Effect of Minimal Group Bias on Memory and Attitudes

Running head: EFFECT OF MINIMAL GROUP BIAS ON MEMORY 1
The Effect of Minimal Group Bias on Memory and Attitude Over Time
Grace Monks
Cornell University

EFFECT OF MINIMAL GROUP BIAS ON MEMORY 2
Abstract
The current experiment tested the hypothesis that adult participants’ membership in
randomly assigned “minimal groups” would be sufficient to induce intergroup bias.
Adults were randomly assigned to orange, green, or yellow groups and listened to stories
about unfamiliar in-group and out-group adults. Participants were more likely to report
negative events than positive events in free recall assessments, but were more accurate
about positive events than negative events in recognition memory assessments. Despite
support for the hypothesis from previous work, no significant in-group preferences were
observed on explicit and implicit measures of attitude or memory of stories. Despite
limitations, findings provide potential knowledge about the reliability of witness
testimony and their susceptibility to ingroup-outgroup bias.
Keywords: minimal groups, ingroup-outgroup bias, memory, attitude

The Effect of Minimal Group Bias on Memory and Attitude Over Time
Every day, individuals rely upon associations between themselves and others to
make conscious and unconscious decisions. Individuals have a tendency to see
themselves as either part of an ingroup or part of an outgroup. Ingroup associations can
have a lasting effect on the way we perceive others. The social identities that we ascertain
have the power to shape social cognition (Van Bavel & Cunningham, 2011). Ingroup
associations play a powerful role in the memories we have about ingroup and outgroup
members (Tajfel, Billig, Bundy, & Flament, 1971). Exactly how small association this
needs to be is the question we seek to answer.
Group Associations in the Context of Memory
The group that we ascribe ourselves to can impact our memory for people and
events. For example, many researchers have shown that people from various racial
identities show better recognition memory for faces of their own race than faces of
another race (Malpass & Kravitz, 1969). The field of social psychology has deemed this
phenomenon own-race bias (Malpass & Kravitz, 1969). Similarly, people tend to report
other-race faces as looking alike but seeing same-race faces as individuals (Malpass &
Kravitz, 1969; Meissner & Brigham, 2011). This is called the out-group homogeneity
effect - the tendency for people to see ingroups as heterogeneous and outgroups as
homogeneous. The potential consequences of this phenomenon are concerning, such as
wrongful convictions based on eyewitness testimony (Brigham & Ready, 1985).
Social Categorization as a Cause of Ingroup Bias
In the past few decades there has been a push towards discovering the cause of
ingroup-outgroup bias. Researchers have investigated social categorization as an

explanation of both racial and minimal group biases (Hugenberg & Sacco, 2008; Levin,
1996; Sporer, 2001). The theory is that when an individual encodes a face, he
immediately categorizes the individual as an ingroup member or an outgroup member.
The faces of ingroup members spark a deeper and different type of processing compared
to those of outgroup members. Ingroup members are viewed more as individual entities,
while outgroup members are viewed as part of a social category (Sporer, 2001). Despite
the arbitrary nature of the social categories, this categorizing process is enough for
individuals to create an ingroup bias in face memory (Bernstein, Young, & Hugenberg,
2007).
Van Bavel, Swencionis, O’Connor, and Cunningham (2011) further added to
this social categorization theory. In one study, the researchers examined social identity
and its impact on memory and social attention. Participants that tended to identify most
highly with their ingroup had the largest degree of outgroup bias (Van Bavel, Packer, &
Cunningham, 2011). In a further investigation of this phenomenon, the researchers
showed that social belonging needs were a strong force behind ingroup-outgroup biases.
Specifically, participants who indicated a higher need to belong showed greater ingroup
bias in the memory tasks and participants that were more socially excluded also showed
greater ingroup bias in the memory tasks (Van Bavel et al., 2011).
Hartstone & Augoustinos (1995) depart from simple social categorization
theory. These researchers suggest that the minimal group effect relies on dichotomous
categorization, or the use of two minimal groups. They discovered that adults display
ingroup bias with two minimal groups but do not display the bias in a three-group context
(Hartstone & Augoustinos, 1995). Spielman (2000) supported this; he duplicated the two-

group versus three-group results but also found that adults will show ingroup bias in a
three-group context when competitively primed (Spielman, 2000). Both studies support
the theory that the competitive nature of dichotomous categorization leads to ingroup bias
in minimal groups.
Minimal Groups
Researchers have shown that this ingroup bias occurs across many different
groups. Dating back to the 1970s, Tajfel and other researchers investigated the minimum
requirements necessary to lead to ingroup discrimination. This group of researchers
created what is now known as the minimal group paradigm: They attempted to create a
situation so free of psychological meaning that ingroup bias would be prevented. What
they found was that despite an arbitrary distinction, ingroup bias still persisted. For
instance, in a resource allocation experiment participants were more likely to favor those
in their ingroup even though it was based on completely arbitrary distinctions (Tajfel,
Billig, Bundy, & Flament, 1971).
Minimal groups share a much less significant relationship than race and are often
created using something as insignificant as a color of shirt or a team name, both randomly
assigned and with pre-experimental associations. The results of many studies suggest that
newly learned and arbitrary group associations can still lead to the memory-altering bias
seen with racial groups (Bernstein, Young, & Hugenberg, 2007; Van Bavel, Packer, &
Cunningham, 2008). Superior recognition memory is seen in ingroups despite the groups
being arbitrary and recent (Bernstein, Young, & Hugenberg, 2007). No stereotype-
inducing measures, prior conflict, or competition for resources is needed to induce the
ingroup-outgroup differentiation (Tajfel, 1970).

The effects of experimentally created minimal groups can even be so powerful
as to override other factors. In one study where the minimal group paradigm was induced,
participants tended to show more ingroup bias toward the minimal group, regardless of
the race of its members. Many researchers believe that these differences in memory for
ingroup and outgroup members are caused by the way in which those individuals and the
actions associated with them are originally encoded (Van Bavel & Cunningham, 2011).
The precise differences in how they are encoded require further investigation.
Furthermore, in a study conducted by Otten and Moskowitz (2000), participants
demonstrated positive affect toward novel, randomly-assigned ingroup members; the
results demonstrated that participants were more likely to categorize an ingroup member
with a positive trait than a negative trait (Otten & Moskowitz, 2000). Additionally,
participants were more likely to assign these positive traits to ingroup members than to
outgroup members. The researchers did not examine this effect on memory or other
assessments (Otten & Moskowitz, 2000).
Assignment in the Minimal Group Paradigm
Researchers have created experimentally created minimal groups in a variety of
ways. Often, participants are told that they belong to a certain group or team. For
example, Spielman (2000) utilized circle, square, and triangle tokens to assign
participants to the circle, square, or triangle groups. In another study, Dunham, Baron,
and Carey (2011) gave participants colored tokens and matching colored t-shirts to create
minimal groups. In this study, the researchers examined explicit attitudes, resource
allocation, behavioral attribution, implicit attitudes, and expectations of reciprocity, but
they did not examine memory-related assessments. The study was conducted with

children and the results demonstrated that ingroup biases affected all measures, including
explicit attitudes, resource allocation, behavioral attribution, implicit attitudes, and
expectation of reciprocity (Dunham, Baron, and Carey, 2011).
The Current Study
One notable gap in the literature has to do with the manner in which ingroup-
outgroup status affects behavioral predictions. No known study to date has examined how
minimal group associations affect behavioral inferences over time. The current study
seeks to close this gap. This information could shed light on the behavioral attributions
individuals make in the face of little external information. Behavioral inferences, in
addition to memory, were measured at two time points to examine how these measures
change over time.
The current study utilized the same paradigm as Dunham, Baron, and Carey
(2011) but examined the impact of minimal group membership on memory, explicit
liking, and behavioral attributions across time in undergraduate students. The aim of the
study was to explore the minimal group paradigm with undergraduates not only in the
context of memory, but in trait and behavioral predictions as well.
It was hypothesized that ingroup biases stemming from minimal group
associations would lead participants to recall their ingroup members more positively and
outgroup members more negatively. Specifically, it was posited that participants would
more accurately recall positive ingroup actions than positive outgroup actions and would
more accurately recall negative outgroup actions than negative ingroup actions.
Additionally, it was hypothesized that participants would evaluate ingroup members
more favorably during explicit liking and behavioral attribution assessments.

Methods
Participants
The participants in this study consisted of 56 adults (69.6% female).
Undergraduate students were recruited through the Cornell University psychology
experiment online sign-up system. Participants from the community were also recruited
through email. Adults ranged from 18-37 years of age (M = 19.92, SD = 2.63). The racial
makeup consisted of 42.9% Caucasian, 28.6% Asian, 16.1% Hispanic, and 12.5%
African American. All participants had at least some college. Three participants were
excluded from the analysis after they mentioned they had previous knowledge of the
stimuli presented. Cornell undergraduates received extra credit for their participation
while participants from the community were entered into a raffle to win a gift card.
Design
The current study examined the impact of ingroup-outgroup membership on
memory, explicit liking, and behavioral attribution. Ingroup-outgroup membership was
manipulated through the use of t-shirt color. Participants were randomly assigned to one
of three t-shirt colors: orange, green, and yellow. The orange and green groups served to
elicit ingroup-outgroup membership while the yellow group served as a control. The
dependent variables included memory for people and events and trait assessments. These
dependent variables were measured immediately (time 1) and one week after (time 2) the
stimuli was presented.
Stimuli
All stimuli and time 1 questionnaires were presented in person. With the
assistance of a research assistant, all content was presented on a laptop computer via

Qualtrics, an online survey tool. Stimuli consisted of 16 still frames of eight adult
volunteers (50% female) (see Appendix A). These adult volunteers ranged from 19-22
years of age (M = 20.25, SD = .89). Each volunteer was photographed twice - once in an
orange t-shirt and once in a green t-shirt. The volunteers had hair pulled back and wore
no makeup. Each participant viewed eight still frames (two females in orange t-shirts,
two females in green t-shirts, two males in orange t-shirts, and two males in green t-
shirts). Color and volunteer were counterbalanced so that for each volunteer, 50% of
participants saw that person in an orange t-shirt, and 50% of volunteers saw that person in
a green t-shirt. As each still frame appeared on Qualtrics survey tool, a research assistant
read one good story or one bad story about the individual shown. Good stories included
positive actions such as sharing food with coworkers, picking up trash in a park, donating
clothes, and picking up dropped papers. Bad stories included negative actions such as
tripping another person, stealing a computer, breaking into a professor’s office, and
throwing water in a coworker’s face. There were a total of eight stories between 33 and
48 words (Appendix B). Stories and still frames were counterbalanced to create four
surveys.
Measures
Memory assessments. The memory assessment consisted of two parts. The first
part involved a free recall task. The research assistant asked open-ended questions such
as, “Tell me everything you can remember about the stories you just heard.” As the
participant responded, the research assistant recorded the information. The second part
consisted of eight multiple-choice questions. Participants were presented with one still
frame at a time and asked, “Which action did this person commit?” The answer options

consisted of all eight actions described in the stories (e.g., “This person stole a
computer”, “This person shared food with others”). The research assistant inputted all
responses into the survey tool (see Appendix C).
Liking assessments. The trait assessment consisted of two parts. The first part-
the explicit liking assessment- involved a series of eight questions. Here, participants
were presented with a still frame of a novel individual wearing either an orange or a
green t-shirt (Appendix D). The new still frames were adult volunteers (50% female).
These adult volunteers ranged from 19-20 years of age (M = 19.88, SD = .35). The new
still frames were photographed in the same manner as the previous eight stimuli still
frames. As the still frame was presented, participants were asked. “How much do you
like this person?” and indicated liking on a 4-point Likert scale. The 4 options included
“1-dislike very much”, “2-dislike moderately”, “3-like moderately”, and “4-like very
much” (see Appendix E).
The second part- the behavioral attribution assessment- involved eight more
questions. Participants were presented with still frames from the second volunteer group
described above and asked, “Please pick one adjective that describes this person.”
Answer choices included “friendly”, “nice”, “smart”, “considerate”, “mean”, “selfish”,
“unfriendly”, and “rude” (see Appendix F).
Procedure
Group assignment. Participants performed the experimental tasks individually.
Participants were instructed to pick a token out of a bag that was said to include green,
orange, and yellow tokens. However, unbeknownst to them, three different bags existed
with entirely green, orange, or yellow tokens. Thus, participants were pre-assigned to a t-

shirt color and pulled a token out of the corresponding bag filled with that color. After
pulling a token, participants were given a t-shirt of the same color and instructed to wear
the t-shirt for the duration of the experiment. Twenty-one participants were in the orange
group, 19 participants were in the green group, and 16 participants were in the yellow
group.
Time 1. Color assignment occurred at time 1. After putting on the t-shirt,
participants were told that they would hear a series of stories and were instructed to look
at the accompanying photos. As the research assistant read the story for each action,
he/she presented the associated photo of the person alleged to have performed it. The
photo presented along with each story was randomized to account for latency and recency
effects as well as individual differences among the photos. After the stimuli were
presented, participants entered a unique participant identification number into Qualtrics.
This identification number was used to connect participants’ Time 1 and Time 2 survey
results. Next, participants were asked to answer some questions about what they saw and
heard. The first task completed was the memory assessment. Participants first were asked
to tell the research assistant everything they remembered from the stories. They were then
asked to recall anything positive the people mentioned did and anything bad the people
mentioned did. Next, the participants were asked the eight specific questions, “What
action did this person commit?”
After the memory assessment was completed, participants completed the trait
assessment. Participants first answered the eight Likert scale questions and then answered
the eight adjective questions instructing them to, “Please pick one adjective that describes
this person.” After the trait assessment, the research assistant thanked the participants and

told them they would receive a survey consisting of the second part of the study via email
in one week.
Time 2. Participants received a survey one week later via email. The survey consisted
of the same memory assessment and trait assessment utilized in Time 1. Participants
completed the recognition memory assessment first, followed by the explicit liking
assessment, and finally the behavioral attribution assessment. After all assessments,
participants were debriefed.
Results
Free-Recall Memory
The mean number of positive events recalled was compared with the mean
number of negative events recalled through a dependent t-test. The analysis revealed a
tendency to remember more negative actions (M = 2.91, SD = .78) than positive actions
(M = 2.55, SD = .86, p < .001). Mean free-recall memory rates for positive and negative
actions are presented in Figure 1.
Figure 1. Free recall as a function of action valence (positive and negative) expressed as

the mean number of actions recalled (of four total actions for each valence).
Recognition Memory
Accuracy for actions was analyzed using a repeated measures analysis of
variance with three within-participant factors (Time: Time 1 vs. Time 2 x Group: Ingroup
vs. Outgroup x Valence: Positive vs. Negative actions). This analysis revealed a tendency
to recall more accurate actions at time 1 compared to time 2 (p < .001). There was also a
slight tendency to recall more accurate ingroup actions than outgroup actions (p = .32).
Furthermore, there was a slight tendency to recall more accurate positive outgroup
(M = 1.47, SD = .65) than positive ingroup actions (M = 1.36, SD = .76) at time 1. At
time 2, this trend reversed: Participants recalled more accurate positive ingroup actions
(M = .78, SD = .59) than positive outgroup actions (M = .64, SD = .64). These tendencies
are displayed in Figure 2.
Figure 2. Recognition memory for positive actions as a function of time (time 1 and time
1) and group (ingroup and outgroup) expressed as the mean number of actions accurately
recalled (for a total of four actions).
Lastly, as displayed in Figure 3, there was a slight tendency for participants to recall
more accurate negative ingroup actions (M = 1.31, SD = .71) than negative outgroup

actions (M = 1.19, SD = .71) at time 1. The same tendency occurred at time 2 (ingroup: M
= .83, SD = .77; outgroup: M = .61, SD = .69). The mean accuracy rates across time,
valence, and group are presented in Table 1. There was no three-way interaction of time
(time 1 and time 2), group (ingroup and outgroup), and valence (positive and negative).
Figure 3. Recognition memory for negative actions as a function of time (time 1 and time
1) and group (ingroup and outgroup) expressed as the mean number of actions accurately
recalled (for a total of four actions).
Table 1. Mean accuracy rates across time, valence, and group in the recognition memory
assessment.
Time 1 Time 2
Positive Negative Positive Negative
Ingroup 1.36 1.31 .78 .83
Outgroup 1.47 1.19 .64 .61
The mean number of accurately remembered positive actions was compared with
accurately remembered negative actions, including both ingroup and outgroup at time 1.
This analysis revealed a tendency to more accurately remember positive actions (M =
2.66, SD = 1.12) than negative actions (M = 2.43, SD = 1.14; p = .07). Mean memory
rates are presented in Figure 4.

Figure 4. Recognition memory as a function of valence (positive or negative) expressed
as the mean number of actions accurately recalled (for a total of four actions for each
valence).
Explicit Liking
Mean ingroup and outgroup liking scores were analyzed using a repeated measures
analysis of variance with two within-participant factors (Time: time 1 vs. time 2 x Group:
ingroup and outgroup). This analysis revealed a very slight preference for ingroup
members (M = 2.74, SD = .41) as compared to outgroup members (M= 2.70, SD = .48) at
time 1. The same trend was also seen at time 2 (ingroup: M = 2.71, SD = .46; outgroup:
M= 2.69, SD = .36). However, there was no significant effect of group on ingroup or
outgroup score (p =.76). An index of group preference (mean ingroup score – mean
outgroup score) was calculated for both time 1 and time 2 (time 1: .04; time 2: .02). There
were no significant interactions, but the tendency for ingroup preference is displayed in
Figure 5.

Figure 5. Explicit liking as a function of time (time 1 and time 1) and group (ingroup and
outgroup) expressed as the mean score for ingroup or outgroup members (for a highest
score of 4 for either group).
Behavioral Attribution
Adjective assignment was analyzed using a repeated measures analysis of variance
with three within-participant factors (Time: time 1 vs. time 2 x Group: ingroup vs.
outgroup x Valence: positive actions vs. negative adjectives). This analysis revealed a
tendency to assign more positive adjectives than negative adjectives overall (p < .001).
There was also an effect of time by valence (p < .05). Furthermore, there was a slight
tendency for participants to assign more positive adjectives to their outgroup than ingroup
at time 1(ingroup: M = 2.61, SD = 1.02; outgroup: M = 2.89, SD = 1.14). At time 2, this
trend reversed- participants assigned more positive adjectives to their ingroup than
outgroup (ingroup: M = 2.42, SD = 1.18; outgroup: M = 2.28, SD = 1.23). These
tendencies are displayed in Figure 6.

Figure 6. Behavioral attribution for positive adjective assignment as a function of time
(time 1 and time 1) and group (ingroup and outgroup) expressed as the mean number of
positive adjectives assigned to ingroup or outgroup members (for a maximum of 4
adjectives for either group).
Lastly, there was a slight tendency for participants to assign more negative
adjectives to their ingroup than outgroup at time 1 (ingroup: M = 1.39, SD = 1.02;
outgroup: M = 1.11, SD = 1.14). At time 2, this trend reversed- participants assigned
more negative adjectives to their outgroup than ingroup (ingroup: M =1.58, SD = 1.18;
outgroup: M = 1.72, SD = 1.23) These tendencies are displayed in Figure 7. The mean
number of adjectives assigned across time, valence, and group are presented in Table 2.
There were no effects as a three-way interaction of time (time 1 and time 2), group
(ingroup and outgroup), and valence (positive and negative).
Table 2. Mean number of adjectives assigned across time, valence, and group in the
behavioral attribution assessment.
Time 1 Time 2
Positive Negative Positive Negative
Ingroup 2.61 1.39 2.42 1.58
Outgroup 2.89 1.11 2.28 1.23

Figure 7. Behavioral attribution for negative adjective assignment as a function of time
(time 1 and time 1) and group (ingroup and outgroup) expressed as the mean number of
negative adjectives assigned to ingroup or outgroup members (for a maximum of 4
adjectives for either group).
Discussion
The purpose of the current study was to examine the effect of ingroup bias on
memory and attitude across time. It was predicted that participants would more
accurately remember positive ingroup actions than positive outgroup actions. It was also
hypothesized that participants would more accurately remember negative outgroup
actions than negative ingroup actions. Finally, we also expected participants to more
accurately remember ingroup actions than outgroup actions.
In the current experiment, individuals were more likely to recall negative events
than positive events in a free-recall setting. This finding is supported by previous research
by Dunham, Baron, and Carey (2011). However, due to the nature of the free recall
assessment, the vast majority of participants did not state which person completed which
actions. Therefore, this assessment provides us with little information regarding ingroup
bias and how it affects memory.

While in the free-recall experiment participants were more likely to recall
negative events, the same was not the case with accuracy. In the recognition memory
assessment, participants were more accurate about positive events than negative events.
In other words, memory was better for remembering who completed positive actions than
for who completed negative actions. These two findings together raise an interesting
point; it seems that while individuals might remember negative actions better than
positive actions, they might be more accurate about the person committing the positive
actions.
When considering ingroup bias specifically, the current study did not yield any
significant findings. There were, however, some notable trends among the memory and
attitude assessments. Participants were more accurate about actions committed by their
ingroup than actions committed by their outgroup. This finding provides support for
social categorization as a cause for ingroup bias. It may be possible that even in arbitrary
minimal groups, the faces of ingroup members lead to a different type of processing than
with those of outgroup members. To examine how exactly this process occurs requires
more investigation (Sporer, 2001).
In terms of ingroup preference, an unexpected trend was discovered. Previous
research utilizing the minimal group paradigm has found an ingroup preference in
memory. For example, Dunham and colleagues (2011) found a tendency to remember
more positive ingroup events than positive outgroup events. In the current study,
however, the opposite trend was found at time 1. Although not statistically significant,
participants were more accurate with positive outgroup actions than with positive ingroup

actions. This trend reversed at time 2 to support ingroup preference- participants were
more accurate with positive ingroup actions than positive outgroup actions.
The trend reversal found in the recognition memory assessment was also
discovered in the behavioral attribution assessment. Despite findings of ingroup
preference in a study conducted by Otten and Moskowitz (2000), an ingroup preference
in behavioral attribution was also not found at time 1. Although not significant, there was
a trend of participants assigning more positive adjectives to their outgroup than to their
ingroup at time 1. Additionally, participants trended toward being more likely to assign
negative adjectives to their ingroup than their outgroup at time 1. However, as with
recognition memory, both of these unexpected trends reversed in time 2 to show ingroup
preference. At time 2, participants were slightly more likely to assign positive adjectives
to their ingroup than to their outgroup and were also more likely to assign negative
adjectives to their outgroup than ingroup. However, there was not a significant
difference.
In the behavioral attribution assessment, participants were more likely to assign
positive adjectives than negative adjectives overall. A similar finding was discovered in
the explicit liking assessment; participants assigned almost equal scores to their ingroup
and outgroup. It appears that the majority of participants had fairly positive feelings to
both groups in both explicit liking and implicit liking as measured by behavioral
attributions. It is possible that more severe actions may lead to different results. There is
also potential for a lack of ingroup preference in adults in terms of liking assessments.
Limitations

Despite several interesting findings and notable trends, the current study
contained several limitations. The largest drawback of the experiment was the low
sample size. A larger sample size would afford more statistical power. It is possible that
with more power, we may have seen more significant findings (i.e., the trends observed
here could have been significant).
In addition to size, the makeup of the sample is also a limitation as the majority
of participants were college-educated Caucasian females. On a similar note, because the
experiment was completed on a university campus, it is possible that there were some
participants that may have seen the volunteer stimuli before. Although participants that
mentioned that they knew one or more of the stimuli were excluded, it is possible that
some participants may have known the stimuli before the experiment.
Finally, as the stimuli are stories read by a research assistant accompanied by
photographs, there is a lower level of ecological validity than with experiments using
videotaped actions or actions witnessed live. Similarly, in an eyewitness case, an
individual would potentially witness one action for a longer period of time rather than
multiple actions for a shorter period of time, as was the case in the current study.
Implications
The current study adds to the existing knowledge regarding ingroup bias and the
minimal group paradigm. As the findings regarding ingroup preference were not
significant, it could be possible that the previously seen ingroup preference in children is
not present or as strong in adults. A large portion of the minimal group paradigm has
examined how ingroup bias affects explicit liking, behavioral attribution, and resource
allocation, little research has examined its effect on memory over time (Dunham, Baron,

& Carey, 2011; Spielman, 2000). However, as previously mentioned, these findings
might be significant with a larger sample size. In that case, it is notable that the trend of
ingroup preference remained at time 2.
The reversals of trends seen in the recognition memory assessment and
behavioral attribution assessment are also notable. In those cases, an unexpected
outgroup preference was discovered at time 1, while a hypothesized ingroup preference
was discovered at time 2. This interesting finding could be due to a defensive mechanism
occurring at time 1. It is possible that after hearing stories of their ingroup performing
negative actions, participants became defensive of their association to this group and
viewed their ingroup less favorably. However, this theory needs a great deal more of
investigation and should be studied more intently in future research.
Future Research
In addition to further investigation into a possible defensive mechanism in
ingroup-outgroup studies, future research should continue examining the minimal group
paradigm and ingroup bias as a whole. As previously mentioned, ecological validity
would be greater with the use of a video or witnessing the actions live. Witnessing one
action for a longer time could also increase ecological validity, which in turn would or
would not support the use of eyewitness testimony in court. Therefore, future research
should examine if the same trends occur with these changes.
Additionally, future research should examine whether ingroup preference occurs
in the case of more severe actions. In cases with eyewitnesses, the crimes could be as
severe as rape or murder, which are more emotionally salient than the negative actions

used in the current experiment. It is possible that memory could be more or less accurate
as the severity of the actions is higher or lower.
Finally, future research should examine the area of ingroup bias as a whole.
Understanding how reliable or unreliable eyewitness testimony can be continues to be a
pressing issue in the legal system. As admissible eyewitness testimony can serve as the
foundation of a case, knowing its potential reliability and credibility is of the utmost
significance. How much weight should be given to this testimony is a question that still
plagues the legal system; more research in this area could help to answer this question.

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Appendix A
Photo headshots presented in stimuli:

Appendix B
Stories presented as stimuli:
1. Jessica was unhappy that her computer was broken. Jessica was working in the library
and saw the person working next to her leave the library and a computer behind to take a
phone call. Jessica decided she would take the computer for her own.
2. Sara was walking to class and overheard a classmate talking about how easy an exam
was. Sara did poorly on the exam and this upset her to hear. As the classmate was
walking by, Sara stuck out her foot and tripped the classmate.
3. Emily had a meeting in the afternoon. Emily had made food and decided to make extra.
Emily brought the food to the afternoon meeting to share with the rest of the people there.
4. Laura was walking through the park on her way home. Laura noticed that a group of
people left a large amount trash behind after a picnic. Laura stopped walking, picked up
all of the trash left behind, and threw it away in a nearby garbage can.
5. Michael was walking through Collegetown after a long day of classes. Michael saw
someone on College Avenue drop a pile of papers on the sidewalk. Michael went over to
the person and helped pick up all of the dropped papers, even though Michael just
wanted to get home.
6. Chris realized that he had a lot of clothes in the closet that he did not wear often. Chris
remembered that there was a clothing drive going on at the school in town. Chris took a
box of clothes and brought them to the school to be donated.
7. Josh realized that he had made a huge mistake on his midterm. Josh knew that the
midterms were kept in the professor’s office after 5pm. Josh picked the lock to the
professor’s office to break in and changed his midterm.
8. Tyler and his coworker always disagreed. One day at work, Tyler and the coworker
got into a big fight. The coworker made an offhanded comment. Tyler became very angry
and threw water in the coworker’s face.

Appendix C
Memory recognition assessment sample question:
Appendix D

Headshots presented in the explicit liking assessment and the behavioral attribution
assessment:

Appendix E
Explicit liking assessment sample question:

Appendix F
Behavioral attribution assessment sample question:

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