinese experience in America. Bloomington, IN: University of Indiana Press. Turpin-Petrosino, C. (2009a). Black victimization: Perceptions and realities. In B. Perry (Ed.), Hate crimes: The victims of hate crime (Vol. 3, pp. 19-44). Westport, CT: Praeger. Turpin-Petrosino, C. (2009b). Historical lessons: What’s past may be prologue. In B. Perry & B. Levin (Eds.), Hate crimes: Understanding and defining hate crime (Vol. 1, pp. 23-40). Westport, CT: Praeger. Umemoto, K., & Mikami, C. K. (2000). A profile of race-bias hate crime in Los Angeles County. Western Criminology Review, 2(2), 1-37. U.S. Census Bureau (2000). American fact finder. Washington, DC: Author. Retrieved from https://www.census.gov U.S. Census Bureau (2010). American fact finder. Washington, DC: Author. Retrieved from https://www.census.gov U.S. Census Bureau (2015). USA Quickfacts. Washington, DC: Author. Retrieved from http://quickfacts.census.gov U.S. Department of Justice (2015). The Matthew Shepard and James Byrd, Jr. Hate Crime Prevention Act of 2009. Washington, DC: Bureau of Justice. Retrieved from http://www.justice.gov United States Commission on Civil Rights (1990). Intimidation and violence: Racial and religious bigotry in America. Washington, DC: Government Printing Office.

152

United States Commission on Civil Rights (1992). Racial and ethnic tensions in American communities: Poverty, inequality, and discrimination. Washington, DC: Government Printing Office. United States Department of Justice (2005). Criminal victimization in the United States, 2005 statistical tables. Washington, DC: Office of Justice Programs. Retrieved from http://www.bjs.gov United States Department of Justice, Federal Bureau of Investigation (2002). Hate Crime Statistics. Washington, DC: Author. Retrieved from https://www.fbi.gov United States Department of Justice, Federal Bureau of Investigation (2007). Uniform crime reports: Hate crime reporting statistics, 2006. Washington, DC: Government Printing Office. Retrieved from http://www.fbi.gov United States Department of Justice, Federal Bureau of Investigation (2010). Hate Crime Statistics. Washington, DC: Author. Retrieved from https://www.fbi.gov United States Department of Justice, Federal Bureau of Investigation (2012). Uniform crime reports: Hate crime reporting statistics, 2012. Washington, DC: Government Printing Office. Retrieved from https://www.fbi.gov United States Department of Justice, Federal Bureau of Investigation (2013). Hate Crime Statistics. Washington, DC: Author. Retrieved from https://www.fbi.gov United States Department of Justice, Federal Bureau of Investigation (2014). Crime in the United States, 2013. Washington, DC: Author. Retrieved from https://www.ucr.fbi.gov United States Department of Justice, Federal Bureau of Investigation (2017). Hate Crime Statistics. Washington, DC: Author. Retrieved from https://www.fbi.gov VanderStoep, S. W., & Green, C. W. (1988). Religiosity and homonegativism: A path-analytic study. Basic and Applied Social Psychology, 9(2), 135-147. Van Dyke, N., & Tester, G. (2014). Dangerous climates: Factors associated with variation in racist hate crimes on college campuses. Journal of Contemporary Criminal Justice, 30(1), 290-309. doi: 10.1177/1043986214536666 Wachholz, S. (2005). Hate crimes against the homeless: Warning-out New England style. Journal of Sociology & Social Welfare, 32, 141-163. Webster, C.D., Douglas, K.S., Eaves, D., & Hart, S.D. (1997). HCR-20: assessing risk for violence, Version 2 manual. Vancouver, BC: Mental Health, Law and Policy Institute, Simon Fraser University. Weinstein, N., Ryan, W. S., Dehaan, C. R., Przbylski, A. K., Legate, N., & Ryan, R. M. (2012). Parental autonomy support and discrepancies between implicit and explicit sexual identities: Dynamics of self-acceptance and defense. Journal of Personality and Social Psychology, 102(4), 815-832. doi: 10.1037/a0026854 Weitzer, R., & Tuch, S. A. (2004). Race and perceptions of police misconduct. Social Problems, 51(3), 305-325. Wertham, F. (1937). The catathymic crisis: A clinical entity. Archives of Neurology and Psychiatry, 37, 974-977. Wertham, F. (1978). The catathymic crisis. In I. L. Kutash, S. B. Kutash, & L. B. Schlesinger (Eds.), Violence: Perspectives on murder and aggression (pp. 165-170). San Francisco: Jossey-Bass. Whitley, B. E., & Kite, M. E. (1995). Sex differences in attitudes toward homosexuality: A comment on Oliver and Hyde (1993). Psychological Bulletin, 117(1), 146-154. Wilchins, R. A., & Taylor, T. (2006). 50 under 30: Masculinity and the war on America's youth

153

— A human rights report. Washington, DC: GenderPAC. Retrieved from http://www.gpac.org/50under30 Wilcox, C., & Norrander, B. (2002). Of moods and morals: The dynamics of opinion on abortion and gay rights. Understanding Public Opinion, 2, 121-148. Wilcox, C., & Wolpert, R. (2000). Gay rights in the public sphere: Public opinion on gay and lesbian equality. In C. A. Rimmerman et al. (Eds.), The politics of gay rights (pp. 409- 432). Chicago, IL: University of Chicago Press. Williams, E. W. (2015, April 24). Eric Holder: The exit interview. The Advocate. Retrieved from www.advocate.com Williams, T., Connolly, J., Pepler, D., & Craig, W. (2003). Questioning and sexual minority adolescents: High school experiences of bullying, sexual harassment and physical abuse. Canadian Journal of Community Mental Health, 22(2), 47-58. doi: 10.7870/cjcmh-2003- 0013 Williams, T., Connolly, J., Pepler, D., & Craig, W. (2005). Peer victimization, social support, and psychosocial adjustment of sexual minority adolescents. Journal of Youth and Adolescence, 34(5), 471-482. doi: 10.1007/s10964-005-7264-x Wilson, C., & Brewer, N. (1992). The incidence of criminal victimisation of individuals with an intellectual disability. Australian Psychologist, 27(2), 114-117. Wilson, M. M. (2014). Hate crime victimization, 2004–2012—Statistical tables. Washington, DC: Bureau of Justice Statistics, Office of Justice Programs. Retrieved from www.bjs.gov Wilson, M., & Ruback, R. (2003). Hate crime in Pennsylvania, 1984-99: Case characteristics and police responses. Justice Quarterly, 20, 373-396. doi: 10.1080/07418820300095561 Wisconsin v. Mitchell, 508 U.S. 476 (1993). Wolfe, L. & Copeland, L. (1994) Violence against women as bias-motivated hate crime: Defining the issues in the USA. London: Zed Books. Wolfgang, M. E. (1957). Victim precipitated criminal homicide. The Journal of Criminal Law, Criminology, and Police Science, 48(1), 1-11. Wright, C. (2015, June 17). Police search for assailant in 4 attacks on Asian women. The New York Times. Retrieved from http://www.nytimes.com Wyss, S. E. (2004). “This was my hell”: The violence experienced by gender non-conforming youth in U.S. high schools. International Journal of Qualitative Studies in Education, 17(5), 709-730. doi: 10.1080/0951839042000253676 Xavier, J. (2000). The Washington, D. C. Transgender Needs Assessment Survey final report for phase two. Washington, DC: Administration for HIV/AIDS of the District of Columbia. Retrieved from http://www.gender.org/resources/dge/ gea01011.pdf Young, I. (1990). Justice and the politics of difference. Princeton, NJ: Princeton University Press. Zimbardo, P. G. (2007). The Lucifer Effect: Understanding how good people turn evil. New York: Random House.

154