Introduction rising racial tensions in Jena

In 2006, rising racial tensions in Jena, Louisiana lead to a big media story now

known as “The Jena Six Story” (Democracy Now, 2007). It began when a student asked

for permission to sit under a tree commonly known as the ‘white tree’ (a tree where

Caucasian students gathered). The following day, students observed three nooses

hanging from the tree. The responsible Caucasian students were suspended for three days

after school administrators determined that the act was just a prank. Subsequent to the

incident, six African-American students attacked one Caucasian student. The Caucasian

victim was sent to hospital for medical clearance, released the same day, and seen at a

school function that evening. The six African-American students responsible for the

attack were arrested and charged with attempted second-degree murder and conspiracy to

commit murder. The charges would leave the students (ranging from 15 to 17 years of

age) facing between twenty and one hundred years in jail. The Jena Six story has

captured national media attention and caused tremendous racial tension (Democracy

Now, 2007). Is this incident an example of racial unfairness in the current judicial

system? Should the incident where Caucasian students hung nooses be classified as a

hate crime? Or should the attack be prosecuted as a hate crime? Or should both incidents

be considered as hate crimes? All these questions remain unanswered as the legal process

continues.

Racially motivated crimes (such as the Jena Six Story) have occurred in great

magnitude in American history (Petrosino, 1999; Perlmutter, 1991; Levin & McDevitt

1993). It is well documented that prejudice and hate have been an issue in the United

States for centuries (Franklin & Moss, 1994; Fredrickson, 2002; Apel, 2004; Harris,

1984) and remains pervasive in today’s society (Feagin & Sikes, 1994; Bonilla-Silva,

2001). Discriminatory and violent victimization against African-Americans dates back to

slavery (Franklin & Moss, 1994; Berlin, 2003; Hacker, 1996). African-Americans were

viewed as inferior, uncivilized, and heathens, views that provided rationalizations for

using them as slaves (Petrosino, 1999). In the slavery era, African-Americans were

dehumanized as they were stripped of their rights, mandated to perform labor, and forced

to live in treacherous conditions (Franklin & Moss, 1994). Criminal acts, such as assault,

torture, kidnapping, rape, and psychological abuse occurred during this period (Petrosino,

1999).

The post-emancipation period was characterized as the “Jim Crow Era,” a time in

history when numerous lynchings occurred (Soule 1992; Tolnay & Beck, 1992; Beck &

Tolnay, 1990). During this era, the “Jim Crow Laws” mandated racial segregation by

prohibiting African-Americans from using the same facilities as Caucasians, such as

schools, transportation, and housing. Additionally, African-Americans were prohibited

from voting and seeking economic opportunities (for example, business ownership). The

laws also allowed private acts of mass racial violence, such as lynchings (Franklin &

Moss, 1994). Lynching was described as murdering an accused person without due

process of the law (Waldrep, 2000; Petrosino, 1999). Lynchings caused discouragement

from overcoming poverty, owning real property, employment, pursuing education, and

voting (Washington, 1899; Aldrich, 1979; Torres, 1999). African-Americans were

essentially treated as second-class citizens (Franklin & Moss, 1994). Subsequent to the

“Jim Crow Era” was the civil rights movement where African-Americans fought against

racial discrimination and demanded freedom, respect, dignity, and economic and social

equality (Lewis, 2000; Williams, 1987; McWhorter 2000). Although African-Americans

gained civil rights in American society, they continued to experience discrimination

(Feagin & Sikes, 1994; Bonilla-Silva, 2001).

Historically, murder, assault, rape, and theft were categorized as criminal acts;

however the racial motivation behind those criminal acts was not (Petrosino, 1999).

Thus, while crimes motivated by racial hatred occurred in the past, the criminalization of

hate has only recently occurred (Petrosino, 1999). In the 1980s, laws were enacted and

definitions established to address hate crimes in the United States (Petrosino, 1999;

Lawrence, 1999). Hate crimes were defined as bias motivated criminal acts against a

person or property (Petrosino, 1999; Torres, 1999; Saucier et al., 2006; Jacobs & Potter,

1997; Craig 1999; Nolan et al. 2002; Marcus-Newhall et al., 2002).

The enactment of hate crime laws set the stage for cultural and structural changes

as there was an observable shift from the slavery and post-emancipation era to the

postcivil rights movement era, a shift depicted by criminalizing racially motivated

criminal acts (Nolan et al., 2002). The passage of hate crime laws demonstrated

recognition that hate crimes were uniquely different from ordinary crimes as they caused

irreparable damage to victims and communities, therefore warranting distinction.

Although the shift in history has been marked by laws that mandate criminalizing hate

crimes, surprisingly, very little attention in the social sciences has been directed in

examining hate crimes and jury decision making. Previous researchers have focused on

race as an extralegal factor (i.e., as an aspect unrelated to the evidence presented in a legal

case) associated with influencing jury decision making. However, a literature review

revealed only four research studies explicitly focusing on jurors’ perceptions of hate

crimes.

The present exploratory study seeks to fill the gaps in the existing literature by

examining jurors’ perceptions of hate crimes to evaluate whether extralegal factors are

taken into account in juror decision making. The aim is to establish whether the

independent effects of race or type of crime (hate crime vs. non-hate) influences mock

juror’s decision making in guilt adjudication and sentencing recommendations. The study

will answer three specific questions. Are there racial differences in adjudication and

sentencing in hate crime and non-hate crime conditions? Does race impact the perception

of crime severity according to the type of crime (hate crime or non-hate crime)? Is the

perception of a hate crime dependent on the victim’s race?

The next chapter will examine the definitions, laws, prevalence, and social factors

that influence hate crimes. Following this in-depth discussion, the third chapter will

elaborate on extralegal factors and outline previous research conducted in race and jury

decision making. Additionally, the chapter will review the scant research specific to hate

crimes and jury decision making. The fourth chapter will review the methods, the fifth

chapter will outline the results, and finally the sixth chapter will summarize the

discussion and conclusion.

Chapter 2

Overview of Hate Crimes

Creation of Legislation for Hate Crimes

Some have suggested that the motivation to enact hate crime laws was encouraged

by triggering events and movements in the 1970s and 1980s, including the women’s

rights, gay rights, and civil rights movements (Gerstenfeld, 2003; Cogen 2002; Nolan et

al., 2002). The Hate Crime Statistics Act (HCSA; 1990) was the first Federal hate crime

law enacted to explicitly deal with racially motivated crimes (Torres, 1999; Saucier et al.,

2006; Craig, 1999; Craig & Waldo, 1996). The HCSA required the attorney general to

institute procedures and collect data regarding crimes such as murder, non-negligent

manslaughter, intimidation, simple assault, aggravated assault, forcible rape, arson, and

property crimes (destruction, damage, or vandalism of property) that showed clear

evidence of motivation based on race, ethnicity, sexual orientation or religion (Nolan et

al., 2002). After the HCSA was established, the FBI created a program called the

National Crime Data Collection program to collect data on hate crimes. This program

was an adjunct to the existing Uniform Crime Reporting Program (Nolan et al., 2002).

Data are collected on the patterns, frequency, location, and extent of hate crimes in order

to assist law enforcement, the legislature and communities to increase awareness on hate

crimes (Jacobs & Potter, 1997).

The Hate Crime Statistics Act was followed by the Hate Crime Sentencing

Enhancement Act (HCSEA) in 1994, which modified the US Sentencing Guidelines.

This new law indicated that individuals who committed a hate crime would receive a

harsher sentence of three offense levels higher than ordinary crimes, such as robbery or

assault (Torres, 1999; Saucier et al., 2006; Craig, 1999). That is, the sentence is

automatically increased by a factor of three times. For example, a felony of the fourth

degree is sentenced as a felony of the first degree. The HCSEA specifically states that,

If the finder of fact at trial or, in the case of a guilty plea,….the court at sentencing

determines beyond a reasonable doubt that the defendant intentionally selected any

victim or any property as object of the offense because of the actual or perceived

race, color, religion, national origin, ethnicity, gender, disability, or sexual

orientation for any person, an additional 3-level enhancement from [the base level

offense] will apply (Wisconsin v. Mitchell, 1993).

One such example of sentencing enhancement occurred in Wisconsin v. Mitchell

(1993) where it was established that if the crime was motivated by prejudice because of

the person’s race, ancestry, national origin, disability, sexual orientation, religion or color

and committed against a person or property, the sentence was tripled. Florida has

instituted the sentencing enhancement law whereby punishments are enhanced for any

felony or misdemeanor crime that is bias-motivated. After the establishment of hate

crime laws, several court hearings occurred that impacted how hate crimes were

prosecuted in a courtroom. The following section explores several court decisions that

lead to judicial procedures for hate crimes.

Hate Crime Procedures

Over the last several years, some court decisions have impacted judicial

procedures for hate crimes. In Jones v. United States (1999) the defendant was sentenced

to 25 years in prison for carjacking when the normal sentence was 10 years for that crime.

The outcome of this court hearing led to the conclusion that the sixth amendment to a

defendant’s right to a jury trial was violated because the judge increased the sentence.

Consequently, sentence enhancements were only permitted after a jury had found beyond

a reasonable doubt that the evidence presented in the case warranted increased sentencing

(526 U.S. 227, 119 S.Ct. 1215,1999). This decision also resulted from the Almendarez-

Torres v. United States (1998) case that had allowed increased sentencing based on prior

convictions (523 U.S. 224, 118 S. Ct. 1219, 1998). In Apprendi

v. New Jersey (2000), a court ruling was overturned after a judge increased sentencing on

a defendant convicted of several weapon offenses against an African-American family

because the judge found that this crime was motivated by race. When this sentence was

reversed, Justice Stevens indicated that other than prior convictions, all facts must be

presented to a jury first and proved beyond a reasonable doubt before sentence

enhancements can occur (530 U.S. 466, 120 S. Ct. 2348, 2000).

Some resistance by the courts was demonstrated during the Harris v. United States

(2002) case that argued that a jury does not need to try a case presenting facts that

mandate minimum sentencing. While cases presented to the jury have an element of an

aggravated crime that would allow an extension of the maximum sentencing guidelines,

this was not the circumstance for cases that require minimum sentencing. Judges could

increase the sentence beyond the mandatory minimum sentencing guidelines with or

without the jury’s verdict. However, Justice Stevens argued that greater punishment than

is necessary would result if mandatory minimum sentences were increased (536 U.S. 545,

122 S.Ct. 2406, 2002).

In Blakey v. Washington (2004), the sentencing schemes involved crimes that were

categorized and assigned penalties. For instance, Class B felonies were assigned

maximum sentences of 10 years. However, specific crimes had smaller ‘standard ranges’;

for instance kidnapping was classified as a Class B felony, however, it only carried a

sentence range of 49 to 53 months. In this case, the sentence was enhanced because the

judge found that the defendant acted by ‘deliberate cruelty’; as such he received a 90

month sentence after being convicted of kidnapping. Justice Scalia found this case

unconstitutional because it exceeded the allowed statutory maximum of 53 months based

on the facts presented in the jury’s verdict (542 U.S. 296, 124 S.Ct. 2531, 2004). A

similar issue was noted in United States v. Booker (2005), where the sentence was

increased beyond the allowed mandatory maximums according to the Federal

Sentencing Guidelines based on judicial facts that were not presented to the jury. Justice

Breyer concluded that Guideline ranges should be advisory to allow the courts to impose

sentences at the statutory maximums. This meant that juries could authorize sentences up

to the statutory maximum amounts (543 U.S. 220, 125 S.CT. 738, 2005). In conclusion,

the results of these court decisions mandated that sentencing enhancements be proven to a

jury in all jurisdictions. Additionally, sentencing guidelines could be increased to the

statutory maximums to allow judges to decrease sentences as necessary and ensure that

all jurisdictions remained within their maximum sentencing enhancement guidelines.

Therefore, the history of these decisions allowed the Supreme Court to delineate clear

procedural guidelines to address the judicial system for hate crimes.

In the state of Florida, jurors are given specific instructions for aggravation of a

crime by selecting a victim based on prejudice according to Florida Statute § 775.085.

Instructions inform jurors to find the defendant guilty of the hate crime if they find the

defendant accountable for the crime and believe that beyond a reasonable doubt the

defendant selected the victim based on prejudice. If jurors believe that the defendant

committed the crime, but they not believe beyond a reasonable doubt that the intention of

the crime was motivated by race, they are asked to find the defendant guilty of the crime

only (775.085, Florida Statutes, Supp. 1998).

After the jury finds that the defendants’ crime was motivated by an aggravating

factor, the judge proceeds with sentencing according to the appropriate sentencing

guidelines. In Florida, according to Florida Statute Florida Statute § 775.085 (2007),

judges follow the specific sentencing guidelines. Crimes are reclassified as Florida law

allows for sentencing enhancement for racially motivated criminal acts. For instance, a

misdemeanor of the second degree is reclassified to a misdemeanor of the first degree, a

misdemeanor of the first degree is reclassified to a felony of the third degree, and a felony

of the third degree is reclassified to a felony of the second degree (775.085,

Florida Statutes, Supp. 1998), and so on.

Overall, the state of Florida provides clear guidelines in accordance with federal

guidelines for jurors hearing hate crimes and judges imposing sentences. Since I have

discussed laws and procedural definitions for hate crimes, an exploration of hate crime

definitions shall follow. Some researchers have identified multiple existing variations of

hate crime definitions. The following section will describe the U.S. Supreme Court’s

definition of a hate crime and the other definitions offered.

Hate Crime Definitions

While researchers have devised a number of similar definitions of a hate crime,

the U.S. Supreme Court has clarified the definition of hate crimes by providing explicit

language in the form of legislation. Specifically, the definition offered in the Hate Crime

Statistics Act is “a criminal offense committed against a person or property, which is

motivated, in whole or in part, by the offender’s bias against race, religion,

ethnic/national origin, or sexual orientation group” (28 U.S.C. 534 [Supp. IV 1996]).

According to the FBI guidelines, the definition of bias is similar to that of prejudice,

where bias is defined as ‘a preformed negative opinion or attitude toward a group of

persons based on their race, religion, ethnicity/national origin, or sexual orientation’

(Jacobs & Potter, 1997). However, definitions of hate crimes vary across jurisdictions

(Torres, 1999; Saucier et al., 2006; Petrosino, 1999). In some jurisdictions, the hate crime

statutes include religion, race, color, and national origin as their legal definition of hate

crimes, while other jurisdictions incorporated sexual orientation, physical handicap, and

gender (Petrosino, 1999). Saucier et al. (2006) indicated that criminal acts are

determined and classified as hate crimes according to the words used at the time of the

incident. For example, a suspect who has committed an assault may have used the words

‘you are not welcome in our neighborhood’. Such a statement may be interpreted as

racially prejudicial, which would result in the reclassification of the assault to a hate

crime. However, interpretation is subject to the judge’s decision of whether the words

used during the assault are indicative of a hate crime. Jacobs and Potter (1997) identify

that the term ‘hate crime’ is not congruent with its actual definition. The argument is that

while there is some overlap between hate and prejudice, the actual term ‘hate crime’

refers to criminal behavior that is motivated by prejudice, not hate (Jacobs & Potter,

1997). Prejudice is defined as either being a subconscious or conscious negative attitude

or opinion about a specific class or group of people (Jacobs & Potter, 1997).

Nolan et al. (2002) indicated that hate crimes are defined as a criminal offense

committed as a result of extreme prejudice against an individual or a group of people.

Craig (1999) defined hate crimes as the intentional selection of a victim based on

prejudice or bias associated with actual or assumed status of the victim and performing an

illegal act such as harassment, intimidation, verbal or physical assault, property damage,

and murder. The victim’s status may be based on membership of a racial, ethnic, and

religious minority group, or being physically challenged, or type of sexual orientation.

Torres (1999) defined hate crimes as crimes incited by hatred against the person because

of the person’s race, national origin, ethnicity, disability, religion, and sexual orientation.

Petrosino (1999) defined hate crimes as the majority group victimizing minority group

members because of their racial and ethnic identity. Other definitions of hate crimes

include ‘words or actions intended to harm or intimidate an individual because of her or

his membership in a minority group’ (Herek, 1989).

Despite the various definitions proposed, all hate crimes have certain elements.

They each note a criminal offense, and they all suggest prejudice as a precipitating factor.

Accordingly, this study focused on racially motivated criminal acts. Some researchers

have proposed several different societal dynamics that provoke the occurrence of hate

crimes. The following section explores several different theories suggesting why hate

crimes occur.

Social Factors That Might Promote an Environment Conducive to Hate Crimes

Several different factors have been offered as possible explanations for hate

crimes against African-Americans. Green et al. (1998) postulated that a change in the

demographic composition of an area is one possible precipitator to hate crimes.

Specifically, they found that the beginning stages of integration resulted in racial tensions

that led to racially motivated crimes. Specifically, racial tensions arose when ethnic

minorities, such as African-Americans and Latinos, moved into predominantly Caucasian

neighborhoods. The tension was associated with Caucasians defending what they

identified as their territory. It is important to note, however, the tensions were most

notable in the beginning stages of demographic change, and subsided thereafter. Greene

et al. (1998) suggested that this was because those opposed to integration fled their

neighborhoods and those who were amenable to the changes remained in the community.

This suggests that there may be something specific to individual attitudes and beliefs that

are important in understanding racial tension, and not simply changes in the demographic

composition.

Overall, racial tensions decline as communities became racially diverse, resulting

in a decreased incidence of racially motivated crimes. Although this suggestion has been

made by Green et al., (1998), other researchers have found that African-Americans are

still the most segregated minority group from Caucasians (Quillian & Pager, 2001).

Caucasians prefer to live in neighborhoods with a very small percentage of

AfricanAmericans. African-American neighborhoods with young African-American men

are perceived as having more crimes, thus fueling racially segregated neighborhoods

(Quillian & Pager, 2001). Results from one study found that neighborhoods with a high

percentage of young African-American men were associated with high crime rates

(Quillian & Pager, 2001). Thus, Caucasians tend to form this stereotype and are averse to

African-American neighborhoods with a high percentage of young African-American

men because of the perceived high crime rates, thereby reinforcing continued segregation

(Quillian & Pager, 2001).

The social dominance theory is an alternative explanation for the occurrence of

hate crimes. The social dominance theory assumes that certain groups in society have

more power than other groups. These dominant groups attempt to maintain their social

status, prefer a hierarchical arrangement, and have a propensity to display racial biases

against the minority groups. The socially dominant group tends to display discrimination

against minority groups and show favoritism towards their own in-group members

(Kemmelmeier, 2005).

Another factor hypothesized to influence hate crimes is stereotyping. Theories on

racial stereotypes have indicated that stereotypes are motivated from the emotional need

of one racial group to justify their position, relative to another racial group (Quillian &

Pager, 2001). Stereotypes of African-Americans have derived from the historical view of

African-Americans as genetically inferior (Hurwitz & Peffley, 1997). The modern

stereotype of African-Americans is that African-Americans are more violent, aggressive,

and likely to engage in criminal activity than any other ethnic minority group (Hurwitz &

Peffley, 1997; Quillian & Pager, 2001; Peffley et al., 1997). Stereotypes and beliefs

about specific ethnic minorities are shaped from media influences. The media has played

an instrumental role in portraying African-Americans as the violent underclass (Hurwitz

& Peffley, 1997). The media more frequently portrays African-Americans as violent

criminals as they are seen in mug shots, handcuffs, and in physical custody (Hurwitz &

Peffley, 1997). When a crime is violent in nature, Caucasians tend to find African-

Americans guilty and give more severe punishments because of the stereotype that

African-Americans are aggressive, violent, and hostile (Hurwitz & Peffley, 1997).

Moreover, researchers have found that racial prejudice is most pronounced against

African-Americans in comparison to other ethnic minorities, such as Latinos (Barkan &

Cohn, 2005). Consequently, Caucasians that are more racially prejudiced and believe that

African Americans are violent are more likely to want to support crime control policies

that include harsher punishments for criminals. As a result of this stereotype, African-

Americans are generally more likely to be convicted of crimes in the criminal justice

system (Austin & Erwin, 2000; Clear, 1994; Bureau of Justice Statistics, 2007;

Gerstenfeld, 2003).

Several other suggestions for the occurrence of hate crimes are related to the

social climate, which includes unemployment, poor financial conditions, advertisements

that are racially biased, radio talk show discussions, one’s own experiences with

AfricanAmericans, or the use of racially criticizing language (Torres, 1999). These broad

social conditions may also influence other factors that are related to the occurrence of

hate crimes. For instance, individuals may blame others when they have experienced a

negative event in their lives, such as losing a job. This is a phenomenon known as

scapegoating. This could potentially result in the perpetrator seeking a victim of a

minority group which the perpetrator seeks to ‘blame’, thus resulting in a hate crime

(Torres, 1999).

Overall, several different researchers have suggested multiple social factors that

promote an atmosphere of racial tension, potentially resulting in hate crimes. The

following section will explore to what magnitude hate crimes occur in the United States.

Prevalence of Hate Crimes

While Torres (1999) identified that hate crimes have substantially increased since

1990, Jacobs and Potter (1997) argued that hate crimes occurred at a greater frequency in

the past during the Jim Crow lynching era. The difference from the past to the recent

years is distinguished by a society that has become sensitive to prejudice and is motivated

to criminalize prejudicial acts (Jacobs & Potter, 1997). The Hate Crime Statistics Act of

1990 provided guidelines for recording and documenting hate crimes. The HCSA

mandated that law enforcement agencies gather data related to hate crime statistics in

their respective jurisdictions to report to the Hate Crime Reporting Unit. The statistics

derived as a result of the Hate Crime Statistics Act have revealed that hate crimes

continue to occur in the United States.

As delineated above, hate crimes are “normal” crimes that have the additional

element of prejudice. As such, any crime – violent or property – can be classified as a

hate crime. Thus, crimes such as murder or vandalism that have the underlying

motivation of prejudice can be classified as a hate crime. Hate crimes generally tend to

be brutal and more frequently occur against individuals as opposed to property (Saucier et

al., 2006). Hate crimes that occur against individuals include murder, rape, aggravated

assaults, simple assaults, criminal intimidation, and robbery (Office of Attorney General

Bob Butterworth, 1995; Nolan et al., 2002; Saucier et al., 2006; Green et al., 1998;

Torres, 1999). Nolan et al. (2002) reported that in the 1999 hate crime statistics provided

by the FBI annual crime report, 66% percent of hate crimes were categorized as assaults

and intimidations reported against persons (Nolan et al., 2002). Data from the 2002

Uniform Crime Reports provided similar information. Approximately 65% of hate

crimes were against persons versus approximately 35% that were property crimes

(Saucier et al., 2006).

Researchers have identified that African-Americans and Hispanics constitute a

high proportion of victims of hate crimes in comparison to the majority groups, with

African-Americans being the minority group more frequently targeted for hate crimes

(Green et al., 1998; Saucier et al., 2006). Researchers reviewed the 1996 statistics and

the 1999 FBI’s annual hate crime report and found that anti-race was the most frequent

form of bias, where 61% of hate crimes were motivated by racial prejudice (Nolan et al.,

2002; Torres, 1999). Statistics show that over 50% of hate crimes are committed against

African-Americans and 18% are anti-White (Jacobs & Potter, 1997; Torres, 1999; Nolan

et al., 2002; Saucier et al., 2006). Additionally, 68% of perpetrators are Caucasian,

reflecting that Caucasians are more frequently committing hate crimes (Nolan et al.,

2002; Jacobs & Potter, 1997). Moreover, an analysis of data between the years of 1992

and 1996 revealed that there was a 52% increase in hate crimes against AfricanAmericans

(Torres, 1999). Thus, it is necessary to study hate crimes, particularly among African-

Americans, as statistics reveal that African-Americans are more frequently the target of

hate crimes than other racial groups and hate crimes continue to increase (Jacobs

& Potter, 1997; Saucier et al., 2006; Green et al., 1998; Nolan et al., 2002; Torres, 1999).

The current study was conducted in Tampa, Florida, thus is it necessary to explore

hate crime statistics specific to this state. The statistics on hate crimes in Florida are

congruent with the statistics reported across the United States. Information from the

Attorney General of Florida indicated that the most commonly reported motivation for

hate crimes was race (2006). The 2006 hate crime report in Florida indicated that 55% of

hate crimes in Florida were racially motivated hate crimes. Other hate crimes reported

were crimes against religion, ethnicity, and sexual orientation. Additionally, the hate

crimes report showed that hate crimes more frequently occurred against persons.

Approximately 66% of hate crimes occurred against persons and the remaining 34% were

property crimes. The hate crimes against persons and property included acts such as

forcible sex offenses, robbery, aggravated assault, burglary, arson, simple assault,

intimidation, and vandalism. Forty-four percent of the hate crimes reported in 2006 were

aggravated assault, thus showing that this was the most common hate crime committed

that year. In Hillsborough County, there were two different agencies reporting hate

crimes, including the Hillsborough County Sheriff’s Office and the Tampa Police

Department. The Hillsborough County Sheriff’s office reported five aggravated assaults

and three intimidations. The Tampa Police Department reported three aggravated

assaults, eleven simple assaults, one intimidation, and two vandalisms (Office of Attorney

Bill McCollum, 2006). Overall, the statistics show that hate crimes continue to occur,

particularly against African-Americans. Despite the relatively high numbers of hate

crimes, they are likely to be underestimates as researchers have suggested that often times

hate crimes go unreported (McDevitt et al. 2000). Although these data indicate hate

crimes are, indeed, a persistent problem, several researchers have presented issues with

hate crime reporting and other disagreements related to hate crime concepts. The

following section focuses on this.

Controversies Related to Hate Crime Reporting, Laws, and Legislation

While the Hate Crime Statistics Act has established a systematic way of collecting

data, some researchers have noted that there is ambiguity in the guidelines. Researchers

postulate that accurate data collection is compromised because of this ambiguity (Jacobs

& Potter, 1997). One argument indicates that overall crime data collection efforts are

inadequate as agencies responsible for reporting hate crime statistics often do not

accurately report this data. Thus the statistics recorded do not accurately reflect the

incidence of hate crimes. McDevitt et al. (2000) identified that hate crimes are

underreported, representing fewer hate crimes than what is actually occurring in today’s

society (McDevitt et al., 2000; Cogan, 2002). Although some agencies do not report hate

crime statistics, researchers have noted that the hate crime reporting system is relatively

new and continues to improve (Jacobs & Potter, 1997).

Some researchers have suggested there is no need to have explicit legislation for

hate crimes. Torres (1999) highlights that some studies indicate that hate crime reporting

has not contributed towards the betterment of society in terms of improving law

enforcement practices or better understanding crime, prejudice, or prejudice-motivated

crimes. Researchers found that some people believe that hate crime laws are a violation

of the 1st Amendment because ‘a crime is a crime’. That is, the crime committed is

already being punished, and there is no need to respond to it differently based on the

offender’s motivation (Saucier et al., 2006; Gerstenfeld, 2003; Jacobs & Potter, 1997;

Torres, 1999). The belief is that hate crime laws are essentially punishing the individual

for inappropriate thinking because of their opinions, thoughts, and values (Freeman

1992/93; Gellman 1992/93; Jacobs & Potter, 1997).

Another criticism of hate crime legislation involves sentencing. Some researchers

believe that believe that enacting harsher sentences for hate crimes may actually affect

minority groups more adversely if a minority group member commits a hate crime against

a member of the majority group (e.g., an African-American offender committing a crime

against a Caucasian individual; Jacobs & Potter, 1997). Research has shown a trend

whereby minority groups receive harsher sentences than members of the majority groups;

specifically African-Americans are found guilty more frequently and receive harsher

sentences in comparison to Caucasians (Saucier et al., 2006; Gerstenfeld, 2003).

Consequently, the fear is that a similar punishment pattern will emerge with respect to

hate crimes.

Finally, Jacobs & Potter (1997) believe that the enactment of hate crimes laws

politicizes the crime problem and divides social groups instead of bringing them together.

The argument is such that hate crime laws will compel society to focus on racial aspects

associated with the crime instead of focusing on the crime committed. This will result in

increased racial tensions and societies will experience division and polarization.

However, this line of reasoning appears to be flawed in some respects. For example,

statistics show that hate crimes continue to occur despite efforts of integration and

equality, which is an issue that needs to be addressed. Simply discussing and increasing

awareness regarding hate crimes does not polarize social groups. In addition to hate

crimes stemming from racial strife, the act of the hate crime further divides social groups

because the hate crime is a public display of racial contention, which intimidates an entire

community. Hate crimes cause distress to the minority groups that experience prejudice

secondary to the hate crime. Thus, ensuring conviction of hate crime perpetrators and

increasing sentences will act as a deterrent effect to lower the incidence of hate crimes in

today’s society (Saucier et al., 2006).

Overall, several individuals have identified issues related to hate crime data

collection, laws, and legislation. Nonetheless, the laws are still in place today and

agencies continue to collect data on hate crimes in their respective jurisdictions.

Essentially, some researchers find that while hate crimes may be a simple notion to

understand, it is a very difficult concept to enact in society today because of the many

different challenges faced by hate crimes (Saucier et al. 2006).

Summary

The previous review discussed the definitions, prevalence, possible sources, and

controversies of hate crimes. All of this information suggests that hate crimes are a

serious problem in the United States that needs to be addressed. Further, as noted above,

the purpose of hate crime legislation was to enact tougher penalties to deter such

behavior. However, much of this is premised on juries perceiving hate crimes as more

deplorable than normal crimes. In the following chapter, the scant research on jury

decision making in hate crime cases is discussed to ascertain whether jurors’ behavior is

consistent with legislative intent.

Chapter Three

Overview of Race and Jury Research

Introduction to Race and Jury Research

While the current legal system assumes that jurors are supposed to focus only on

the facts of the case, some research suggests that extralegal indicators – such as race, sex,

and attractiveness of the defendant – are considered in jury decisions (Hymes et al., 1993;

Mazzella & Feingold, 1994; Zebrowitz & McDonald, 1991). Extralegal factors are

defined as any characteristic that is taken into consideration by jurors that influence or

bias the juror’s decision about adjudication or sentencing the defendant beyond the facts

of the case (Reskin & Visher 1986; Lizotte, 1978; Hagan, 1974). Although there are

several extralegal factors documented that influence juror’s decision making, race is the

most researched extralegal factor (Marcus-Newhall et al., 2002).

Although the influence of race on jury decision making is an important area of

inquiry, the knowledge garnered from the existing literature seems to have provided more

questions than answers (Sommers & Ellsworth, 2000). Of the few studies conducted,

most have yielded inconsistent results about juror’s perceptions of guilty verdicts and

sentencing related to race. For instance, some studies have found bias against defendants;

specifically, African-Americans are more likely to be arrested, convicted, and receive

harsher sentences (Sommers & Ellsworth, 2000; Marcus-Newhall et al., 2002;

Kemmelmeier, 2005). Yet, it is important to consider not just the race of the defendant,

but also the juror. Here, too, there is inconsistent evidence. While some studies have

found juror biases against defendants of the same race, others have found no differences

or inconsistent data (Sommers & Ellsworth, 2000; Marcus-Newhall et al., 2002;

Kemmelmeier, 2005). In addition, researchers have found anti-White biases for

highstatus crimes, like embezzlement, in which Caucasians are more likely to be found

guilty.

However, for low-status crimes like robbery and assault, anti-minority biases occur

(Kemmelmeier, 2005). Moreover, few studies consider the perceptions of

AfricanAmerican jurors (Sommers & Ellsworth, 2000). This is important because

research indicates that in-group bias might exist. That is, African-American mock jurors

may be more lenient towards African-American defendants than Caucasian mock jurors

(Abshire

& Bornstein, 2003).

In-Group versus Out-Group Favoritism and Racial Salience in Jury Decision Making

Several different theories and factors that influence jury decision making have

been suggested. Racial salience is a phenomenon that has been studied in the race and

jury literature. Studies have found that when Caucasian jurors are reminded of racial

prejudice, they are more likely to pay attention to legally relevant information when the

defendant is African-American. Thus, Caucasian jurors are more likely to

overcompensate because of the motivation to appear non-prejudicial (Sommers &

Ellsworth, 2000; Sargent & Bradfield, 2004; Kemmelmeier, 2005). However when race

is less salient, racial prejudice is more often expressed (Sommers & Ellsworth, 2000).

For example, Sargent and Bradfield (2004) conducted two studies composed of all

Caucasian participants recruited from public places, such as shopping malls and the

airport. In this study, participants read a case where either a Caucasian or

AfricanAmerican man was charged with armed robbery, and the alibi offered was either

strong or weak. There were two additional conditions presented in the study. The first

was where mock jurors were not motivated to pay attention to the details of the case by

being informed that the study was a pilot study in preparation for future research and they

would receive $5 for participation; this condition was named the ‘low motivation’

condition. The second condition motivated mock jurors to pay attention to the case

details, and was labeled the ‘high motivation’ condition (mock jurors were informed that

case was a real case and the results of the study would impact future jury instruction;

additionally mock jurors would only be compensated $5 if their responses were congruent

with the outcome of the actual case). The researchers found that when participants were

highly motivated to pay attention to the trial details, race did not have any effect.

However, in the low motivation condition, race played an effect on the mock jurors’

likelihood of finding the defendant guilty based on the alibi presented (Sargent &

Bradfield, 2004). Specifically, the mock jurors were likely to find the defendant guilty if

the defendant was African-American and had a weak alibi. However, there was no effect

for Caucasian defendants on alibi strength with guilt adjudication (Sargent & Bradfield,

2004).

In the second study conducted by Sargent and Bradfield (2004), the conditions

were similar to the first study. The only difference was that the alibi strength

manipulation was replaced by the district attorney’s effectiveness of cross examination of

the defense witness. The results showed a three-way interaction effect such that in the

low motivation condition where participants were sensitive to the cross-examination if

the defendant was African-American. There was no race effect found in the high

motivation condition related to cross-examination (Sargent & Bradfield, 2004). In

summary, the impact of legally relevant information was more important when the

defendant was African-American and the motivation was low.

Another factor that influences jury decision making is the psychological

phenomenon of in-group versus out-group favoritism. In-group bias is defined as bias

whereby members of a particular racial group tend to show favoritism for their own

members of that particular racial group. Out-group bias is described as preference

towards non-members of that particular racial group (Sommers & Ellsworth, 2000). One

may propose that the ‘Black Sheep Effect’ has occurred when out-group bias occurs. The

‘Black Sheep Effect’ is defined as “in-group targets are rated more negatively than

outgroup targets when a target’s features are unambiguously negative” (Khan & Lambert,

1998). This theory has garnered some credibility in psychological research. For instance,

it has been found that people tend to be more punitive to in-group members when an in-

group member commits a crime (Prooijen, 2006; Marcus-Newhall et al., 2002). It is

considered a negative attribute when an individual commits a crime. The more severe the

crime, the more negative the crime is presumed. In-group members are motivated to

maintain a positive social status and avoid negativity. Thus, when an ingroup member

commits a crime, other in-group members tend to avoid any association with that

particular in-group criminal. Therefore, in-group members tend to be more punitive

towards members of their own group who commit crimes in efforts to maintain a positive

social status and disassociate with negativity.

Conversely, other studies have shown that some people display ‘in-group’

favoritism to criminal suspects. Generally, the studies that found in-group favoritism

occurred in situations where the guilt of the defendant was disputable (Prooijen, 2006).

While individuals may display in-group favoritism in certain situations, on the other

hand, racial salience mitigates this; when racial issues are made salient, Caucasian mock

jurors tend to show less favor to their in-group member. Caucasian mock jurors were

more likely to adjudicate the suspect guilty in racially salient conditions. When the

situation was vague, jurors tended to exhibit in-group favoritism (Marcus-Newhall et al.,

2002). Other studies have found that jurors were more likely to find the in-group

defendant guilty when the evidence was strong. However, they were likely to find the out-

group defendant guilty when the evidence was weak (Prooijen, 2006). Kemmelmeier

(2005) found that individuals of an oppressed group generally presented leniency towards

their own in-group members and showed harsher reactions to the out-group/racially

dominant group.

Another study was conducted to examine the in-group/out-group phenomenon.

Prooijen (2006) conducted four experiments designed to examine in-group versus

outgroup bias. The results of one study indicated that participants displayed more

retributive affect towards in-group members when guilt was certain and less retributive

affect to outgroup members. Participants were more likely to seek justice and be more

punitive to ingroup members versus out-group members when guilt was certain.

However, they showed less retributive affect to in-group members when the guilt was

uncertain and more retributive affect to out-group members when the guilt was uncertain.

While there was no guilt probability main effect found in the first experiment, a main

effect was found in the second experiment; the researcher attributed this finding to the

higher severity of the crime in the second experiment (Prooijen, 2006). Based on the

findings of these two studies, it was concluded that guilt probability is a moderating

factor of the influence of social classification on an individual’s punitive emotions, that is,

their ratings of anger and hostility.

Other studies have shown that there is in-group bias when that group has high

status and power. However, there tends to be out-group favoritism when that particular

group is of lower status and power (Marcus-Newhall et al., 2002). Sommers and

Ellsworth (2000) conducted two studies aimed at elucidating these effects. In the first

study, they provided trial summaries and questions to college students; race was made

salient in the trial summaries. The study showed that African-American mock jurors

were more likely to convict Caucasian defendants. Caucasian defendants did not show

any preference for convicting either the African-American or Caucasian defendant. This

result is consistent with the idea that African-American jurors are less likely to convict

their in-group members. It is also congruent with the social dominance theory. This

theory assumes that individuals of a lower social class tend to distrust higher institutions,

such as the judicial system as they suspect these higher entities of discriminating against

minority groups (Kemmelmeier, 2005).

On the other hand, the social dominance theory suggests that individuals in higher

social classes are more likely to have faith in higher institutions, and as such perceive

judicial systems are fair and just (Kemmelmeier, 2005). Consequently, AfricanAmericans

that already believe that justice institutions are unfair are less likely to convict their in-

group member. In a study of social dominance, Caucasian participants (undergraduates)

in a mock-juror situation were presented with an assault case and the race of the

defendant was manipulated. The results indicated that individuals in the

social dominant group were likely to give guilty judgments and high sentence

recommendations as they exhibited anti-black biases. However, the individuals who were

low in social dominance showed pro-Black biases (Kemmelmeier, 2005).

In the second study, Sommers & Ellsworth (2000) recruited participants at an

airport and randomly assigned individuals to one of four versions of the trial summary.

Some of the conditions in the study were race-salient conditions, while other conditions

were non-race salient. In the race salient conditions, African-American mock jurors were

more likely to exhibit same-race leniency, while Caucasian mock jurors appeared

nonprejudicial. In the non-race salient condition, both African-American and Caucasian

mock jurors demonstrated in-group favoritism where they found out-group members

guilty and gave harsher sentences (Sommers & Ellsworth, 2000).

Race and Jury Decision Making Summary

Overall, researchers have identified race as an influential extralegal factor. The

research on race and jury decision making primarily focuses on racial salience, and how it

affects in-group and out-group bias. Prior research has also demonstrated that individuals

exhibited in-group and out-group bias in certain circumstances. Researchers found that in

racially salient circumstances, Caucasian participants generally paid special attention to

case details in attempts to appear non-prejudicial, while African-American mock jurors

demonstrated in-group favoritism. However, in non-race salient conditions, Caucasian

and African-American mock jurors exhibited in-group bias. Overall, African-

American mock jurors tended to exhibit in-group favoritism when the defendant was

African-American in criminal cases despite racial salience. These factors may be

particularly important in hate crimes, which are inherently race salient. However, very

little is known about the specific influence of hate crimes on mock juror decision making

and what factors are related to jurors’ perceptions of hate crimes. The following section

describes the scant research in this area and highlights the need for additional research.

Hate Crime and Jury Decision Making Research

Hate crimes and jury decision making is an important area to study because hate

crimes produce a very unique dynamic. Although it is important to understand hate crime

and jury decision making because hate crimes continue to occur, surprisingly there is very

little research conducted in this area. In fact, a literature search revealed only four studies

on this topic. This section will explore the results of the four existing research studies.

Marcus-Newhall et al. (2002) conducted three separate studies involving hate

crimes and jury decision making. The study participants (all Caucasian college students)

read a paragraph about a shooting that took place between two motorists; racial slurs were

mentioned in this scenario. In the first experiment, the researchers looked at the effect

of the race of the victim (African-American, Caucasian), race of the perpetrator (African-

American, Caucasian), and political orientation (self-identified conservative, liberal).

The study found that when the hate crime was committed by a Caucasian against an

African-American victim, participants were more likely to give a guilty adjudication and

a longer sentence than in the scenario in which an African-American committed a hate

crime on a Caucasian victim (Marcus-Newhall et al., 2002). In this experiment,

Caucasians did not show in-group bias, suggesting that Caucasians no longer receive

ingroup favoritism because of the misuse of the power they have in society by

committing a hate crime (Marcus-Newhall et al., 2002).

In the second experiment, the researchers replicated and extended the findings

from the first experiment by surveying individuals from a food court. This sample was

presumed to be more similar to actual jurors than a sample of college students. Findings

from this study indicated that when Caucasians committed a hate crime against an

African-American victim, it was perceived as a more negative event, in comparison to a

hate crime committed by an African-American perpetrator on a Caucasian victim

(Marcus-Newhall et al., 2002). Additionally, the researchers found that there was a

higher certainty of guilt when the victim was African-American and the perpetrator was

Caucasian. However there was no significant effect on sentencing rating.

In the third experiment, the researchers recruited 35 minority and 83 Caucasian

participants. The race of the perpetrator was held constant as Caucasian, while the race of

the victim was manipulated. Juror race was also examined to determine what influence it

might exert on guilt outcomes. The results showed that minority participants displayed

in-group favoritism. Specifically, minority mock jurors perceived the hate crime event

more severe when the victim was African-American than when the victim was Caucasian

(Marcus-Newhall et al., 2002). Overall, race of the perpetrator and race of the victim

differentially influenced mock jurors (Marcus-Newhall et al., 2002). While prior research

has demonstrated in-group favoritism in non-race salient conditions (Sommers &

Ellsworth, 2000), hate crime research is congruent with racially salient findings, such that

Caucasian mock jurors do not exhibit in-group favoritism (Sommers & Ellsworth, 2000;

Marcus-Newhall et al., 2002). Researchers have suggested that the out-group favoritism

is connected to attempts to appear non-prejudicial (Sommers & Ellsworth, 2000; Marcus-

Newhall et al., 2002); this attempt is explained by the aversive racism theory (Gaertner &

Dovidio, 1988).

The aversive racism theory hypothesizes a sub-conscious effort by Caucasian

Americans who hold prejudicial attitudes to maintain a non-prejudicial social image.

Aversive racists believe that they are not prejudiced; however they have negative, racist

beliefs and feelings that they may be unaware of, or that they try to disassociate from

their social image. The negative, racial beliefs generally stem from learned social biases

that may have been influenced by media representations of minority groups. Aversive

racists will not show their prejudicial attitudes in public. However, a display of prejudice

may occur in situations where their actions can be justified by another cause other than

race, such as negligence committed by a minority group member (Gaertner & Dovidio,

1988).

The second study on hate crimes was conducted by Gerstenfeld (2003). In this

study, the researcher recruited 190 voluntary participants, composed of both

undergraduate students and non-student adults. The participants were informed that the

perpetrator had been charged with an assault felony, felony assault with a deadly weapon,

and a hate crime. He hypothesized that African-American defendants would be found

guilty at a significantly higher rate and receive harsher sentences in comparison to

Caucasian defendants. This is consistent with the general research findings regarding

punitive behavior toward African-American defendants (Sommers & Ellsworth, 2000;

Marcus-Newhall et al., 2002; Kemmelmeier, 2005). However, this study found results

similar to other studies in hate crimes and jury decision making research. Specifically,

jurors were more certain of Caucasian defendants’ guilt and convicted Caucasian

defendants more frequently of hate crimes. However there was no difference in

sentencing (Gerstenfeld, 2003). Although the results were opposite to the researcher’s

hypothesis, the results were congruent with hate crime research in jury decision making.

The researcher initially attributed his hypothesis to stereotypes about African-Americans.

This stereotype generally suggests that African-Americans are found guilty more

frequently and receive harsher sentences than Caucasians. However, statistics show that

African-Americans are more frequently victims of hate crimes, and Caucasians are

generally the perpetrators of hate crimes (Green et al., 1998; Saucier et al., 2006; Nolan et

al., 2002; Jacobs & Potter, 1997). Thus, the stereotype for hate crimes (AfricanAmerican

victims and Caucasian perpetrators) is different from general stereotypes about African-

American criminal behavior.

The third hate crime study (Saucier et al., 2006) sought to examine the mock juror

(i.e., college students) beliefs about hate crimes sentencing compared to non-hate crimes.

The participants read an assault crime scenario where the defendant insulted the victim

with racial slurs. The results of this study showed that the participants were more likely

to give more severe sentences when the victim was an African-American male, Jewish

male, Latino male, Asian male, or gay male than if the victim was a Caucasian female or

a Caucasian male in the simple assault conditions. They also found that participants were

likely to classify the assault as a hate crime when it was against a minority group member

than when it was against Caucasians. Additionally, the participants believed that the hate

crimes were more severe than other crimes (Saucier et al., 2006). Notably, however, the

authors did not explicitly label the crime depicted in the scenario as a hate crime. This is

important because using the term, hate crime, ensures participants’ awareness of the

presence of the hate crime; this avoids potential misinterpretations between racially

manipulated scenarios and actual hate crime conditions.

In the fourth hate crime study, Craig et al., (1999) examined 24 African-American

and 49 Caucasian male participants observing video-taped assaults, across two

conditions. In one condition the perpetrator and the victim were the same race. In the

second condition, the race was varied where the assailant was Caucasian and the victim

was African-American, and vice versa. In this condition, the perpetrator and the victim

exchanged racially provocative remarks. The second condition was classified as the hate

crime condition in this study. The results of this study showed that African-American

participants rated the hate crime event as more typical and likely to occur in comparison

to the Caucasian participants. Additionally, African-American participants indicated that

they were more likely to retaliate and express desire for revenge if put in a similar

situation (Craig, 1999).

All four studies are congruent with history and statistics that show that African-

Americans tend to be victims of hate crimes more frequently than Caucasians (Craig,

1999; Marcus-Newhall et al., 2002; Gerstenfeld, 2003; Saucier et al., 2006; Jacobs &

Potter, 1997; Saucier et al., 2006; Green et al., 1998; Nolan et al., 2002; Torres, 1999).

Stereotypic notions of what a hate crime is, is influenced by the perpetrator and victims’

races. While the studies presented in this section provide an opening to research in this

area, the studies have identified flaws that need to be addressed for future research. The

following section explores the flaws found in these studies.

Flaws in Existing Hate Crime and Jury Decision Making Research

The design in the Craig et al. (1999) study was flawed. First, all participants

watched the video scenes where the assault occurred either on the same race or different

race victim. This design is flawed because it inhibits the participants’ ability to

independently evaluate each scene since they have been exposed to both crime scenarios.

Juror perceptions of the race manipulated condition are influenced by the observation of

the non-race condition. Ideally, participants should be randomly assigned to different

assault conditions, one group of participants having observed only the non-race condition,

and another group of participants having observed the race manipulated condition.

Other hate crime researchers (Marcus-Newhall et al. 2002; Gerstenfeld 2003;

Saucier et al., 2006) presented a racially varied assault condition and labeled it as a hate

crime; however, the term hate crime for this condition is not actually used. Only Craig et

al. (1999) actually used the term hate crime in their study. As opposed to simply

manipulating the race in an assault condition, the use of the term hate crime and

providing sentencing guidelines for hate crimes may significantly alter the results of a

study. This is because labeling the crime as a hate crime increases racial salience.

Moreover, one of the very important concerns is that while all of the studies

manipulated race, none of the studies took into consideration that other factors, other than

race, may have influenced adjudication and sentencing outcomes. For instance,

perceptions of aggressiveness are known to influence sentencing and adjudication

(Hurwitz & Peffley, 1997; Quillian & Pager, 2001; Peffley et al., 1997). However none

of the studies demonstrated that any potentially influential factors were controlled for.

Marcus-Newhall et al. (2002) manipulated the race of the victim, the race of the

perpetrator, and the role of peer group (peer influence – encouraging discouraging),

however there was no attempt to control for any confounding factors. Gerstenfeld (2003)

manipulated the offender's race, the victim's race, and the participant’s level of racism,

however other covarying factors were not considered. In the Saucier (2006) article, the

researchers manipulated severity of crime, and the target's group membership; however

potential influential factors were not discussed. And finally Craig et al. (1999)

manipulated race of the perpetrator; the victim was always the same race as the

participant’s race; however other factors that may impact the outcomes were not included

in the study.

Jury Decision Making in the Context of Hate Crimes Summary

In summary, to my knowledge, only four hate crime and jury decision making

studies have been conducted. Research in this area is particularly interesting as it reveals

an in-group/out-group dynamic. The results of hate crime studies show that since the

hate crime condition is a racially salient condition, Caucasian mock jurors tend to find

Caucasian defendants guilty and impose harsher sentences when the victim is

AfricanAmerican; Caucasian defendants show out-group favoritism while African-

American mock jurors demonstrate in-group favoritism. The hate crime studies, as well

as the statistics provided show congruency with the stereotypes, such that Caucasians

tend to be perpetrators of hate crimes and African-Americans tend to be the victims.

Of the studies examined, all studies have identified flaws. Of significance, while

prior studies have found significant results, none of the studies have examined to what

extent legally relevant and legally irrelevant factors exert influence on mock juror’s

decision making on adjudication and sentencing recommendations. Additionally, in some

of the study designs, participants were exposed to all conditions. Three of the four

conditions did not use the term hate crime. The current study seeks to address all the

flaws indicated. The following chapter will describe the methods used to conduct the

study. The chapters after the methods include the results, discussion, and conclusion.

Chapter Four

Methods

Participants

Participants were recruited from undergraduate criminology classes at a large,

state university in Florida. Participants were informed that the study was confidential and

their participation was voluntary. Because the courses serve a wide variety of

undergraduate students, the sample was reasonably representative of the student body of

the university. Although there are some differences between undergraduate samples and

non-college samples generally (Sears, 1986), such samples have been found to be

acceptable in jury decision making research. For instance, after a 20 year review of jury

simulation studies, Bornstein (1999) noted that not only are the majority of studies based

on college samples, but that there are few substantive differences between college and

community samples. Thus, the current sample is acceptable and consistent with previous

studies on jury decision making.

Procedure

Researchers have noted that numerous studies use the experimental approach by

providing mock jurors a trial summary and questionnaires (Sommers & Adekanmbi,

2008, Bornstein, 1999). Sommers & Adekanmbi (2008) indicated that the experimental

approach is frequently used as it increases internal validity by controlling for many

factors that could potentially influence mock jurors. Using the experimental approach

allows researchers to hold all other factors constant and focus on the variables they are

attempting to manipulate (Sommers & Adekanmbi, 2008). As such, in the current study,

participants were informed that they would participate in a study on legal opinions.

Specifically, they were asked to read a hypothetical court transcript and answer a series of

questions about how they decided in the case, as well as their opinions of the defendant,

victim, and witnesses who testified. As noted below, there were four different versions of

the trial. These different scenarios were randomly distributed to participants during a

regular class session. Participants were asked to return the completed questionnaire

within one week. The trial scenario and questionnaire took approximately 20 minutes to

complete. Students were given extra credit in the course for completing the protocol.

Students who opted not to participate in the research, but wanted extra credit were

provided with an alternative way of earning extra credit.

Study Materials

Participants were randomly assigned to one of four conditions. In all conditions,

participants were provided with the basic facts of the case, which were supplemented

with an abbreviated court transcript. In every scenario, the offenses (aggravated battery

and robbery) and the facts of the case were the same. What varied across the scenarios

was the inclusion of racially salient material. The race of the offenders and victims were

also varied all study conditions. The first and second conditions were the racially salient

hate crime conditions. The third and fourth conditions were non-hate crime conditions.

In the first and third condition, the victim was African-American and the perpetrator was

Caucasian. In the second and fourth condition, victim was Caucasian and the perpetrator

was African-American. The first two conditions were termed the hate crime conditions as

they were explicitly defined as hate crimes. In addition, these initial two conditions

contained testimony that the offender used racial slurs. The third and fourth condition did

not include testimony that the perpetrator used racial slurs; only the race of the victim and

perpetrator were varied. Therefore, the third and fourth conditions were named the non-

hate crime conditions. After reading the trial scenario, participants answered several

questions (see next section, Measures of Dependant Variables).

Measures of Independent and Dependent Variables

Verdicts. Jurors were asked to render separate verdicts (for aggravated battery and

robbery) in this hypothetical case. Specifically, they chose between the options of “1 =

Guilty” and “2 = Not Guilty.” In addition, they were asked to indicate the likelihood that

the defendant committed the crimes; responses ranged from 1 (“not at all likely”) to 10

(“the defendant definitely committed the crime”). Participants were asked the second

question to establish variability in responses with respect to adjudication.

Punishment Severity. Jurors were asked to recommend a sentence for aggravated

battery and robbery. Jurors were asked to rate how much punishment the defendant

deserved on a scale of 1 (no punishment) to 10 (maximum punishment). Participants

were also asked to recommend a sentence, from no sentence to 13 – 15 years for the

nonhate crime conditions or no sentence to 28 – 30 years for the hate crime conditions.

While jurors in actual cases do not determine sentencing, I was interested in investigating

whether participants would respond in accordance with sentencing guidelines and hate

crime laws.

Perceptions of Trial Participants. In all conditions, jurors responded to questions

asking how aggressive they believed the defendant was on a scale of 1 (not aggressive at

all) to 10 (very aggressive). They rated how likely they believed the defendant would

commit a crime in the future on a scale of 1 (not likely) to 10 (very likely). Correlational

analyses were computed to examine inter-relationships between the two above mentioned

variables. Results indicated that the defendant’s perceived aggressiveness and likelihood

for future criminal activity were strongly, significantly, and positively correlated (r = 0.8,

p < .01). As such, a dangerousness variable was created by combining the raw scores of

the defendant’s perceived aggressiveness and likelihood of future criminal activity.

Additionally, jurors rated the credibility of the witnesses (victim and police) in the trial on

a scale of 1 (not believable at all) to 10 (very believable). And finally, mock jurors rated

how attractive they believed the defendant and the victim were on a scale of 1 (not

attractive) to 10 (very attractive). Mock jurors were asked about their perceptions on

dangerousness, witness credibility, and attractiveness because prior research has

suggested that the above mentioned perceptions exert influence on mock juror’s decisions

on adjudication and sentencing (Marcus-Newhall et al., 2002; Hymes et al., 1993;

Mazzella & Feingold, 1994; Reskin & Visher 1986; Lizotte, 1978; Hagan, 1974).

Although these factors influence juror decision making, some factors are expected to

exert influence (legally relevant variables), while others are not (legally irrelevant

variables). Specifically, witness credibility is a legally relevant factor for guilt

adjudication; it is a legally irrelevant factor for sentencing (775.085, Florida Statutes,

Supp. 1998). Dangerousness is a legally relevant factor for sentence recommendations

and deserved punishment; it is a legally irrelevant factor for guilt adjudication (775.085,

Florida Statutes, Supp. 1998). Attractiveness, however, is a legally irrelevant factor for

all outcomes (Zebrowitz & McDonald, 1991). Mock jurors were asked about the above

mentioned factors as they may be potential covariates that influence adjudication,

deserved punishment, and sentencing outcomes. The aim of this study was to examine

the true independent effects of offender-victim racial composition and type of crime

manipulations, by controlling for these covarying factors.

Perceptions of Racially Motivating Factors. In the first two conditions that were

labeled hate crime conditions, mock jurors were asked whether they believed the crime

committed was a hate crime; mock jurors answered yes if they believed it was a hate

crime and no if they did not believe it was a hate crime. Furthermore, in the hate crime

and non-hate crime conditions, mock jurors were asked whether they believed the victim

was a target because of his race on a scale of 1 (not likely) to 10 (very likely) and whether

the defendant was prejudicial on the same scale. Correlational analyses were computed

to examine inter-relationships between these latter 2 variables. The results demonstrated

a strong, significant and positive correlation between the defendant’s prejudice and

whether the victim was targeted because of race (r = 0.6, p < .01). Therefore, a hate

motivation variable was created by combining the raw scores of two variables indicated

above. Similar to the covariates (dangerousness, witness credibility, and attractiveness)

previously indicated, hate motivation was examined as a potential covarying factor, as it

is known to influence adjudication and sentencing outcomes (Craig et al., 1999; Saucier

et al., 2006; Gerstenfeld, 2003; Marcus-Newhall et al., 2002). Additionally, with respect

to legal relevance in criminal cases, hate motivation is a legally relevant factor for hate

crime adjudication and sentencing and a legally irrelevant factor for crime adjudication

and non-hate crimes (775.085, Florida Statutes, Supp.

1998).

Juror Characteristics. Jurors answered questions regarding demographic

characteristics. Specifically, jurors responded to questions about age, sex, race, and

ethnicity. The purpose of obtaining demographic information was to garner information

on the mock juror characteristics for the sample acquired for this study.

Hypothesis

This section outlines the hypotheses for the hate crime conditions for both

aggravated battery and robbery, as well as hypotheses focusing on the interracial

dynamics of the offender and victim dyads.

Hypothesis 1: Based on previous research that has focused on the influence

of racial salience, there will be differences in adjudications across the experimental

conditions:

1a). Chi-square analyses will indicate that the distribution of guilt adjudication for

aggravated assault and robbery will significantly vary across experimental conditions;

1b). Chi-square analyses will indicate that the distribution of hate adjudication

will significantly vary across experimental conditions;

Hypothesis 2: Several covariates will be included in the multivariate models

to examine their influence on guilt adjudication, deserved punishment, and sentence

recommendations. Additionally, the covariates will be included in the multivariate

model to examine whether the experimental manipulations persist after controlling

for offender dangerousness, witness credibility, and hate motivation. The following

hypotheses are offered regarding those covariates:

2a). Perceptions of witness credibility (victim and police) will be significantly

related to ratings of the likelihood that the defendant committed both crimes (aggravated

battery and robbery);

2b). Perceptions of offender dangerousness will be significantly related to

sentence recommendations and deserved punishment for aggravated battery and robbery;

2c). Perceptions of hate motivation will be significantly related to deserved

punishment and sentence recommendations for aggravated battery and robbery;

Although previous research has suggested that hate crimes are viewed differently

than non-hate crimes, the extant literature has not examined the influence of

offendervictim racial composition and the effect of labeling crimes as hate crimes. In this

study, the offender–victim dyad was expected to interact with the effect of labeling the

crimes as hate crimes even after controlling for offender dangerousness, witness

credibility, and hate motivation. As such, the following hypotheses are proposed:

Hypothesis 3: There will be no main effect observed for type of crime (hate

versus non-hate) on ratings of the likelihood the defendant committed aggravated

battery and robbery, deserved punishment, and sentence recommendations.

Hypothesis 4: There will be no main effect observed for offender-victim racial

composition (Caucasian offender/African-American victim versus AfricanAmerican

offender/Caucasian victim) on ratings of the likelihood the defendant committed

aggravated battery and robbery, deserved punishment, and sentence

recommendations.

Hypothesis 5: There will be an interaction between type of crime (hate versus

non-hate) and offender-victim racial composition (Caucasian

offender/AfricanAmerican victim versus African-American offender/Caucasian

victim) on ratings of the likelihood the defendant committed aggravated battery and

robbery, deserved punishment, and sentence recommendations after controlling for

offender dangerousness, witness credibility, and hate motivation:

5a). For those conditions labeled as hate crimes, there will be significantly higher

means on (1) the likelihood that the defendant committed the crimes, (2) the deserved

punishment, and (3) the recommended sentence when the victim is African-American and

the defendant is Caucasian after controlling for offender dangerousness, witness

credibility, and hate motivation [compared to when the victim is Caucasian and the

defendant is African-American];

5b). For those conditions that are not labeled as hate crimes, there will be

significantly higher means on (1) the likelihood that the defendant committed aggravated

battery and robbery, (2) the deserved punishment, and (3) the recommended sentence

when the victim is Caucasian and the defendant is African-American after controlling for

offender dangerousness, witness credibility, and hate motivation [compared to when the

victim is African-American and the defendant is Caucasian];

Design and Statistical Analysis

I computed descriptive statistics to obtain information on the mock juror

characteristics for the sample acquired. Correlations were conducted to establish

relationships among variables. Chi-square analyses were also computed to examine

categorical data for guilt adjudication for aggravated battery and robbery, and perceptions

of hate crimes. I conducted a 2 x 2 Factorial Multivariate Analysis of Variance

(MANOVA) to examine main effects for type of crime (hate versus non-hate),

offendervictim racial composition (Caucasian/African-American), and the interaction

between these two variables on ratings of likelihood the defendant committed aggravated

battery and robbery, deserved punishment, and sentencing. I then examined the same

fixed factors and outcome variables after controlling for perceived racial motivation,

dangerousness, and witness credibility. Because covariates were included in this final

series of analyses, a 2 x 2 Factorial Multivariate Analysis of Covariance (MANCOVA)

was used.

Chapter Five

Results

In the current study there were 90 participants. All participants were

undergraduate college students enrolled in criminology courses. There were 60 (66.7%)

Caucasian participants, 12 (13.3%) African-American participants, 16 (17.7%) other

participants (Asian, American-Indian or Alaska Native, and Native Hawaiian or Other

Pacific Islander), and 2 (2.2%) participants missing race information. Twenty (22.2%)

participants identified themselves as Latino/Hispanic, and 70 (77.8%) participants who

did not identify themselves as Latino/Hispanic. There were 43 (47.8%) female and 47

(52.2%) male participants. The ages of the participants ranged from 19 years old to 50

years old. The average age was 23 years old.

First, bivariate correlations were computed to explore the relationships among the

study variables. Of particular interest were the relationships between dangerousness, hate

motivation, witness credibility (police and victim), and attractiveness, with likelihood for

guilt adjudication, deserved punishment, and sentencing. Cohen’s (1992) standards were

used to determine small, medium, and large effect sizes for this study.

The results showed that for aggravated battery, there was a significant, strong, and

positive relationship between the outcome variable of likelihood of guilt adjudication and

dangerousness (r = 0.761, p < .01) and police credibility (r = 0.576, p < .01), a moderate

relationship with victim credibility (r = 0.409, p < .01), and a small relationship with hate

motivation (r = 0.281, p < .01). Additionally, for robbery, there was a significant, strong,

and positive relationship between likelihood of guilt adjudication and perceived

dangerousness (r = 0.693, p < .01), moderate relationships with witness credibility with

both victim (r = 0.342, p < .01) and police (r = 0.438, p < .01), and a small correlation

with hate motivation (r = 0.221, p < .05). Attractiveness was not significantly related to

likelihood of guilt adjudication for aggravated battery and robbery.

Regarding the outcome variable of deserved punishment, the results showed a

significant, strong, and positive relationship between deserved punishment and perceived

dangerousness (r = 0.622, p < .01), and moderate relationships with hate motivation (r =

0.493, p < .01) and witness credibility with both the police (r = 0.540, p < .01) and the

victim (r = 0.409, p < .01) for aggravated battery. There were significant, positive, and

moderate relationships observed between deserved punishment and perceived

dangerousness (r = 0.480, p < .01), and police credibility (r = 0.335, p < .01), and small

relationships with victim credibility (r = 0.199, p < .05) and hate motivation (r = 0.292, p

< .01) for robbery. Attractiveness was not significantly correlated with deserved

punishment for aggravated battery and robbery.

Finally, in reference to the outcome variable for sentencing, the results indicated

that there was a significant, strong, and positive relationship between sentencing and

perceived dangerousness (r = 0.565, p < .01) and a moderate relationship with hate

motivation (r = 0.449, p < .01). Additionally, there was a significant, moderate, and

positive relationship between sentencing and witness credibility for both police (r =

0.510, p < .01) and victim (r = 0.364, p < .01) for aggravated battery. The results also

showed that there were significant, moderate, and positive relationships between

sentencing and perceived dangerousness (r = 0.581, p < .01), hate motivation (r = 0.387, p

< .01), and witness credibility for the police (r = 0.416, p < .01), and a small relationship

with witness credibility for the victim (r = 0.261, p < .01) for robbery. Attractiveness was

not significantly related to sentencing for aggravated battery and robbery.

In summary, dangerousness, hate motivation, and witness credibility (police and

victim) were significantly related to likelihood of guilt adjudication, deserved

punishment, and sentencing. However attractiveness was not significantly correlated

with any of the outcome variables (see Table 1). Therefore, the bivariate findings

indicate that factors, such as dangerousness, witness credibility, and hate motivation need

to be controlled for in the multivariate analyses in order to evaluate the whether or not the

manipulations related to (1) labeling the crime as a hate crime and (2) varying the

victimoffender races exerted any independent influence. Attractiveness was not included

in the multivariate analyses as a covariate as it was not related to likelihood of guilt

adjudication, deserved punishment, and sentencing.

Table 1

Correlations Between Adjudication and Punishment Variables with Aggressiveness,

Likelihood of Future Crime, and Prejudice for the Hate Crime Study

Prison

Battery

Punishment

Battery

Prison

Robbery

Punishment

Robbery

Likely Likely

Battery Robbery

Danger.565**

.622**

.480**

.581**

.761**

.693**

Race .449**

.493**

.292**

.387**

.281**

.221*

Motivation

Police .510**

.540**

.335**

.416**

.576**

.438**

Credibility

Victim .364**

.409**

.199*

.261**

.409**

.342**

Credibility

Def. .003

.134

-.061

.087

.094

.031

Attractiveness

Victim .088

Attractiveness

.134

.007

.160

.140

.120

n = 90 **p

< .01

*p < .05

Following correlational analyses, I conducted chi-square analyses to test whether

there were differences across experimental conditions for 1. guilt adjudication and 2. hate

adjudication. The first chi-square analysis examined whether the guilty verdicts (guilty

vs. not guilty) varied by condition for the aggravated assault and robbery. The first

hypothesis suggested that there would be observed differences in adjudication across the

experimental conditions. The chi-square was statistically significant, therefore suggesting

that there were significant differences across the cells that did not occur by chance for

aggravated battery (χ2 (3, n = 89) = 11.795, p < .05). However, the chi-square for robbery

was not statistically significant (χ2 (3, n = 90) = 6.458, p > .05), thus there were no

differences across the cells; therefore hypothesis 1a. was supported for aggravated battery

only. Although chi-square analyses cannot indicate precisely which cells differ from one

another, an examination of the percentages in each cell does provide some insight into

where the greatest differences lie. Thirty-one percent of mock jurors found the African-

American defendant (Caucasian victim) guilty for aggravated battery, in comparison to

17.8% of mock jurors who found the Caucasian defendant (AfricanAmerican victim)

guilty for aggravated battery when comparing the two hate crime conditions. When

comparing the non-hate crime conditions, 11.1% of mock jurors found the African-

American defendant (Caucasian victim) guilty for aggravated battery compared to 40.0%

of mock jurors who found the Caucasian defendant (African-

American victim) guilty for aggravated battery. Please see table 2 for details. It is

important to note that these analyses did not include covariates. Thus, it remains unclear

whether these differences were due to the experimental manipulations or some other

factors. (This more detailed analysis will be the focus of the MANCOVAs that follow.)

Table 2

Chi-Square Analysis for Guilty Verdicts for Assault and Robbery – the Observed Counts

vs. Expected Counts

Aggravated Battery

Robbery

Condition

Guilty

Not Guilty

Guilty

Not

1. Hate – BV/WD Count

% within Decision

17.8%

20.5%

19.5%

18.4%

2. Hate – WV/BD Count

% within Decision

31.1%

25.0%

34.1%

24.5%

3. Non-Hate – BV/WD Count 14

% within Decision 40.0%

15.9%

34.1%

22.4%

4. Non-Hate – WV/BD Count 5

% within Decision

11.1%

38.6%

12.2%

34.73%

Total

% Total within Decision

100.0%

n = 90

The third chi-square test examined whether participants viewed the two hate

conditions as actual hate crimes. Since the first two conditions were described as hate

crimes (the remaining two conditions did not contain explicit suggestion that the crimes

were classified as hate crimes), only these two conditions were included in this analysis.

The results showed that the chi-square value was statistically significant, indicating that

the distribution for hate adjudication significantly varied across experimental hate crime

conditions (χ2 (1, n = 42) = 4.061, p < .05); therefore hypothesis 1b. was supported. The

analysis revealed that the 51.9% of mock jurors believed the crime was a hate crime when

the victim was African-American and the defendant was Caucasian, in comparison to

20.0% who did not. However, when the victim was Caucasian and the defendant was

African-American, 48.1% of mock jurors believed the crime was a hate crime in

comparison to 80.0% who did not. This pattern of results suggests that the most notable

differences were in regards to when the defendant was Caucasian and the victim was

African-American. Further, the distribution of guilty verdicts suggests that when the

victim is African-American and the offender is Caucasian, mock jurors are inclined to

view this as more representative of a hate crime than when the offender is

AfricanAmerican and the victim is Caucasian. Please see table 3 for a review of the hate

crime verdicts. Table 3

Chi-Square Analysis for Hate Crime Verdicts – the Observed Counts vs. Expected Counts

Condition

Yes

1. Hate – BV/WD Count

% within Decision

51.9%

20.0%

2. Hate – WV/BD Count

% within Decision

48.1%

80.0%

Total

% within Decision

100.0%

n = 42

Upon completion of the chi-square analyses, the multivariate analyses were

computed. The goal was to asses whether type of crime (hate versus non-hate),

offendervictim racial composition (Caucasian/African-American), or the interaction

between these two variables influenced determinations of (1) likelihood of guilt

adjudication, (2) recommended sentence, and (3) punishment recommendations. These

analyses were separated by crime (aggravated battery and robbery) and conducted in two

stages. The first stage used type of crime and offender-victim racial composition as the

fixed factors and examined whether these factors or the interaction between them

influenced the above mentioned outcomes before controlling for dangerousness, witness

credibility, and hate motivation. As such, the first series of analyses employed a 2 x 2

Factorial Multivariate Analyses of Variance (MANOVAs), which is a test used to assess

the exerted influence of two fixed factors and their interaction on ratings of multiple

(more than one) dependent variables (outcomes). The second stage assessed the influence

of type of crime and offender-victim racial composition on guilt adjudication, deserved

punishment, and sentence recommendations after controlling for offender dangerousness,

witness credibility, and hate motivation. The second stage used of 2 x 2 Factorial

Multivariate Analyses of Covariance (MANCOVAs), which is a statistical analyses

employed to examine the influence two fixed factors and their interaction exert on

outcome variables after controlling for variables that have potential influence on the

outcomes. The objective for employing such a statistical technique was to assess whether

the experimental manipulations still exert influence on the outcomes after controlling

certain influential variables. Additionally the MANCOVAs were also conducted to

examine whether the covariates exerted any influence on the outcomes.

The first 2 x 2 Factorial MANOVA focused on whether there would be main

effects observed for type of crime (hate versus non-hate), offender-victim racial

composition (Caucasian/African-American), and the interaction between these variables

on ratings of likelihood the defendant committed aggravated battery and deserved

punishment. The objective was to examine the effects of the experimental manipulations

on the outcome variables before controlling for potential covarying factors (see Table 4

for descriptive statistics).

Table 4

Descriptive Statistics for Hate Crime Study Examining Type of Crime, Victim-Offender

Racial Composition, and Interaction Effects on Ratings of Likelihood of Guilt

Adjudication and Deserved Punishment for Aggravated Battery.

n = 83

The multivariate results showed that there were no significant main effects

observed for type of crime (multivariate F (2, 83) = 1.059, p > .05) or offender-victim

racial composition (multivariate F (2, 83) = 1.921, p > .05). However, the interaction was

significant (multivariate F (2, 82) = 5.205, p = .007). The multivariate F statistic

indicates whether the independent variables have any influence on any the outcomes. In a

MANOVA, there are multiple dependent variables. However, to further examine the

influence of the independent variable on each specific dependent variable in the model,

one must examine the between-subjects effects. In this first 2 x 2 Factorial MANOVA,

the test for between-subjects effects showed that the interaction effect was significantly

related to ratings of guilt likelihood for aggravated battery (F (1, 84) = 10.514, p = .002).

The R2 value was .11, which indicated that the interaction between type of crime and

offender-victim racial composition explained 11% of the variance for guilt likelihood for

aggravated battery. With respect to deserved punishment, the interaction was only

marginally significant (F (1, 84) = 3.441, p = .067). The R2 value was .04, which

indicated that the interaction between type of crime and offender-victim racial

Hate Crime

Condition

Race

Mean

Likelihood for Yes

BV/WD

6.19

2.04

Aggravated Battery Yes

WV/BD

7.46

1.96

BV/WD

7.12

2.13

WV/BD

5.19

2.89

Deserved Punishment Yes

BV/WD

4.94

3.15

Aggravated Battery Yes

WV/BD

4.93

3.24

BV/WD

5.32

3.11

WV/BD

2.90

2.23

composition explained 4% of the variance for guilt likelihood for aggravated battery. See

table 5 for details.

Table 5

2 x 2 Factorial MANOVA Summary Table for Hate Crime Study Examining Type of Crime,

Victim-Offender Racial Composition, and Interaction Effects on Ratings of Likelihood of

Guilt Adjudication and Deserved Punishment for Aggravated Battery.

Fixed Factor DV SS

Type of Crime Likelihood for 9.501

9.501

1.836

.02

Battery

Deserved

Punishment

14.190

1.598

.02

O-V

Likelihood

2.278

.440

.01

Race Comp.

Battery

Deserved

Punishment

31.304

3.525

.04

Crime*Race

Likelihood

54.421

10.514*

.11

Battery

Deserved

Punishment

30.565

3.441a

.04

n = 43

*p < .05

marginal significance approaching .05 significance level

As shown in the estimated marginal means (see Figure 1), the interaction was not

consistent with the expected direction as suggested in prior research. Specifically, in the

hate crime condition, the mean likelihood that the defendant committed the crime was

higher when the offender was African-American and the victim was Caucasian, compared

to when the offender was Caucasian and the victim was African-American. As noted in

the hypotheses, it was expected that there would be higher means for likelihood that the

defendant committed the crime when the victim was African American. In the non-hate

crime condition, the mean likelihood that the defendant committed aggravated battery

was higher when the offender was Caucasian and the victim was AfricanAmerican,

compared to when the offender was African-American and the victim was Caucasian.

Again, the hypothesis stated that when the crime was not labeled as a hate crime, higher

means would be observed when the victim was white.

The same series of analyses were conducted when examining the outcome of

sentence recommendations. Specifically, a 2 x 2 Factorial ANOVA was computed to

examine whether there were main effects observed for type of crime (hate versus

nonhate), offender-victim racial composition (Caucasian/African-American), and the

interaction between these variables on ratings of sentence recommendations for

aggravated battery. The purpose of computing this analysis separately was to examine the

recommended sentence only for those mock jurors that had found the defendant guilty for

aggravated battery (n = 41).

Figure 1. Estimated Marginal Means of Likelihood that the Defendant Committed

Aggravated Battery

The results demonstrated non-significant findings for main effects of type of

crime (F (1, 41) = 2.676, p = .110) and offender-victim racial composition (F (1, 41) =

0.663, p = .420), and the interaction between these two variables (F (1, 41) = 0.340, p =

.563) on ratings of recommended sentence for aggravated battery; this finding did not

support prior studies and hypothesis 5. See table 6 for details.

Table 6

2 x 2 Factorial ANOVA Summary Table for Hate Crime Study Examining Type of Crime,

Victim-Offender Racial Composition, and Interaction Effects on Ratings of Sentencing

Recommendations for Aggravated Battery.

Hate Crime Condition

Yes

8.0

7.5

7.0

6.5

6.0

5.5

5.0

Race of the Victim

Black

White

Fixed Factor DV

SS df

Type of Crime Years in Prison

For Battery

6.927 1

6.927

2.676

.06

O-V

Years in Prison

1.715 1

1.715

.663

.02

Race Comp.

For Battery

Crime*Race

Years in Prison For

Battery

.880 1

.880

.340

.01

n = 41 *p

< .05

The analyses examined thus far have asked and answered questions similar to

previous studies in hate crime and jury decision making research. However, those studies

did not control for factors such as dangerousness, hate motivation, and witness credibility

that may have impacted mock juror’s decision making on guilt adjudication, deserved

punishment, and sentencing. Thus, any significant findings may have been a function of

the covarying factors indicated above, as opposed to the independent effects of

offendervictim racial composition or labeling a crime as a hate crime.

The following MANCOVA was computed to determine whether there were main

effects observed for type of crime (hate versus non-hate), offender-victim racial

composition (Caucasian/African-American), and the interaction between these variables

on ratings of likelihood the defendant committed aggravated battery and deserved

punishment after controlling for perceptions of offender dangerousness, hate motivation,

and witness credibility (victim and police). The purpose of conducting this analysis was

to determine whether the offender-victim race manipulation, or the hate crime

manipulation, or a combination of both were truly impacting likelihood of guilt and

recommended punishment after controlling for the above mentioned variables.

Additionally, the analyses would examine whether dangerousness, hate motivation, and

witness credibility would exert a significant influence on the dependent variables. The

second hypothesis indicated that witness credibility would impact guilt likelihood, while

dangerousness and hate motivation would impact deserved punishment. The third and

forth hypothesis suggested that there would be no main effects observed for type of crime

and offender-victim racial composition on ratings of guilt likelihood, deserved

punishment, and sentencing recommendations. However the fifth hypothesis suggested

that there would be an interaction between type of crime and offender-victim racial

composition on ratings of guilt likelihood, deserved punishment, sentencing

recommendations after controlling for offender dangerousness, witness credibility, and

hate motivation. Specifically, for those conditions labeled as hate crimes, there would be

significantly higher means on the likelihood that the defendant committed aggravated

battery and deserved punishment when the victim was African-American and the

defendant was Caucasian. However, for those conditions that are not labeled as hate

crimes, there would be significantly higher means on the likelihood that the defendant

committed aggravated battery and deserved punishment when the victim was Caucasian

and the defendant was African-American.

The results of these analyses revealed that after controlling for dangerousness,

hate motivation, and witness credibility, there were no significant main effects observed

for type of crime (multivariate F (2, 76) = 0.083, p = .920), offender-victim racial

composition (multivariate F (2, 76) = 0.211, p = .810), and interaction effects between

these two variables (multivariate F (2, 76) = 2.305, p = .107) on ratings of guilt likelihood

and deserved punishment. These findings supported hypothesis 3 and 4.

However, they failed to support the hypothesis 5. Regarding the covariates, both victim

(multivariate F (2, 76) = .188, p = .829) and police credibility (multivariate F (2, 76) =

1.383, p = .257) were non-significant, thus not supporting hypothesis 2a. However, the

tests of Between-Subjects Effects showed that dangerousness significantly impacted

ratings of guilt likelihood (F (1, 77) = 43.577, p = .000) and deserved punishment (F (1,

77) = 17.214, p = .000). The R2 value indicated that dangerousness explained 36% of the

variance for guilt likelihood for aggravated battery and 18% of the variance for deserved

punishment. Additionally, hate motivation had a significant impact on ratings of

deserved punishment (F (1, 77) = 9.815, p = .002). The R2 value was .11, which

indicated that hate motivation explained 11% of the variance for deserved punishment for

aggravated battery. Therefore, hypothesis 2 b. and 2c. were supported. Although

dangerousness is a legally relevant factor for deserved punishment, it should not be

considered for guilt likelihood; however, the results suggested that dangerousness

impacted guilt likelihood, as well as deserved punishment. See table 7 for details.

Table 7

2 x 2 Factorial MANCOVA Summary Table for Hate Crime Study Examining Type of Crime, VictimOffender

Racial Composition, and Interaction Effects on outcome variables after controlling for dangerousness,

witness credibility, and hate motivation for Aggravated Battery.

Fixed Factor

F R2

Dangerousness

Likelihood

104.047

43.577** .36

Battery

Deserved

Punishment

85.943

17.314* .18

Hate Motivation Likelihood for .393

.393

.165

.00

Battery

Deserved

Punishment

49.004

9.815** .11

Victim

Likelihood for

.739

.310

.00

Credibility

Battery

Deserved

Punishment

.799

.160

.00

Police

Likelihood for

5.604

2.347

.03

Credibility

Battery

Deserved

Punishment

5.427

1.087

.01

Type of

Likelihood for

9.145E-02

.038

.00

Crime

Battery

Deserved

Punishment

.446

.089

.00

Offender-Victim Likelihood for .309

.309

.129

.00

Race Composition

Battery

Deserved

Punishment

.952

.191

.00

Crime*Race

Likelihood for

10.735

4.496

.37

Battery

Deserved

Punishment

4.440

.889

.01

n = 77;

*p < .05

**p < .01

Although the 2 x 2 Factorial ANOVA (presented above) demonstrated

nonsignificant findings related to sentencing, the Analysis of Covariance (ANCOVA) was

computed to examine whether dangerousness, hate motivation, and witness credibility,

were related to sentencing recommendations. Recall that sentencing was computed

separately to only examine those mock jurors that had found the defendant guilty for

aggravated battery (n = 35). In examining the results, dangerousness and witness

credibility were non-significant. However, hate motivation exerted a significant impact

on sentencing (F (1, 35) = 6.958, p = .012). This finding supported hypothesis 2c. The

R2 value was .17, which indicated that hate motivation explained 17% of the variance for

sentence recommendations for aggravated battery. See table 8 for details.

Table 8

2 x 2 Factorial MANCOVA Summary Table for Hate Crime Study Examining Type of Crime, VictimOffender

Racial Composition, and Interaction Effects on Sentencing after controlling for dangerousness, witness

credibility, and hate motivation for Aggravated Battery.

Fixed Factor

SS df

F R2

Dangerousness

Years in Prison For

Battery

8.208 1

8.208

3.722 .10

Hate Motivation

Years in Prison For

Battery

15.345 1

15.345

6.958* .17

Victim

Years in Prison

.497

.225

.00

Credibility

For Battery

Police

Years in Prison

.227

.103

.00

Credibility

For Battery

Type of

Years in Prison

.197

.089

.00

Crime

For Battery

Offender-Victim

Years in Prison

3.657

.017

.00

Race Composition

For Battery

Crime*Race

Years in Prison For

Battery

.927

.421

.01

n = 35 *p

< .05

Similar analyses were undertaken for the robbery charge variable. The goal was

to asses whether there would be main effects observed for type of crime (hate versus

nonhate), offender-victim racial composition (Caucasian/African-American), and the

interaction between these variables on ratings of (1) likelihood of guilt adjudication, (2)

recommended sentence, and (3) punishment recommendations for robbery. The first

analysis computed was a 2 x 2 Factorial MANOVA to examined mean differences in

ratings of guilt adjudication and deserved punishment as a function of type of crime,

offender-victim racial composition, or the interaction of the two variables for robbery

before controlling for deserved punishment, witness credibility, and hate motivation (see

Table 9). Table

Descriptive Statistics for Hate Crime Study Examining Type of Crime, Victim-Offender

Racial Composition, and Interaction Effects on Ratings of Likelihood of Guilt

Adjudication and Deserved Punishment for Robbery.

Hate Crime

Condition

Race

Mean

Likelihood for

Yes

BV/WD

5.44

2.03

Robbery

Yes

WV/BD

6.58

2.66

BV/WD

5.24

2.98

WV/BD

4.38

2.69

Deserved Punishment

Yes

BV/WD

3.94

2.67

For Robbery Yes

WV/BD

4.19

3.37

BV/WD

4.20

3.35

No WV/BD 2.48 2.40 21

n = 83

The multivariate results showed that there were no significant main effects

observed for type of crime (multivariate F (2, 83) = 2.171, p = .121) offender-victim

racial composition (multivariate F (2, 83) = 1.423, p = .247), or an interaction effect

between these two variables (multivariate F (2, 83) = 1.593, p = .209) on ratings of

likelihood that the defendant committed robbery and deserved punishment. These

findings were not congruent with prior research, nor the hypotheses proposed for this

study. See table 10 for details on between-subjects effects.

Table 10

2 x 2 Factorial MANOVA Summary Table for Hate Crime Study Examining Type of Crime,

Victim-Offender Racial Composition, and Interaction Effects on Ratings of Likelihood of

Guilt Adjudication and Deserved Punishment for Robbery.

Fixed Factor DV SS

Type of

Likelihood 30.378

30.378

4.283

.05

Crime

Robbery

Deserved 11.205

Punishment

11.205

1.213

.01

O-V

Likelihood for .417

.417

.059

.00

Race Comp.

Robbery

Deserved 11.443

Punishment

11.443

1.238

.02

Crime*Race

Likelihood for 21.179

21.179

2.986

.03

Robbery

Deserved 20.760

Punishment

20.760

2.247

.03

n = 83 *p

< .05

A 2 x 2 Factorial ANOVA was computed to examine main effects of type of

crime, offender-victim racial composition, and the interaction between the two variables

on ratings of recommended sentence for robbery separately. The purpose of this analysis

was to examine the recommended sentence only for those mock jurors that had found the

defendant guilty of robbery (n = 37). The results demonstrated that there were

nonsignificant main effects for type of crime (multivariate F (1, 37) = 0.442, p = .510),

offender-victim racial composition (multivariate F (1, 37) = 0.01, p = .972), and

interaction effects between these two variables (multivariate F (1, 37) = 0.511, p = .479)

on ratings of recommended sentence (years in prison for robbery). See table 11 for the

between-subjects effects.

Table 11

2 x 2 Factorial ANOVA Summary Table for Hate Crime Study Examining Type of Crime,

Victim-Offender Racial Composition, and Interaction Effects on Ratings of Sentencing

Recommendations for Robbery.

Fixed Factor DV

SS df

Type of

Years in Prison

1.929 1

1.929

.442

.01

Crime

For Robbery

O-V

Years in Prison

5.344 1

5.344

.001

.00

Race Comp.

For Robbery

Crime*Race

Years in Prison For

Robbery

2.230 1

2.230

.511

.01

n = 37 *p

< .05

Despite the non-significant findings with respect to robbery, a 2 x 2 Factorial

MANCOVA was nonetheless performed to examine whether dangerousness, witness

credibility, and hate motivation were related to guilt likelihood and deserved punishment

for robbery. The second hypothesis indicated that the above mentioned covariates would

impact guilt likelihood and deserved punishment. Based on the preceding MANOVAs

(presented above), there was no reason to expect hypotheses three, four, or five would be

supported in the following MANCOVA.

The results indicated that the effect of witness credibility on likelihood of guilt

and deserved punishment was non-significant. However dangerousness (multivariate

F(2, 76) = 21.419, p = .000) and hate motivation (multivariate F(2, 76) = 3.755, p = .028)

were significant. The tests of Between-Subjects Effects showed that dangerousness

significantly impacted guilt likelihood (F (1, 77) = 40.745, p = .000) and deserved

punishment (F (1, 77) = 18.990, p = .000). The R2 value indicated that dangerousness

explained 35% of the variance for guilt likelihood for robbery and 20% of the variance

for deserved punishment. Additionally, hate motivation significantly impacted deserved

punishment (F (1, 77) = 6.136, p = .015). The R2 value indicated that hate motivation

explained 7% of the variance for deserved punishment for robbery. These findings did

not support hypothesis 2a.) that indicated that witness credibility would be significantly

related to guilt likelihood, however hypothesis 2b. and 2c. were supported, which

indicated that dangerousness and hate motivation would be significantly related to

deserved punishment. Although dangerousness is a legally relevant factor for deserved

punishment, it should not be considered for guilt likelihood; however, the results

suggested that dangerousness impacted guilt likelihood, as well as deserved punishment.

As expected, because of the null findings in the previously computed 2 x 2 Factorial

MANOVA, there were non-significant main effects observed for type of crime

(multivariate F (1, 77) = 1.371, p = .260), offender-victim racial composition

(multivariate F (1, 77) = .738, p = .481), and the interaction between these two variables

(multivariate F (1, 77) = .032, p = .969) on ratings of likelihood for guilt adjudication for

robbery and deserved punishment after controlling for dangerousness, hate motivation, and

witness credibility. Therefore the third and fourth hypotheses were supported; however the

fifth hypothesis was not supported. See table 12 for between-subjects effects.

The second 2 x 2 Factorial ANCOVA was computed to examine whether

dangerousness, hate motivation, and witness credibility were related to sentencing for

robbery. The hypothesis indicated that the dangerousness and hate motivation would

impact sentencing. Sentencing was computed separately to only examine those mock

jurors that had found the defendant guilty for robbery (n = 35). Interestingly, the results

did not support the hypothesis 2c.; the findings showed that hate motivation, and witness

credibility did not significantly relate to sentencing. However, hypothesis 2b. was

supported as the results showed that dangerousness was significantly related to sentence

recommendations for robbery (F (1, 35) = 8.618, p = .006). The R2 value was .20, which

indicated that dangerousness explained 20% of the variance for sentence

recommendations for robbery. As expected because of the null findings in the previously

computed 2 x 2 Factorial ANOVA, the results of these analyses supported the third and

fourth hypothesis, however the fifth hypothesis was not supported, illustrating that after

controlling for dangerousness, hate motivation, and witness credibility, there were no

main effects observed for type of crime (F (1, 35) = 0.240, p = .628), offender-victim

racial composition (F (1, 35) = 0.170, p = .683), and the interaction between the two

variables F (1, 35) = 0.010, p = .919) on ratings of sentencing recommendations for

robbery. See table 13 for between-subjects effects.

Table 12

2 x 2 Factorial MANCOVA Summary Table for Hate Crime Study Examining Type of Crime,

Victim-Offender Racial Composition, and Interaction Effects on outcome variables after

controlling for dangerousness, witness credibility, and hate motivation for Robbery.

Fixed Factor

F R2

Dangerousness

Likelihood

163.354

40.745** .35

Robbery

Deserved

Punishment

115.881

18.995** .20

Hate Motivation

Likelihood

9.028E-03

.002 .00

Robbery

Deserved

Punishment

37.432

6.136* .07

Victim

Likelihood

1.137

.284

.00

Credibility

Robbery

Deserved

Punishment

3.387

.555

.00

Police

Likelihood

5.947E-03

.001

.00

Credibility

Robbery

Deserved

Punishment

1.697

.287

.00

Type of Crime

Likelihood

7.643

1.906

.02

Robbery

Deserved

Punishment

.249

.041

.00

Offender-Victim

Likelihood

5.465

1.363

.02

Race Composition

Robbery

Deserved

Punishment

.262

.043

.00

Crime* Race

Likelihood

7.020E-04

.000

.00

Robbery

Deserved

Punishment

.330

.054

.00

n = 77

*p < .05

**p < .01

Table 13

2 x 2 Factorial ANCOVA Summary Table for Hate Crime Study Examining Type of Crime,

Victim-Offender Racial Composition, and Interaction Effects on Sentencing after

controlling for dangerousness, witness credibility, and hate motivation for Robbery.

Fixed Factor

DV SS

F R2

Dangerousness

Years in Prison34.614

For Robbery

34.614

8.618**.20

Hate Motivation

Years in Prison10.752

For Robbery

10.752

2.677 .07

Victim

Years in Prison3.226

3.226

.803

.02

Credibility

For Robbery

Police

Years in Prison.926

.926

.231

.00

Credibility

For Robbery

Type of

Years in Prison.962

.962

.240

.00

Crime

For Robbery

Offender-Victim

Years in Prison.682

.682

.170

.00

Race Composition

For Robbery

Crime*Race

Years in Prison4.195 For

Robbery

4.195 .010

.00

n = 35 **p<

.01

Overall, these findings suggested that some of the covariates were significantly

related to some of the outcomes. More specifically, witness credibility did not impact

guilt adjudication, deserved punishment, and sentencing. However dangerousness

impacted guilt adjudication and deserved punishment for both robbery and aggravated

battery. Additionally, hate motivation impacted deserved punishment for both aggravated

battery and robbery. Interestingly, hate motivation only impacted sentencing for

aggravated battery; no effect was observed for robbery. The results also demonstrated

that before controlling for the above mentioned covariates, there were no main effects

observed for type of crime (hate versus non-hate) and offender-victim racial composition

(Caucasian/African-American). While these null effects were predicted in the current

study, it was hypothesized that they would significantly interact. However, after including

the covariates in the model, the interaction effect on ratings of guilt likelihood was no

longer significant, contrary to the proposed hypotheses. There were no other interactions

observed for the other dependant variables (deserved punishment and sentencing

recommendations). Collectively, there was only partial support across the various

hypotheses in the current analysis, a pattern which will be discussed in greater detail in

the conclusions.

Supplemental Analyses

As indicated in the previous analyses, some of the hypotheses were not supported

in the current study. While prior studies had previously indicated that the race and hate

crime manipulations impacted guilt adjudication, deserved punishment, and sentencing,

these results were not observed in this study. In fact, after covariates were included in the

models, none of the manipulated variables, nor their interactions, were significantly

related to the outcomes. This was not only inconsistent with the hypotheses, but seems

inconsistent with the bivariate analyses. Specifically, there were significant differences in

the adjudication of guilt observed in the chi-square analyses. Although it was suspected

that the interaction between type of crime and victim-offender racial composition was

driving this, the multivariate analyses failed to support such a conclusion. In an effort to

further explore the data, and perhaps get some sense of what might have influenced mock

jurors’ decisions about guilt, a One-Way ANOVA was computed to determine whether

there were mean differences in perceptions of dangerousness and hate motivation across

the conditions.

The results showed a non-significant finding for dangerousness across the

conditions, indicating that perceptions of dangerousness did not vary across the

conditions. However, there were mean differences for hate motivation across the four

conditions (F (3, 87) = 3.299, p = .024). To further examine to which of the four groups

significantly differed from each other, Bonferroni pairwise comparison tests were

conducted. The results indicated that condition 1 (African-American victim/Caucasian

defendant; hate crime) and condition 4 (Caucasian victim/African-American defendant;

non-hate crime scenario) significantly differed from each other; thus, mock jurors were

more likely believe that the African-American victim was targeted because of hate

motivation when the defendant was Caucasian in the hate crime condition, in comparison

to when the victim was Caucasian and the defendant was African-American in the

nonhate crime condition. This is congruent with the suggested theories on stereotypes that

propose that the victim’s race and calling the crime a hate crime influenced mock juror’s

perception of hate motivation. All other pairwise comparisons for the hate motivation

were non-significant (see Table 14).

Table 14

Pairwise Group Comparisons of Hate Motivation Across Conditions

DV Comparison

Mean

Difference

Hate Motive Hate (BV/WD)

hate (WV/BD)

3.21

1.43

Inter-R (BV/WD)

2.85

1.43

Inter-R (WV/BD)

4.58*

1.48

Hate (WV/BD)

Hate (BV/WD)

-3.21

1.42

Inter-R (BV/WD)

-.36

1.28

Inter-R (WV/BD)

1.36

1.34

Inter-R (BV/WD)

Hate (BV/WD)

-2.85

1.43

Hate (WV/BD)

.36

1.28

Inter-R (WV/BD)

1.73

1.34

Inter-R (WV/BD)

Hate (BV/WD)

-4.58*

1.48

Hate (WV/BD)

-1.37

1.34

Inter-R (BV/WD)

-1.73

1.34

n = 87 P

< .05*

Chapter

Six

Discussion and Conclusion

The aim of this study was to examine the influence of labeling a crime as a hate

crime, the victim-offender racial composition, and their interaction on mock jurors’

perceptions and decision making. Specifically, the objective was to examine whether

there were main effects observed for the type of crime (hate versus non-hate),

offendervictim racial composition (Caucasian/African-American) and the interaction

between these two variables on ratings for guilt likelihood, how much punishment the

defendant deserved, and sentence recommendations after controlling potential covariates.

There were five broad hypotheses in this study. The first hypothesis stated that

differences in guilt and hate crime adjudications would emerge across the experimental

conditions. This hypothesis was based on previous research that had focused on the

influence of racial salience (Sommers & Ellsworth, 2000; Marcus-Newhall et al., 2002).

The second hypothesis indicated that dangerousness, hate motivation, and witness

credibility would exert significant influences as well. This second series of hypotheses

was important in that previous research has not included them as potentially covarying

factors when examining adjudication and sentencing outcomes. Thus, previous research

which has suggested racially salient crimes are reacted to differently may be misleading

to the extent that other factors (e.g., perceptions of dangerousness) are driving mock

jurors’ decision-making. The third and fourth hypothesis stated that there would be no

main effects observed for type of crime (hate versus non-hate) and offender-victim racial

composition (Caucasian/African-American) on ratings of likelihood the defendant

committed aggravated battery and robbery, how much punishment the defendant

deserved, and sentence recommendations. The fifth hypothesis suggested that there

would be an interaction between type of crime (hate versus non-hate) and offender-victim

racial composition (Caucasian offender/African-American victim versus

AfricanAmerican offender/Caucasian victim) on ratings of the likelihood the defendant

committed aggravated battery and robbery, how much punishment the defendant

deserved, and sentence recommendations. The statistical analyses used in this study

including descriptive statistics, correlations, Chi-Squares, 2 x 2 Factorial Multivariate

Analyses of Variance, and 2 x 2 Factorial Multivariate Analyses of Covariance.

First, correlational analyses were computed to determine whether the potential

covariates were correlated with the outcome variables. As expected, dangerousness, hate

motivation, and witness credibility (police and victim) were significantly related to

likelihood of guilt, how much punishment the defendant deserved, and sentencing. Thus,

these findings suggested that these factors were related to jurors’ decision-making, and

therefore should have been included in previous research. For the purposes of this study,

dangerousness, hate motivation, and witness credibility were included in the multivariate

analyses. The purpose for including these factors as covariates was to examine the true

independent effects of race or the hate crime manipulation on ratings of guilt likelihood,

how much punishment the defendant deserved, and sentencing recommendations.

However, attractiveness was not significantly related to any of the outcome variables.

Therefore, for the purposes of computing the multivariate analyses, attractiveness was not

included as a covarying factor. After establishing these relationships, I proceeded to

examine the several hypotheses suggested.

In the first hypothesis, I anticipated that there would be differences in adjudication

across cells in the experimental conditions. Specifically, it was expected that the

distribution of guilt adjudication for aggravated battery and robbery would significantly

vary across the four study conditions. Additionally, the distribution of hate adjudication

would significantly vary across the first two hate crime experimental conditions.

Although no specific a priori hypotheses were generated regarding the specific pattern of

results in these chi-square analyses, the general patterns appeared to be inconsistent with

what one might expect. For example, mock jurors appeared to render more guilty verdicts

to the African-American defendant in comparison to the Caucasian defendant in the hate

crime scenario for aggravated battery. Conversely, in the non-hate crime condition, mock

jurors rendered more guilty verdicts to the Caucasian defendant, in comparison to the

African-American defendant for aggravated battery. It is unclear as to exactly what may

have led to these general patterns, although the combined influence of the type of crime

and the victim-offender relationship would appear to be implicated. This conclusion is

consistent with the multivariate analysis of variance, which showed a positive interaction

effect between type of crime (hate vs. non-hate) and offender-victim racial composition

(African-American / Caucasian) on ratings of guilt likelihood. Additionally, the estimated

marginal means suggested a similar pattern to what was observed in the chi-square. Thus,

it appears that the interaction effect did have an impact on guilt adjudication for battery.

Importantly, however, this interaction was rendered non-significant after the inclusion of

the covariates.

The chi-square analysis for robbery was non-significant indicating that the

distribution of guilt adjudication across experimental conditions did not significantly

vary. It appears that this non-significant finding may have been a consequence of the

limited evidence available in the trial scenarios related to robbery. It is possible that if

there was more evidence that the defendant committed robbery – for instance, if the

stolen items were found in the defendant’s possession – it is plausible that guilt

adjudication for robbery would have also significantly varied across study conditions.

In addition to adjudications for guilt, I also asked mock jurors to adjudicate

whether or not they perceived those crimes labeled as hate crimes as actual hate crimes.

The results regarding this adjudication were quite interesting in that mock jurors were

more likely to adjudicate the crimes as hate crimes when they conformed to stereotypical

views of what constitutes a hate crime. For instance, statistics show that Caucasians are

generally perpetrators of hate crimes and African-Americans are most frequently victims

of hate crimes. Such occurrences create stereotypes that result in people commonly

believing that hate crimes are generally committed by Caucasians against

AfricanAmericans (Craig et al., 1999; Saucier et al., 2006; Gerstenfeld, 2003; Marcus-

Newhall et al., 2002). Interestingly, the results indicated that more mock jurors believed

the crime was a hate crime when the victim was African-American and the defendant was

Caucasian, in comparison to when the victim was Caucasian and the defendant was

African-American. This observed result is congruent with prior suggestions that hate

crimes are stereotypically viewed as crimes against African-Americans (Craig et al.,

1999; Saucier et al., 2006; Gerstenfeld, 2003; Marcus-Newhall et al., 2002).

The second series of hypotheses indicated that dangerousness, witness credibility,

and hate motivation would be related to guilt adjudication, ratings of how much

punishment the defendant deserved, and sentencing recommendations. The results

suggested that some of these hypotheses were supported, while others were not. First, I

expected that perceptions of witness credibility (police and victim) would be significantly

related to ratings of the likelihood that the defendant committed aggravated battery and

robbery. Interestingly, the results suggested that witness credibility did not impact guilt

adjudication, how much punishment the defendant deserved, and sentencing. While

witness credibility should be a legally relevant factor taken into consideration in criminal

cases, the results suggested that it did not have any influence on the outcomes. This null

finding may be explained by evidence strength. Perhaps the testimony provided by both

the police and victim in the crime scenarios was perceived as being weak by mock jurors,

and thus inconsequential in affecting guilt adjudication, how much punishment the

defendant deserved, and sentencing.

Second, it was hypothesized that perceptions of offender dangerousness would be

significantly related to sentence recommendations and how much punishment the mock

jurors believed the defendant deserved for aggravated battery and robbery. As expected,

the results indicated that dangerousness impacted how much punishment the defendant

deserved and sentence recommendations for both robbery and aggravated battery crimes.

Dangerousness accounted for approximately 18% of the variance for perceptions of

deserved punishment. Additionally, dangerousness accounted for 10% and 20% of the

variance for sentencing recommendations for aggravated battery and robbery

respectively. The findings also suggested that dangerousness influenced guilt likelihood

for aggravated battery and robbery. Dangerousness explained approximately 35% of the

variance for likelihood for battery and robbery. It emerged that dangerousness seemed to

have accounted for a considerable amount of variance for both crimes. While

dangerousness is a legally relevant factor for sentencing recommendations and how much

punishment the defendant deserved, it appeared that dangerousness was an influential

factor that also impacted guilt adjudication. This suggests that mock jurors associated

perceptions of offender dangerousness with guilt culpability.

Finally, the hypothesis suggested that perceptions of hate motivation would be

significantly related to recommendations for severity of punishment for aggravated

battery and robbery. As expected, the findings suggested that hate motivation impacted

how much punishment the defendant deserved for both aggravated and robbery crimes.

Additionally, hate motivation accounted for 11% and 7% of the variation for aggravated

battery and robbery respectively. Interestingly, however, hate motivation only impacted

sentencing for aggravated battery and accounted for 17% of the variation; no effect was

observed for robbery. The non-significant finding for hate motivation’s impact on

sentencing for robbery may have been related to the nature of the crime and the

availability of evidence. That is, mock jurors may have perceived aggravated battery as a

crime stereotypically motivated by hate. However, the robbery may have not been

considered to be motivated by racial animus. Additionally, the scenario focused on

evidence related to the aggravated battery, however there was very limited evidence in the

case that suggested that robbery took place; for instance, there was very little mention

about robbery in the crime scenario and there was no indication that the stolen property

was found in the defendant’s possession. As such, this weak evidence may have impacted

the outcomes.

The final series of hypotheses suggested that there would be no main effects

observed for type of crime (hate versus non-hate) and offender-victim racial composition

(Caucasian/African-American) on ratings of likelihood the defendant committed

aggravated battery and robbery, how much punishment the defendant deserved, and

sentence recommendations. As predicted, the 2 x 2 Factorial Multivariate Analyses

revealed that there were no significant main effects observed. Therefore, this finding

suggests that the type of crime alone (hate versus non-hate) and the offender-victim racial

dyad alone (African-American/Caucasian) did not impact how much punishment the

defendant deserved, guilt likelihood, and sentencing recommendations.

The final series of hypotheses also suggested that there would be an interaction

between type of crime (hate versus non-hate) and offender-victim racial composition

(Caucasian offender/African-American victim versus African-American

offender/Caucasian victim) on ratings of the likelihood the defendant committed

aggravated battery and robbery, how much punishment the defendant deserved, and

sentence recommendations. Specifically, for those conditions labeled as hate crimes,

there would be significantly higher means on likelihood for committing both crimes,

sentence recommendations, and how much punishment the defendant deserved when the

victim was African-American and the defendant was Caucasian (compared to when the

victim was Caucasian and the defendant was African-American). Conversely, for those

conditions labeled as non-hate crimes, there would be significantly higher means on

likelihood for committing both crimes, how much punishment the defendant deserved,

and sentence recommendations when the victim was Caucasian and the defendant was

African-American (compared to when the victim was African-American and the

defendant was Caucasian). A 2 x 2 Factorial MANOVA revealed that there was an

interaction effect on ratings of likelihood that the defendant committed aggravated battery

before controlling for the covariates in the model. This interaction demonstrated that the

crime label and racial dyad did interact. However, the interaction demonstrated that in

the hate crime condition, the mean likelihood that the defendant committed the crime was

higher when the offender was African-American and the victim was

Caucasian, compared to when the offender was Caucasian and the victim was

AfricanAmerican. These outcomes were not consistent with the direction predicted in the

hypothesis for hate crimes. A plausible suggestion to this outcome may be related to

some criticisms that have been suggested for hate crime legislation. Some researchers

have suggested that hate crime laws may have an adverse affect on minority group

members (Jacobs & Potter, 1997). For instance, African-Americans may receive harsher

sentences for committing a hate crime against a member of the majority group

(Caucasians) as research has shown a trend whereby minority group members receive

harsher sentences than members of the majority groups (Saucier et al., 2006; Gerstenfeld,

2003). The results in this study suggest that this criticism may be plausible.

Conversely, the results indicated that in the non-hate crime condition, the mean

likelihood that the defendant committed aggravated battery was higher when the offender

was Caucasian and the victim was African-American, compared to when the offender was

African-American and the victim was Caucasian. This outcome was also not congruent

with the direction predicted in the hypothesis. A potential reason for this outcome could

have been that students may have realized that the study was exploring the potential

impact of race on juror decision making. The students may have been aware of known

race-related imprisonment issues that suggest that African-Americans are more frequently

found guilty of crimes and receive harsher sentences (Clear, 1994). Consequently guilt

likelihood was increased in the opposite direction where Caucasians were more likely to

be guilty when the victim was African-American, in comparison to the African-American

defendant when the victim was Caucasian. Interestingly, however, after controlling for

offender dangerousness, witness credibility, and hate motivation, the interaction effect

disappeared. Therefore, the significant interaction between type of crimes (hate/non-

hate) and offender-victim racial composition (African-

American/Caucasian) on ratings of guilt likelihood may have been a function of the

covariates indicated above. Thus, prior research that has suggested differences in

adjudication and sentencing in hate crimes may have been inaccurate as the findings may

have been a function of other potentially covarying factors.

The series of 2 x 2 Factorial MANCOVAs revealed that after controlling for

dangerousness, witness credibility, and hate motivation, there were no observed main

effects of type of crime and offender-victim racial composition, and there were no

interaction effects between these two variables on ratings of likelihood the defendant

committed aggravated battery and robbery, how much punishment the defendant

deserved, and sentencing recommendations. The results of the main effects were

congruent with the hypothesis in this study; however the interaction effects observed

were not. While the hypotheses in this study suggested significant differences across

groups because of the victim-offender racial composition and hate crime label

manipulation, this was not supported with these results, and was not congruent with prior

hate crime research studies (Craig et al., 1999; Saucier et al., 2006; Gerstenfeld, 2003;

Marcus-Newhall et al., 2002). Prior researchers have suggested that race and the hate

crime manipulation influenced adjudication and sentencing. However, the important note

to consider is that prior researchers have not controlled for potential covarying factors

that influence these outcomes. As such, the significant results found in prior research

may have essentially been a function of the covarying factors, not the actual race or hate

crime manipulation. The current study focused on controlling for potential covarying

factors that have been suggested to influence adjudication and sentencing. The main

effect effects and interactions did not impact the outcomes; rather, it appeared that

offender dangerousness and hate motivation were influential factors in this case. Witness

credibility remained constant across the conditions as there was no significant variation

observed, suggesting that witness credibility did not influence mock jurors perceptions of

adjudication and sentencing depending on which condition they were assigned to.

Although, it is important to note that dangerousness did influence guilt likelihood, this

factor should not be a legally relevant factor considered by jurors in assessing guilt.

Since we found that mock jurors in this study focused on offender dangerousness

and hate motivation, there was further interest to determine whether these factors differed

across the conditions. There was a possibility that perhaps calling a crime a hate crime

alters perceptions of offender dangerousness or perceptions of hate motivation. Or the

race of the victim impacts whether the crime is perceived as being motivated by hate.

While this hypothesis was not suggested in this study, to further analyze the results, a

One-Way ANOVA was computed to determine mean differences for dangerousness and

perceived hate motivation across the conditions. The results showed that perceptions of

dangerousness did not vary across the conditions. However, the results showed that

mock jurors were more likely to believe that the African-American victim was targeted

because of hate motivation when the defendant was Caucasian in the hate crime

condition, in comparison to when the victim was Caucasian and the defendant was

African-American in the non-hate crime condition. Therefore, this suggests that the

victim’s race and calling the crime a hate crime influenced mock juror’s perception of

hate motivation. This is congruent with the notion that there are stereotypes about what a

hate crime is (Craig et al., 1999; Saucier et al., 2006; Gerstenfeld, 2003; Marcus-Newhall

et al., 2002). Specifically, it appears that the stereotype of a hate crime is one in which

there is an African-American victim and a Caucasian offender.

While interesting results emerged in this study, the results were not congruent

with prior hate crime research. Several reasons may explain the outcomes observed in the

current study. Perhaps the inconsistent results obtained in the study were impacted by

specifically labeling crimes as hate crimes, or the inclusion of multiple victim-offender

racial dyads. Other research has not typically created such unique experimental

conditions, and those in turn may have influenced the results. Perhaps it was something

about they way the crime was described in the trial scenario that impacted the results.

These are all possibilities; however it remains unclear as to why they seem contrary to

prior research.

Another consideration for why these results emerged may have been related to the

sample. The study was selected from undergraduate criminology students. Criminology

classes focus on issues related to extralegal factors (such as race), imprisonment, and

other legal issues. Such factors may have played a role in mock juror’s considerations for

likelihood of guilt, how much punishment the defendant deserved, and sentence

recommendations because of the sensitivity regarding shockingly high imprisonment

rates in the last 30 years (Clear, 1994). As a result, mock jurors in this study sample may

have been less likely to adjudicate the defendants guilty, less likely to believe they

deserved punishment, and decreased recommended sentences in comparison to a sample

of non-criminology students or community samples. This may be indicative of prior

studies that have found significant results related to increased adjudication and sentencing

for Caucasian perpetrators for hate crimes in comparison to African-American

perpetrators as the samples used were non-criminology student samples, such as

psychology student samples or community samples (Craig et al., 1999; Saucier et al.,

2006; Gerstenfeld, 2003; Marcus-Newhall et al., 2002).

A final consideration may be that the evidence presented for robbery negatively

impacted the outcomes in this study. The crime scenario focused on evidence related to

aggravated battery. There was very limited information provided for the robbery. In

particular, no information was provided that indicated whether belongings were found in

the defendant’s possession. Given that the primary factor related to jurors’ decision is the

strength of evidence (Sargent & Bradfield, 2004), and the evidence regarding burglary

was admittedly weak, the nonsignificant findings regarding robbery may have been

appropriate.

In summary, the current study revealed some very interesting findings that added

to existing literature. Essentially, what this body of research previously suggested prior to

this study was that race was a factor that influenced adjudication and sentencing. In race

and jury studies, prior researchers have suggested that African-Americans tend to be

found guilty more frequently and receive harsher sentences. However, when race is made

salient, mock jurors tend to pay attention to legally relevant details of the case. In hate

crime and jury research, when race is made salient, prior researchers have suggested that

mock jurors tend to be more punitive towards Caucasian perpetrators of hate crimes when

the victim is African-American. What had not yet been examined prior to this study was

whether these patterns hold when covariates that may modify the findings are controlled

for. For the purposes of this study, hate motivation (which was a combination of whether

the victim was targeted because of race and the defendant’s perceived prejudice), witness

credibility (police and victim) and dangerousness (which was a combination of the

defendant’s perceived aggressiveness and likelihood of future crime) were controlled for,

as prior research has suggested that these factors influence adjudication and sentencing.

The results of this study found no differences in mock juror’s decisions about how much

punishment the defendant deserved, and sentence recommendations before and after

holding all the covariates constant. However, there was a significant interaction between

type of crime and offender-victim racial composition observed on ratings of guilt

likelihood for aggravated battery only (nonsignificant for robbery) before controlling for

the covariates in the model. Conversely, after controlling for offender dangerousness,

witness credibility, and hate motivation the interaction effect disappeared. Thus, it

appears that while prior researchers have suggested that race is a factor, the present study

suggests that mock jurors are not influenced by race. This outcome in the study is a

positive and important outcome to note. In fact, the influential factors on guilt

adjunction, how much punishment the defendant deserved, and sentencing appeared to be

the covarying factors such as dangerousness and hate motivation.

Some flaws were identified in this study. First and foremost, some sampling

issues were noted. The sample was not diverse, as 66.7% of mock jurors were Caucasian.

There were less than 25 participants in each condition, indicating that the sample size was

small. The sample selected was comprised of college students. While numerous

researchers use college student samples, it decreases external validity (Sommers &

Adekanmbi, 2008). Sampling is an important component for consideration for future

research. Specifically, researchers should focus on more diverse and larger sample sizes.

Since the African-American population in the United States is lower than the Caucasian

population, it is likely that a diverse sample will be difficult to obtain. Therefore, future

researchers should focus on obtaining a survey that is stratified to include more diverse

samples. Additionally, samples should be selected from an actual jury pool in order to

increase external validity.

There is very limited research in the area of hate crimes and jury decision making.

Thus, it is necessary to continue conducting further studies to examine juror’s perceptions

of hate crimes to increase knowledge in this area. One consideration for future research

involves strength of presented evidence. Prior researchers have noted differences in

adjudication and sentencing depending on evidence strength (Sargent & Bradfield, 2004).

In the current study, the percentage of guilty adjudications was approximately 50%. This

suggests that the evidence was ambiguous as intended. However, a more sophisticated

design could include varying levels of strength of evidence, an approach future

researchers should consider.

Despite the limitations, this study adds to the literature as key covarying factors

were identified, such as offender dangerousness and hate motivation. These covariates

were influential on ratings of guilt adjudication, perceptions of how much punishment the

defendant deserved, and sentence recommendations. Because prior studies have not

taken into account such factors, some of the findings stemming from them may be

misspecified. We encourage future efforts to examine these and other potential

covariates, as they appear to be important. To the extent that the current findings are

replicated, it may reveal that race is less influential than previously thought. This would

be an encouraging finding as jurors are charged with carrying out their duties in an

impartial, and thus racially neutral, manner.

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