University of Harvard Psychology Essay

Please summarize the following article. Has to be TWO pages.

INTERPERSONAL RELATIONS AND GROUP PROCESSES
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Across the Thin Blue Line: Police Officers and Racial Bias in the Decision
to Shoot
Joshua Correll
Bernadette Park and Charles M. Judd
University of Chicago
University of Colorado at Boulder
Bernd Wittenbrink
Melody S. Sadler
University of Chicago
University of Colorado at Boulder
Tracie Keesee
University of Denver
Police officers were compared with community members in terms of the speed and accuracy with which
they made simulated decisions to shoot (or not shoot) Black and White targets. Both samples exhibited
robust racial bias in response speed. Officers outperformed community members on a number of
measures, including overall speed and accuracy. Moreover, although community respondents set the
decision criterion lower for Black targets than for White targets (indicating bias), police officers did not.
The authors suggest that training may not affect the speed with which stereotype-incongruent targets are
processed but that it does affect the ultimate decision (particularly the placement of the decision
criterion). Findings from a study in which a college sample received training support this conclusion.
Keywords: police, race, bias, weapon, training
& Wittenbrink, 2002; Greenwald, Oakes, & Hoffman, 2003;
Payne, 2001). Although social psychologists have only recently
addressed this question, the impact of suspect ethnicity on police
shootings has long been the focus of researchers in other fields of
study, particularly sociology, political science, and law enforcement. Investigators have consistently found evidence that police
use greater force, including lethal force, with minority suspects
than with White suspects (e.g., Inn, Wheeler, & Sparling, 1977;
Smith, 2004; see Geller, 1982, for a review). Data from the
Department of Justice (2001), itself, indicate that Black suspects
are approximately five times more likely than White suspects, per
capita, to die at the hands of a police officer.
One of the most detrimental consequences of police shootings is
the upheaval they can provoke. Shootings of a minority suspect
may engender a sense of mistrust and victimization among community members and give rise to conflict between the community
and police. Weitzer and Tuch (2004) present evidence that members of ethnic minorities often feel that they are mistreated by the
police, even after statistically controlling for factors like personal
and vicarious experiences with the law, exposure to the media, and
neighborhood disadvantage (see also Sunshine & Tyler, 2003).
The implication is that the police are racist and that officers use
excessive force with minority suspects. In response, Black people
may engage in more belligerent behavior, including “talking back”
to police officers, and—in a vicious cycle—this belligerence may
prompt more severe use of force by police (Reisig, McCluskey,
Inspired in part by high-profile police shootings of unarmed
Black men, a flurry of social psychological research has attempted
to assess the influence of a suspect’s race on the use of force,
specifically in terms of the decision to shoot (Correll, Park, Judd,
Joshua Correll, Department of Psychology, University of Chicago;
Bernadette Park, Charles M. Judd, and Melody S. Sadler, Department of
Psychology, University of Colorado at Boulder; Bernd Wittenbrink, Graduate School of Business, University of Chicago; Tracie Keesee, University
of Denver.
Primary support for this work was provided by a grant from the Russell
Sage Foundation. Support for this work also came from National Institute
of Mental Health Grant F31-MH069017 to Joshua Correll and National
Institute of Mental Health Grant R01-45049 to Bernadette Park and
Charles M. Judd.
In the interest of disclosure, we note that Tracie Keesee also serves as
a commander in the Denver Police Department. We thank Chief Gerald
Whitman, the Denver Police Department, Calibre Press, the Denver Department of Motor Vehicles, and (especially) the many officers of the
Denver Police Department and police departments around the country for
their assistance, patience, and participation. We also thank Alinne Barrera,
Heather Coulter, and David M. Deffenbacher for their invaluable assistance with this research and Myron Rothbart for his many helpful comments.
Correspondence concerning this article should be addressed to Joshua
Correll, Department of Psychology, University of Chicago, Chicago, IL
60637. E-mail: jcorrell@uchicago.edu
Journal of Personality and Social Psychology, 2007, Vol. 92, No. 6, 1006 –1023
Copyright 2007 by the American Psychological Association 0022-3514/07/$12.00
DOI: 10.1037/0022-3514.92.6.1006
1006
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THIN BLUE LINE
Mastrofski, & Terrill, 2004). It is equally important to note that, as
a consequence of this tension, officers who see their job as protecting the community may feel, and to some extent may actually
be, thwarted in their efforts to perform their duty.
Officer-involved shootings, then, can have severe consequences,
not just for the officers and suspects involved, but for the community at large as well. It is of paramount importance to understand and explain why minority suspects are disproportionately
likely to be shot. The sociological literature offers a number of
explanations. Some research suggests that bias in police shootings
stems, at least in part, from the officers’ role as protectors of the
privileged (predominantly White) classes over the less fortunate
(predominantly minority) members of society (Sorenson, Marquart, & Brock, 1993). Others argue that the racial discrepancy in
officer-involved shootings stems from differential minority involvement in criminal activity (Department of Justice, 2001; Inn et
al., 1977) or from the fact that minorities are disproportionately
likely to live and work in low-income, high-crime communities
(Terrill & Reisig, 2003).
A primary strength of the sociological approach is that it examines police use of force directly and in its true context. These
researchers study real locations and real officers, and their dependent variable is the number of suspects who are actually shot. They
thus maintain the richness and complexity of the real world when
analyzing relationships between officer-involved shootings and
variables like race or community disadvantage. At the same time,
the preexisting correlations among these variables confound efforts to assess their independent effects. For example, the relationship between the proportion of Black citizens in a community and
perceptions of disorder (Sampson & Raudenbush, 2004) is inextricably tied to, and cannot be fully separated from, racial discrepancies in officer-involved shootings (Terrill & Reisig, 2003). For
this reason, a social psychological analysis of the problem with
experimental methods is useful not to replace but rather to supplement research of a more naturalistic sort.
Over the past several years, social psychological researchers
have examined the effect of race on shoot/don’t-shoot decisions
using videogame-like simulations. In one paradigm, participants
view a series of images (background scenes and people) and are
instructed to respond to armed targets with a shoot response, and
to unarmed targets with a don’t-shoot response as quickly and as
accurately as possible (Correll et al., 2002; Correll, Park, Judd, &
Wittenbrink, 2007; Correll, Urland, & Ito, 2006). The results of
some 20 studies with this task, with a variety of parameters and
manipulations, consistently show racial bias in both the speed and
accuracy with which such decisions can be made. Participants are
faster and more accurate when shooting an armed Black man
rather than an armed White man, and faster and more accurate
when responding “don’t shoot” to an unarmed White man rather
than an unarmed Black man. The bulk of this research has been
conducted with college students, but the effect has been replicated
with community samples of both White and Black participants,
and conceptually similar effects have been obtained by a number
of other labs (Amodio et al., 2004; Greenwald et al., 2003; Payne,
2001; Payne, Lambert, & Jacoby, 2002; Plant, Peruche, & Butz,
2005). These findings, along with reports from sociological and
related literatures, clearly indicate that race can play an important
role in decisions about the danger or threat posed by a particular
1007
person. But experimental data rarely speak directly to police behavior.
In our literature review, we discovered only two papers that
examine officers in experimental studies of racial bias. Eberhardt,
Goff, Purdie, and Davies (2004) found that priming the concept of
crime served to orient attention to Black (more than White) faces.
This pattern held for officers and civilians alike. Plant and Peruche
(2005) examined training effects among officers on a task where
images of White and Black men appeared with a gun or nongun
object superimposed on the face. They found that officers showed
racial bias in their errors during the first phase of the study (i.e.,
officers were more likely to mistakenly shoot Black targets who
appeared with nongun objects, and to not shoot White targets who
appeared with a gun in the first 80 trials of the task), but that bias
fell to nonsignificant levels in the second phase (i.e., the last 80
trials of the task). These studies suggest that officers, like undergraduates, show racial biases in the processing of crime-related
stimuli.
But there is reason to believe that police will differ from citizens
in shoot/don’t-shoot decisions. Most notably, officers receive extensive experience with firearms during their academy training
(before they are sworn in) and throughout their careers. For example, the Denver Police Department requires that new recruits
spend 72 hr in practical weapons training, and officers must
recertify on a quarterly basis. At the firing range, officers and
recruits make shoot/don’t-shoot decisions for target silhouettes
that appear suddenly, either armed or unarmed; in Firearms Training System simulators (Firearms Training Systems, Inc., Atlanta,
GA), they respond to an interactive video simulation of a potentially hostile suspect; and in simulated searches, they confront live
actors armed with weapons that fire painful but nonlethal ammunition (e.g., paintballs, Simunition, or Air Soft pellets).
An extensive body of research shows that training improves
performance on tasks in which a peripheral cue interferes with a
participant’s response to a central or task-relevant cue. Through
training, participants learn to ignore the irrelevant information and
respond primarily on the basis of the central feature of the stimulus
(e.g., MacLeod, 1998; MacLeod & Dunbar, 1988; Plant & Peruche, 2005). For example, in a Stroop (1935) task, participants
classify the color in which a word is printed (e.g., red). Color is
thus the central cue. This task becomes more difficult if the word
(a peripheral cue) refers to a different color (e.g., the word “blue”
printed in red). Initially, participants have difficulty with this task,
responding slowly and inaccurately when the central and peripheral cues conflict. But with training, judgment improves. Responses occur more quickly and require less effort and less cognitive control. As a result, experts demonstrate reduced
interference in both latencies and errors. Neuroimaging studies
have even documented the shifting patterns of brain activity that
correspond to the development of automatic task performance
(Bush et al., 1998; Jansma, Ramsey, Slagter, & Kahn, 2001; for a
review, see Kelly & Garavan, 2004). During initial performance on
interference tasks, participants recruit brain regions related to
conflict detection and response control (e.g., the anterior cingulate
and medial prefrontal cortexes). With extensive practice, however,
activation in these regions decreases, presumably because an automatic task requires less executive supervision.
But automatization may not characterize all learning on interference tasks. In some cases, training actually promotes controlled
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1008
CORRELL ET AL.
processing. For example, when participants are continuously challenged by variable task requirements or increasing demands, practice can lead to more extensive recruitment of prefrontal brain
regions (Olesen, Westerberg, & Klingberg, 2004; Weissman,
Woldorff, Hazlett, & Mangun, 2002). Of particular relevance to
shoot/don’t-shoot decisions, this control involves the medial and
middle frontal gyri—areas related to the detection and resolution
of conflicting information and to the maintenance of goal-relevant
representations. In some cases, then, training leads participants to
work harder, in cognitive terms, as they learn to marshal the
attention and control necessary for optimal performance.
When will training promote automaticity in a judgment task, and
when will it promote control? A probable moderator is task complexity (Birnboim, 2003; Green & Bavelier, 2003). On tasks with
simple stimuli (e.g., the words presented in a Stroop task), practice
allows participants to streamline the judgment process, performing
it easily and automatically. Only when the task is difficult (e.g.,
involving visually complex stimuli or ever-changing task requirements) does practice seem to promote control. As Birnboim (2003)
wrote, “automatic processing relies on a reduction of stimulus
information to its perceptual and motor features” (p. 29). When
complexity renders this kind of reduction impossible, controlled
processing may be required to “extract more meaningful information” (p. 29). Consistent with this argument, Green and Bavelier
(2003) have shown that practice on a visually complex video game
(i.e., Medal of Honor; Electronic Arts, Redwood City, CA) improves performance on attention-demanding tasks, but practice on
a visually simple video game (i.e., Tetris; Electronorgtechnica,
Moscow, Russia) does not.
Task complexity has tremendous relevance for the officer engaged in a potentially hostile encounter. Faced with a range of
irrelevant and confusing factors (e.g., darkness, noise, movement,
bystanders), the officer must determine whether or not a small and
relatively inconspicuous weapon is present. On a reduced scale,
our paradigm attempts to simulate this visual and cognitive challenge. The task employs a variety of complex and realistic backgrounds (e.g., parking lots, train stations). By varying backgrounds
and suspect poses (e.g., standing, crouching), as well as the timing
of stimulus onset, we prevent participants from knowing when or
where an object will appear. When the object does appear, it
accounts for roughly 0.2% of the visual field. To respond correctly,
participants must engage in a careful, controlled search for a small
cue amid a complex stimulus array. In contrast to the visually
simple tasks typically employed in research on training, training on
this relatively complex task may not foster automaticity in the
shoot/don’t-shoot decision. In our task—as in a police encounter—
even highly trained experts may need to fully engage executive
control processes to identify the object and execute the appropriate
response (Weissman et al., 2002).
If experts are better able than novices to engage control processes, it stands to reason that police officers, whose training and
on-the-job experiences routinely force them to identify weapons in
complex environments, should make fewer errors in our shoot/
don’t-shoot task and should show reduced racial bias in those
errors (i.e., their expertise should minimize stereotypic errors).
This training-based reduction in bias, which we might call a
“police as experts” pattern, serves as our primary hypothesis (H1).
But control may not entirely eliminate race-based processing. The
necessity of a slow, effortful, and controlled search for the object
leaves open the possibility that even experts will inadvertently
process racial information. Research suggests that racial cues are
often perceived quickly, whether or not the participant intends to
do so (Cunningham et al., 2004; Ito & Urland, 2003), and accordingly, a slow visual search for the object should glean racial
information. By activating stereotypes, these cues may interfere
with the speed of the decision-making process. By virtue of enhanced control, experts may rarely, if ever, shoot an unarmed
Black individual; but because even experts must search (slowly)
for the object, they are likely to perceive the target’s skin color and
facial features, triggering relevant stereotypes. Again, experts may
effectively override this interference and make an unbiased response (“don’t shoot”), but because the weapon judgment is not
automatic, the controlled decision to stereotype incongruent targets
may still take more time. This leads us to predict a dissociation,
such that a target’s race may affect the speed of the expert’s
decisions, even though it has no impact on their accuracy.
To examine this possibility, the present research extends past
work in two critical ways. First, we examine bias in both response
times and errors. In past research (e.g., Correll et al., 2002; Payne,
2001), results from these two measures mirrored one another and
were characterized as more or less interchangeable. But the measures may capture partially distinct aspects of the decision process.
Latency—the time necessary for a participant to respond correctly
to a given target—should depend on the difficulty of processing
the stimulus. The fact that stereotype-incongruent targets (unarmed
Black targets and armed White targets) generally produce longer
latencies suggests that participants have greater difficulty arriving
at a correct decision for these stimuli. Processing difficulty may
also influence error rates, but errors also reflect the participant’s
ultimate decision about which response to make. Particularly from
an officer’s perspective, the distinction between a slow-butaccurate response (e.g., hesitating and then deciding not to fire)
and an incorrect response (e.g., shooting an unarmed suspect)
assumes great importance.
This research also advances our understanding by comparing
police officers with samples of laypeople drawn from the communities those officers serve. Community samples provide a crucial
baseline against which we can compare the police. As we have
already discussed, one of the most damaging consequences of
officer-involved shootings in which a minority suspect is killed is
the implication that police inappropriately use race when making
the decision to fire. However, given the prevalence of bias in the
decision to shoot (which has been documented in all types of
people, from White college students to Black community members), how can we interpret the magnitude of any bias we might
observe among the police? Inhabitants of the community served by
a given police department provide a critical comparison. As members of a common culture, these individuals experience many of
the same influences, whether very global (e.g., national broadcast
media) or very local (e.g., racial and ethnic composition of the
neighborhood, local levels of poverty and crime) in nature. To
fully characterize the presence of any bias among police, it is
therefore critical to examine bias in the communities they serve.
No such comparison is available in existing research. Although we
have elaborated the hypothesis that police will demonstrate less
bias than the community, particularly with respect to their error
rates (H1), we note that the comparison between police and community presents two other possibilities.
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THIN BLUE LINE
Of course, it is also possible that officers will show more
pronounced bias than community members (H2) or that police and
civilians will show relatively similar patterns of bias (H0). In line
with the former hypothesis, Teahan (1975a, 1975b) presented
evidence that police departments acculturate White officers into
more prejudicial views during their first years on the job. Similarly, the Christopher Commission’s investigation into the Los
Angeles Police Department’s 1991 beating of Rodney King reported that officers who adopted anti-Black attitudes were more
likely to be promoted within the department (Christopher, 1998).
This ostensible culture of bias may find expression in police
officers’ relatively high social dominance orientation (Sidanius &
Pratto, 1999), reflecting support for the group-based (and racebased) hierarchical structure of society (see Sorenson et al., 1993,
for similar conclusions on the basis of police use of force). Given
these findings, we might reasonably expect a “police as profilers”
pattern, with officers relying heavily on racial information when
making their decisions to shoot.
Finally, police officers and community members may show
equivalent levels of racial bias in decisions to shoot. Inasmuch as
police and community members are subject to the same general
cognitive heuristics (Hamilton & Trolier, 1986) and sociocultural
influences (Devine & Elliot, 1995), the two groups may demonstrate similar patterns of behavior in the video game simulation.
This prediction would yield a pattern we might call “police as
citizens.”
Our primary hypothesis derives from the possibility that practice
enables police officers to more effectively exert control over their
behavioral choices (relative to untrained civilians). That is, H1
suggests that officers may more extensively engage in controlled
processing operations during the course of the shoot/don’t-shoot
task. Because of this difference in processing, we predict a divergence between measures of bias that are based on errors and
measures that are based on reaction times. By contrast, H2 and H0
offer no clear reason to predict differences between officers and
civilians in terms of cognitive processing, and (accordingly) they
offer no reason to expect a divergence between error-rate and
reaction-time measures.
Study 1
Method
Overview. Three samples of participants completed a 100-trial
video game simulation in which armed and unarmed White and
Black men appeared in a variety of background images. Participants were instructed that any armed target posed an imminent
threat and should be shot as quickly as possible. Unarmed targets
posed no threat and should be flagged accordingly by pushing the
don’t-shoot button, again as quickly as possible. The speed and
accuracy with which these decisions were made served as our
primary dependent variables, and performance was compared
across three samples: officers from the Denver Police Department,
civilians drawn from the communities those officers served, and a
group of officers from across the country attending a 2-day police
training seminar.
1009
Participants. For the purposes of law enforcement, the city of
Denver is divided into six districts. With the help of the command
staff, officers were recruited for this study from four of these
districts during roll call. Participation was completely voluntary,
and officers were assured that there would be no way to identify
individual performance on the task and that the command staff
would not be informed of who did and did not participate. Officers
were required to complete the simulation during off-duty hours.
Our goal was to recruit primarily patrol officers, and, in this effort,
we were successful: 84% of the sample listed patrol as their job
category. Investigative officers accounted for 9% of the sample,
administrative officers for 2% of the sample, with the remaining
5% of the officers from a mixture of other job categories. A total
of 124 officers participated in the study (9 female, 114 male, 1
missing gender; 85 White, 16 Black, 19 Latina/o, 3 other, 1
missing ethnicity; mean age ⫽ 37.9 years). Each received $50.
To obtain a companion civilian sample, we enlisted the Department of Motor Vehicles (DMV) office in each of the four districts,
recruiting community members to perform the simulation on or
around the same days as the police officers. Several of the DMVs
were in areas with a high concentration of Spanish-speaking citizens. For these areas, a bilingual research assistant recruited and
instructed the participants.1 A total of 135 civilians participated in
the study. Eight participants were dropped from the analyses: 2
because of a computer malfunction and 6 because they had fewer
than five correct trials for at least one of the four cells of the
simulation design. Thus, the reported results for this sample are
based on 127 civilians (51 female, 73 male, 3 missing gender; 39
White, 16 Black, 63 Latina/o, 9 other; mean age ⫽ 35.5 years).
Each received $20.
To collect the national police sample, we attended a training
seminar for officers. This was one of several seminars that officers
voluntarily attend to obtain additional training in some particular
area of law enforcement. The seminars are specifically geared for
patrol officers, rather than administrative personnel. The sample of
officers obtained for this study came from 14 different states, and
only 7% worked in some administrative capacity. The remaining
job categories included patrol officers (58%), investigative officers
(14%), traffic officers (7%), SWAT team members (3%), and a
sprinkling of other categories (11%). Although this clearly is not a
random national sample of officers, it offers a greater diversity of
background than the Denver sample. An announcement regarding
the study was made during the seminar, and officers were invited
to participate on one of two evenings after the conclusion of the
seminar for that day. A total of 113 officers participated in the
study (12 female, 100 male, 1 missing gender; 72 White, 10 Black,
15 Latina/o, 13 other, 3 missing ethnicity; mean age ⫽ 38.4 years).
Each received $50.
Video game simulation. Fifty men (25 Black, 25 White) were
photographed in five poses holding one of a variety of objects,
including four guns (a large black 9 mm, a small black revolver, a
large silver revolver, and a small silver automatic) and four nonguns (a large black wallet, a small black cell phone, a large silver
Coke can, and a small silver cell phone). For each individual, we
1
Many thanks to Alinne Barrera who tirelessly and happily made time
in her busy schedule to accompany us on these sojourns at the Denver
DMVs.
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1010
CORRELL ET AL.
selected two images, one with a gun and one with an innocuous
object, resulting in 100 distinct images (25 of each type: armed
White, armed Black, unarmed White, and unarmed Black), which
served as the principal stimuli, or targets, in the game. Forty of
these images were drawn from previous work (see Correll et al.,
2002, for example stimuli). The others were added in an effort to
diversify the sample of targets. Using Photoshop, we embedded
targets in 20 otherwise unpopulated background scenes, including
images of the countryside, city parks, facades of apartment buildings, and so on. Each target was randomly assigned to a particular
background, with the restriction that each type of target should be
represented with equal frequency in each background.
Design. The video game, developed in PsyScope (Cohen,
MacWhinney, Flatt, & Provost, 1993), followed a 2 ⫻ 2 withinsubjects design, with Target Race (Black vs. White) and Object
Type (gun vs. nongun) as repeated factors (see Correll et al.,
2002). On any given trial of the game, a random number (0 –3) of
preliminary backgrounds appeared in slideshow fashion. These
scenes were drawn from the set of 20 original unpopulated background images. Each remained on the screen for a random period
of time (500 ms– 800 ms). Subsequently, a final background appeared (e.g., an apartment building), again for a random duration.
This background was replaced by an image of a target person
embedded in that background (e.g., an armed White man standing
in front of the building). From the player’s perspective, the target
simply seemed to appear in the scene. The player was instructed to
respond as quickly as possible whenever a target appeared, pressing a button labeled shoot if the target was armed and pressing a
button labeled don’t shoot if the target was unarmed. The game
awarded points on the basis of performance. Correctly pressing
don’t shoot in response to an unarmed target earned 5 points, but
shooting earned a penalty of 20 points; pressing shoot in response
to an armed target earned 10 points, but pressing don’t shoot
earned a penalty of 40 points (the implication being that the hostile
target shot the player). Failure to respond to a target within 850 ms
of target onset resulted in a penalty of 10 points. Feedback, both
visual and auditory, and point totals were presented at the conclusion of every trial. The game consisted of a 16-trial practice block
and a 100-trial test block.
Procedure. Officers in the Denver sample were recruited
roughly 1 week prior to the study. Volunteers selected a time and
date to participate. At the scheduled time, each officer was seated
at a small cubicle in a test room equipped with a laptop computer,
button box, and headphones. They completed the simulation and
questionnaire packet. The measures included in the questionnaire
packet are summarized in Table 1. Community members were
approached at one of the various DMV locations, and those who
agreed to participate completed the simulation using the same
equipment as the officers. Community members completed the
same questionnaire as the officers (excluding items specific to
policing). For the national sample of officers, an announcement
was made the first day of the training seminar inviting officers to
participate in the study. Officers completed the simulation and
questionnaire packet on one of two evenings in a room in the hotel
where the conference was held. The equipment was identical to
that used for the Denver officers and civilians. Upon completion,
all participants were debriefed and thanked.
Results
Signal-detection analyses. We began by examining the accuracy of responses as a function of trial type and sample. Overall,
participants responded incorrectly on 4.7% of the trials and timed
out on another 4.8% of the trials. Correct and incorrect responses
(i.e., excluding timeouts) were used to conduct a signal-detection
analysis. Applied to the shooter simulation, signal detection theory
(SDT) assumes that armed and unarmed targets vary along some
dimension relevant to the decision at hand (e.g., the threat they
pose). SDT yields estimates of participants’ ability to discriminate
between the two types of target (i.e., sensitivity to the presence of
a weapon, a statistic called d⬘) and the point on that decisionrelevant dimension at which they decide a stimulus is threatening
enough to warrant shooting (i.e., the psychological criterion for the
decision to shoot, a statistic called c). With SDT it is possible to
test whether the race of a target affects discriminability and,
separately, whether target race affects the decision to shoot. Correll et al. (2002, Study 2) observed no race differences in d⬘ but
found that c was lower for Black targets than for White targets.
That is, participants were equally able to differentiate between
armed and unarmed targets regardless of target race, but they used
a more lenient threshold—indicating a greater willingness to
shoot—when the target was Black rather than White.
We calculated d⬘, or the ability to accurately discriminate armed
from unarmed targets, once for the White targets and once for the
Black targets. We also calculated c, or the criterion, assessing the
threshold for making a shoot response separately for Black and
White targets.2 The SDT estimates were submitted to separate 3
(Sample: national officers vs. Denver officers vs. Denver community) ⫻ 2 (Target Race: Black vs. White) mixed-model analyses of
variance (ANOVAs).
Placement of the criterion for the decision to shoot (c) at zero
indicates no greater tendency to make a shoot response than a
don’t-shoot response. Deviations from zero in a positive direction
indicate a bias favoring the don’t-shoot response, and deviations in
a negative direction indicate a bias to shoot. On average (i.e., for
both officers and civilians and both Black and White targets),
participants demonstrated a bias in favor of the shoot response,
F(1, 361) ⫽ 4.68, p ⫽ .03, but the extent to which this was true
depended on sample, F(2, 361) ⫽ 4.97, p ⬍ .008. Pairwise
comparisons indicated that the community set significantly lower
criteria than either officer sample, both Fs(1, 361) ⬎ 4.12, ps ⬍
.05. (All pairwise comparisons were tested with the error term
from the full sample.) Indeed, although the mean threshold was
significantly below zero for the community sample, F(1, 126) ⫽
10.05, p ⬍ .002, it did not differ from zero for either of the two
officer samples, both Fs ⬍ 1, and the two officer samples did not
differ from each other, F(1, 361) ⫽ 1.22, p ⫽ .27.
It is important to note that the main effect of target race in the
placement of the decision criterion was significant, F(1, 361) ⫽
5.17, p ⬍ .03, such that c was lower when responding to Black
c ⫽ ⫺0.5 ⫻ (zFA ⫹ zH); d⬘ ⫽ zH ⫺ zFA, where FA is the proportion
of false alarms (relative to correct rejections) and H represents the proportion of hits (relative to misses). The z operator is the translation of these
proportions to z-scores. Both FA and H were assigned a minimum value of
1/2n (where n ⫽ the total number of no-gun and gun trials, respectively)
and a maximum of 1 ⫺ (1/2n), to eliminate infinite z-scores.
2
THIN BLUE LINE
1011
Table 1
Demographic and Psychological Variables Included in Questionnaire Packet and Their
Correlations With Bias in Latencies in Study 1
Correlation with bias in latencies
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Variable
Population of city in which officer serves
Population of county in which officer serves
Violent crime in community served
% African Americans in community served
% all ethnic minority groups in community served
Classroom firearms training
Firing-range firearms training
Video firearms training
Live firearms training
Total years on the force
Gender (⫺1 ⫽ female; 1 ⫽ male)
Ethnicity (⫺1 ⫽ non-White; 1 ⫽ White)
Education
Self-rated liberalism (1)–conservatism (13)
Thermometer rating (warmth toward White people–warmth
toward Black people)
Thermometer rating (warmth toward White people–warmth
toward members of all ethnic minority groups)
Personal stereotype of Black people as dangerous, violent,
and aggressive
Cultural stereotype of Black people as dangerous, violent,
and aggressive
Contact with Black people
Internal motivation to control prejudice
External motivation to control prejudice
Discrimination scale
National
officers
Denver
officers
Denver
community
.31***
.31***
.20**
.21**
.22**
.01
.03
⫺.02
.02
⫺.09
⫺.13
⫺.09
.02
⫺.04
.00
—
—
⫺.09
.01
⫺.02
—
—
—
—
⫺.17*
⫺.13
⫺.14
.10
⫺.21**
⫺.02
—
—
⫺.05
.01
.05
—
—
—
—
—
.21**
⫺.08
⫺.12
⫺.06
.03
.00
.00
⫺.04
.02
.01
.20**
.02
.05
.09
.05
⫺.04
.16
⫺.13
⫺.02
.05
⫺.12
⫺.04
.11
⫺.11
.20**
.08
Note. City and county population have no variance for the Denver police and community samples, and hence
no correlation can be computed. Firearms training data were not collected for the Denver officers, nor for the
community. Ns vary slightly across entries because of missing observations. In the national sample, ns vary from
97–113; in the Denver police sample, they vary from 118 –123; and in the Denver community sample, they vary
from 120 –127. Dashes indicate that data were not collected.
*
p ⬍ .10. **p ⬍ .05. ***p ⬍ .01.
rather than White targets (see the top half of Figure 1 and the
means in Table 2). This discrepancy constitutes bias. Although the
omnibus test of the interaction between target race and sample was
not significant, F(2, 361) ⫽ 1.87, p ⫽ .16, pairwise comparisons
indicated a larger target race difference for the Denver community
compared with the national officer sample, F(1, 361) ⫽ 3.67, p ⫽
.056, other Fs ⬍ 1.49, ps ⬎ .22. Racial bias in c was significant
among the Denver community sample, F(1, 126) ⫽ 5.71, p ⬍ .02,
marginally significant among the Denver officer sample, F(1,
123) ⫽ 3.28, p ⫽ .07, and nonsignificant among the national
officer sample, F ⬍ 1.
It is informative to examine sample differences in c separately
for the White and Black targets. As is clear from Figure 2,
placement of the criterion for the White targets changed very little
across the three samples, and in fact neither the omnibus test of
sample differences, F ⬍ 1, nor any of the pairwise comparisons, all
Fs(1, 361) ⬍ 1.54, ps ⬎ .22, revealed a significant difference on
this measure. Moreover, the criterion for White targets was not
significantly different from zero for any of the three samples, all
Fs ⬍ 1.49, ps ⬎ .23. That is, neither officers nor community
members showed a tendency to favor one response over the other
when the target was White. In contrast, the threshold for Black
targets changed substantially and significantly across the three
samples, F(2, 361) ⫽ 7.03, p ⬍ .001. The criterion was set lowest
by the Denver community sample, whose mean c was both significantly lower than zero, F(1, 126) ⫽ 15.05, p ⬍ .001, and
significantly lower than either of the two officer samples, both
Fs(1, 361) ⬎ 4.42, ps ⬍ .04. The Denver officers’ mean c value
was also significantly below zero, F(1, 123) ⫽ 4.04, p ⬍ .05, and
approached a significant difference when compared to the national
officer sample, F(1, 361) ⫽ 2.79, p ⫽ .10. The national officers’
criteria for Black targets did not differ from zero, F ⬍ 1.3
3
In each of the three samples, we tested for moderation of bias in
latencies, d⬘, and c by participant ethnicity and gender. Because of the
relatively small number of non-White participants, particularly in the
officer samples, these analyses compared all non-White participants with
White participants. Bias was not moderated by participant ethnicity for any
of the samples ( ps ranged from .76 to .11). The only effect of gender was
moderation of bias in response times for the community sample. Bias was
significantly greater for male than for female community members, F(1,
122) ⫽ 5.66, p ⬍ .02, but it is important to note that bias was significant
within each sample, F(1, 50) ⫽ 11.16, p ⬍ .002 for female participants,
and F(1, 72) ⫽ 61.00, p ⬍ .001 for male participants.
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1012
CORRELL ET AL.
Figure 1. Decision criterion placement (c) and sensitivity (d⬘) for Black and White targets as a function of
sample (Study 1).
With respect to the analysis of d⬘, these data largely replicated
previous work, such that target race did not affect participants’
ability to discriminate armed from unarmed targets. In other
words, the main effect of target race was not significant in the d⬘
analysis, F(1, 361) ⫽ 1.12, p ⫽ .29 (see the bottom panel of
Figure 1 and Table 2 for all means and standard deviations).
However, the main effect of sample was significant, F(2, 361) ⫽
11.69, p ⬍ .001. Pairwise comparisons indicated that both officer
samples showed higher discriminability than the community, indicating a greater ability to differentiate armed from unarmed
targets, both Fs(1, 361) ⬎ 11.01, ps ⬍ .001. The two officer
samples did not differ from one another, F(1, 361) ⫽ 1.55, p ⫽
.21. The interaction between sample and race of target was marginally significant, F(2, 361) ⫽ 2.49, p ⫽ .085. Pairwise comparisons indicated a significant difference only between the Denver
officers and the Denver community, F(1, 361) ⫽ 4.63, p ⬍ .04.
The officers showed slightly (but nonsignificant, F ⬍ 1) greater
sensitivity to weapon detection for Black rather than White targets.
Among the community, d⬘ was significantly higher for White
targets than for Black targets, F(1, 126) ⫽ 4.84, p ⬍ .03.
Reaction-time analyses. We next examined reaction times. For
each participant, latencies from correct responses were log transformed and averaged separately for each type of target (see Table
2 for means and standard deviations). Averages were analyzed as
a function of sample (national officers vs. Denver officers vs.
Denver community), target race (Black vs. White), and object type
(gun vs. nongun) using a 3 ⫻ 2 ⫻ 2 mixed-model ANOVA with
repeated measures on the latter two factors. Consistent with past
research, we obtained a main effect of object type, F(1, 361) ⫽
2,171.27, p ⬍ .001, such that participants shot armed targets more
THIN BLUE LINE
1013
Table 2
Response Time, Sensitivity, and Decision Criterion Means and Standard Deviations for Studies 1 and 2
Sample
National officers
Black
Variable
M
Denver officers
White
SD
M
Black
SD
M
Denver community
White
Black
White
SD
M
SD
M
SD
M
SD
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Study 1
Response time
Gun
ms
log transformed mean
No gun
ms
log transformed mean
Sensitivity (d⬘)
Threshold (c)
Sensitivity (d⬘)
Threshold (c)
552a
6.31
0.07
560b
6.33
0.07
560a
6.33
0.08
572b
6.35
0.07
568a
6.34
0.09
578b
6.36
0.09
648a
6.47
3.42
.014
0.06
0.59
0.19
635a
6.45
3.43
.009
0.06
0.50
0.21
653a
6.48
3.54
⫺.032*
0.05
0.52
0.18
637b
6.46
3.50
.006
0.06
0.59
0.21
663a
6.50
3.12
⫺.087*
0.07
0.78a
0.25a
649b
6.48
3.24
⫺.026
0.07
0.76b
0.24b
Study 2
2.39
0.80
⫺.072
0.30
2.17
⫺.122*
0.73
0.31
1.39
⫺.302*
0.84
0.33a
1.47
⫺.185*
1.03
0.39b
Note. Different row subscripts within each sample indicate a significant Black–White difference at p ⬍ .05. For the decision criterion, means significantly
different from zero at p ⬍ .05 are indicated with an asterisk.
quickly than they decided to not shoot unarmed targets. The target
race main effect was also significant, F(1, 361) ⫽ 4.90, p ⬍ .03,
such that, overall, responses were very slightly faster to White
(M ⫽ 605 ms) than to Black targets (M ⫽ 608 ms). Moreover, the
sample main effect was significant, F(2, 361) ⫽ 5.36, p ⬍ .006.
Contrasts among the samples indicated that both officer groups
responded significantly faster overall than the civilian group, Fs(1,
361) ⬎ 3.68, ps ⬍ .056, and the two officer samples did not differ
from each other, F ⫽ 1.86, p ⫽ .18 (Mnational officers ⫽ 597 ms,
MDenver officers⫽ 604 ms, MDenver community ⫽ 613 ms).
It is important to note that we obtained the Target Race ⫻
Object Type interaction, F(1, 361) ⫽ 239.37, p ⬍ .001. This effect
reflects racial bias in decisions to shoot (see Figure 2). Notably, the
interaction did not depend on sample, F(2, 361) ⫽ 1.74, p ⫽ .18.
Bias was significant for all three samples: for the national sample
of officers, F(1, 112) ⫽ 68.89, p ⬍ .001, for the Denver officers,
F(1, 123) ⫽ 117.29, p ⬍ .001, and for the Denver community
sample, F(1, 126) ⫽ 65.29, p ⬍ .001. Pairwise comparisons
among the samples revealed no differences in the magnitude of
bias between the community sample and either of the officers
samples, Fs ⬍ 1.17, ps ⬎ .28, and marginally greater bias among
the Denver than national officer sample, F(1, 361) ⫽ 3.44, p ⫽
.065.
We further examined the simple effects of target race for each
type of object. Again, consistent with previous findings, participants shot armed targets more quickly when they were Black,
rather than White, F(1, 361) ⫽ 74.04, p ⬍ .001, and they indicated
don’t shoot in response to unarmed targets more quickly when they
Figure 2. Response times to Black and White armed and unarmed targets as a function of sample (Study 1).
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1014
CORRELL ET AL.
were White, rather than Black, F(1, 361) ⫽ 177.27, p ⬍ .001.
These simple effects did not depend on sample, both Fs ⬍ 1, ps ⬎
.39, and both of the simple target race effects within object type
were significant for each of the three samples, all Fs ⬎ 15.00, all
ps ⬍ .001. Pairwise comparisons for the simple effects among the
three samples revealed no significant differences, all Fs ⬍ 1.85, all
ps ⬎ .17.
Summarizing the results thus far, we see that officers and
community members differ in the criteria they employ for Black
targets. Community members set a lower, more lenient criterion
for shooting Black targets than either of the two officer samples.
At the same time, officers and community members show similar
levels of bias in terms of the speed with which they can correctly
respond to targets. We have suggested that, by virtue of their
training or expertise, officers may exert control over their behavior, possibly overriding the influence of racial stereotypes. Consistent with the possibility of enhanced control, officers also
showed greater sensitivity than did community members to the
presence of a weapon, regardless of target race. However, we do
not suggest that officers are completely immune to stereotypes. To
the extent that a Black target evokes the concept of danger,
behavioral control should be difficult. Reactions to targets that
violate stereotypic expectancies (i.e., unarmed Black targets and
armed White targets) should be slower than reactions to
stereotype-congruent targets. If officers’ response latencies reflect
the magnitude of racial stereotypes, we might expect greater latency bias for officers exposed to stronger environmental associations between Black people and crime. Community characteristics, such as crime rates and the proportion of minority residents,
might predict the magnitude of bias among officers in the latencies. It is important to note, however, that if officers can exert
control over their behavior, stereotypic associations should not
produce greater bias in the SDT criteria they employ. We used the
questionnaire data to explore this issue. Because there is very little
variance among the Denver officers on these community characteristics (that is, the population of the city and county served by all
officers in Denver is the same, and racial makeup across communities varies minimally), the national officer sample affords a more
effective test of these possibilities.
Correlational analyses. We computed indices of racial bias
on the basis of both response times ([RTunarmed Black target ⫺
RTunarmed White target] ⫹ [RTarmed White target ⫺ RTarmed Black target]),
and criteria (cWhite ⫺ cBlack). Higher numbers indicate greater
racial bias. We also calculated the effect of target race on discriminability (d⬘White ⫺ d⬘Black), with higher numbers representing
greater sensitivity for White targets than for Black targets.
We then conducted exploratory analyses of the relationships
between each of these indices and the questionnaire measures
obtained. We report correlations for all three samples (see Table
1), but again, because the national sample offers greater variability
in terms of community demographics, we focus our discussion on
that sample. Bias in the response times was positively related to the
size (i.e., population) of the city, r(97) ⫽ .31, p ⬍ .003, and
county, r(103) ⫽ .31, p ⬍ .002, in which the officer served
(population variables were log transformed to normalize their
distributions). This effect suggests that officers in larger communities showed greater bias in the latency measure. In addition,
officers’ reports of the level of violent crime in their districts
predicted bias in response latencies, r(111) ⫽ .20, p ⬍ .03, such
that increases in violent crime were associated with greater racial
bias. Officers rated violent crime levels with respect to FBI statistics for the average national violent crime rate (500 offenses per
100,000 persons) on a 5-point scale with the endpoints anchored at
much lower than average and much higher than average. Officers
were also asked to estimate the ethnic makeup of the communities
in which they served. The estimated percentage of both African
Americans, r(108) ⫽ .21, p ⬍ .03, and ethnic minorities more
generally, r(108) ⫽ .22, p ⬍ .03, living in the community positively predicted racial bias in the latencies. None of the remaining
correlations for the national sample of officers was significant.
Officers serving in districts characterized by a large population,
a high rate of violent crime, and a greater concentration of Black
people and other minorities showed increased bias in their reaction
times. We tentatively suggest that these environments may reinforce cultural stereotypes, linking Black people to the concept of
violence. The fact that officers from these urban, violent areas
show more pronounced bias in their latencies suggests that stereotypic associations may indeed influence police on some level. But
if training enables officers to effectively control their behavior,
such stereotypes should not influence their final shoot/don’t-shoot
decisions. It is interesting that these community demographics,
which systematically predicted latency bias, were completely unrelated to bias in the SDT estimates of decision criteria (rs ranged
from ⫺.14 to .13, smallest p value ⫽ .19). In other words,
environmental variables that increased bias in officers’ latencies
had no effect on the degree of bias in their ultimate decisions.
We also asked participants (community members and officers
alike) to complete several measures of stereotyping and prejudice.
In the past, we have obtained relationships between bias in response times and an individual’s awareness of cultural stereotypes
about Black people (Correll et al., 2002, Study 3; Correll, et al.,
2007). In the present study, measures of personally endorsed
stereotypes did correlate with latency bias for the community
members, r(123) ⫽ .21, p ⬍ .05, but cultural stereotypes did not.
Moreover, in the officers’ data, neither of these relationships
emerged. It is possible that this difference reflects something
special about the relationship between stereotypes and bias among
officers, but we suspect that the reason has more to do with the
officers’ concerns about going “on the record” with regard to their
attitudes about race. Despite our assurances of anonymity, several
officers were unwilling to complete the measures, and others told
us, rather bluntly, that they would not respond honestly to these
sensitive questions. We therefore view these items with suspicion,
at least for the officer samples.
The effects of target race on the SDT estimates were not related
to any of the demographic variables. As null effects, these results
are difficult to interpret. They may reflect a true lack of correspondence between demographics and performance, but they may
also stem from the relatively low error rates in this task (which
likely reduce the reliability of the SDT estimates).4 Although
Black–White differences were unrelated to the questionnaire measures, we did find that the average values of both d⬘ and c
(independent of target race) were correlated with training in simulated building searches. In this type of training, officers interact
with actors, some of whom attack the trainee using weapons
4
We thank an anonymous reviewer for this insight.
THIN BLUE LINE
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equipped with nonlethal ammunition. Police with more extensive
training in these encounters were better able to discriminate between armed and unarmed targets, regardless of the race of the
target, r(113) ⫽ .20, p ⬍ .04, and they tended to set a higher
overall criterion in the task, r(113) ⫽ .17, p ⬍ .07, reflecting
greater reluctance to shoot. It is interesting that no other type of
training (e.g., classroom training, firing range, interactive video
training) predicted performance in the game. Future researchers
should attempt to replicate these correlations, but the results tentatively suggest that live, interactive training provides officers with
a chance to hone their skills in a manner that improves performance.
Discussion
Analyses of the behavioral data showed that the officers’ overall
performance on the video game simulation exceeded that of the
civilians in several ways. First, their response times were faster.
On average, officers were simply quicker to make correct shoot/
don’t-shoot decisions than were civilians. Second, they were better
able to differentiate armed targets from unarmed targets. On average (i.e., across White and Black targets), d⬘ was greater for the
officers than for the community sample. Third, whereas the criterion c for the community was significantly below zero (reflecting
a tendency to favor the “shoot” response), officers adopted a more
balanced criterion. In fact, not only was the officers’ criterion
significantly higher than the community’s, but the officers’ threshold also did not differ significantly from zero. This placement
suggests equal use of the “shoot” and “don’t shoot” responses.
In terms of bias, the SDT results suggest that officers may show
less bias than civilians in their final decisions. Among the community sample, these data revealed a clear tendency to set a lower
(i.e., more lenient or “trigger-happy”) criterion for Black, rather
than White, targets. But this bias was weaker, or even nonexistent,
for the officers. The reduction in bias seemed to reflect the fact
that, compared with the community members, officers set a higher,
more stringent threshold for the decision to shoot Black targets.
Placement of the criterion for White targets varied minimally
across the three samples.
The response-time data show clear evidence of racial bias for all
samples in this study, the 237 police officers and the community
members alike. Like college students in previous studies, these
individuals seemed to have greater difficulty (indexed by longer
latencies) responding to stereotype-incongruent targets (unarmed
Black targets and armed White targets), rather than to stereotypecongruent targets. The magnitude of this bias did not differ across
the three samples. It is interesting to note that this equivalence
emerged in spite of the fact that the civilian sample contained
many more ethnic minority members than did the predominantly
White police samples. Although any evidence of racial bias among
police may be cause for concern, there is certainly nothing in the
present data to suggest that officers show greater bias than the
people who live in the communities they serve.
We used correlational analyses to examine officers in the national sample, and, of all the variables examined, three predicted
bias in reaction times (no variables related to bias in the decision
criteria). Each of the relevant variables reflected some aspect of the
community the officer served. Bias increased as a function of the
community’s size, crime rate, and the proportion of Black resi-
1015
dents and other ethnic minority residents. Police in larger, more
dangerous and more racially diverse environments are presumably
much more likely to encounter Black criminals, reinforcing the
stereotypic association between race and crime. By contrast, officers with little exposure to Black people may be less likely to
rehearse this association. As a consequence, these officers may
experience less stereotypic interference during the video game
task.
The results from the signal-detection analysis are particularly
provocative. Although police may have difficulty processing
stereotype-inconsistent targets (as evidenced by bias in their response times), the SDT results suggest that police do not show bias
in their ultimate decisions. That is, the expertise that police bring
to a shoot/don’t-shoot situation may not eliminate the difficulty of
interpreting a stereotype-inconsistent target, but it does seem to
minimize the otherwise robust impact of target race on the decision
to shoot. Inasmuch as it is the actual decision to shoot (and not the
delay in making that decision) that carries life-and-death consequences for the suspect, bias in the criterion may be considered the
variable of greatest interest to both the police and the community.
However, because of the profound implications of these conclusions, we felt it necessary to replicate these effects. The video
game used in Study 1 imposed an 850-ms timeout window. Although this restriction certainly exerts some pressure on participants, it offers them sufficient time to respond correctly on the vast
majority of trials. In Study 1, errors and timeouts, together, accounted for only 9.5% of trials. When the total number of errors is
so low, idiosyncratic responses to particular targets may dramatically affect the SDT estimates. In Study 2, therefore, we reduced
the time window in an effort to increase errors and obtain more
stable SDT estimates.
Study 2
Method
Participants. We returned to one police district in Denver and
recruited an additional 33 officers, as well as 52 community
members from a nearby DMV, each of whom completed a version
of the video game simulation with a more restrictive time window.
Several participants experienced great difficulty responding within
this limit, producing few errors and a very high number of timeouts. Two officers and 7 civilians had an excessive ratio of
timeouts to incorrect trials (more than four timeouts for every
error) and were excluded from the analyses. The results do not
change substantially if they are included. The final sample included 31 officers (3 female, 26 male, 2 missing gender; 16 White,
6 Black, 4 Latina/o, 3 other, 2 missing ethnicity; mean age ⫽ 35.6
years) and 45 community members (20 female, 23 male, 2 missing
gender; 14 White, 18 Black, 10 Latina/o, 3 other; mean age ⫽ 36.8
years). Officers completed the study while off duty and were paid
$50 in compensation. Community members were paid $20.
Video game simulation and procedure. The video game was
identical to that in Study 1, with the exception that the timeout
window was set to 630 ms. Participants were instructed to respond
as quickly and as accurately as possible, and response latencies
longer than 630 ms were penalized with a loss of 20 points.
Otherwise, the procedures were identical to those in Study 1.
1016
CORRELL ET AL.
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Results
Our goal in reducing the timeout window was to induce a
greater number of errors. Our analysis therefore focused on the
parameters derived from the signal-detection analysis. Errors were
substantially greater in this version of the simulation. Overall,
participants made incorrect responses on 16% of the 100 trials and
timed out on 17%. We computed sensitivity (d⬘) and the decision
criterion (c) as in Study 1, using only the correct and incorrect
trials (i.e., excluding timeouts). The estimates were analyzed in a
Sample (officer vs. civilian) ⫻ Target Race (Black vs. White) 2 ⫻
2 mixed-model ANOVA, with repeated measures on the latter
factor (see Table 2 for means and standard deviations; see also
Figure 3).
Signal-detection analyses. With respect to the criteria or
estimates of c, we observed that the average criterion was
significantly below zero, F(1, 74) ⫽ 27.06, p ⬍ .001. In fact,
the criteria in Study 2 were lower than those in the first study.
Presumably because of the increase in time pressure, participants showed a greater propensity to shoot (compare Figures 1
and 3). More interesting, the location of the criterion depended
on sample, F(1, 74) ⫽ 4.95, p ⬍ .03 (i.e., there was a main
effect of sample). Although the mean value of c was significantly below zero for both the officers, F(1, 30) ⫽ 4.84, p ⬍ .04
(M ⫽ ⫺.10), and the community, F(1, 44) ⫽ 29.38, p ⬍ .001,
(M ⫽ ⫺.24), it was significantly lower for the latter. Unlike in
previous work, the main effect of target race in c was not
Figure 3. Decision criterion placement (c) and sensitivity (d⬘) for Black and White targets as a function of
sample (Study 2).
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THIN BLUE LINE
significant, F ⬍ 1, but the Sample ⫻ Target Race interaction
was, F(1, 74) ⫽ 3.69, p ⫽ .059 (see Figure 3). As in Study 1,
the community sample set a lower threshold to shoot Black
targets than to shoot White targets, F(1, 44) ⫽ 4.24, p ⬍ .05.
Officers, on the other hand, demonstrated no racial bias, F ⬍ 1.
Again replicating Study 1, this interaction seems to reflect the
fact that the community set a lower threshold for Black targets
than did the officers, F(1, 74) ⫽ 9.74, p ⬍ .003. The two
samples did not differ in the placement of their criteria for
White targets, F ⬍ 1. It is also interesting to note that all four
of the mean c values in Figure 3 were significantly below zero,
all ts ⬍ ⫺2.17, ps ⬍ .04, with the exception of the officers’
criterion for Black targets, t(30) ⫽ ⫺1.36, p ⫽ .18.
Turning to sensitivity, we found that d⬘ was generally lower in
Study 2 than in Study 1, particularly for the community members,
suggesting that time pressure impaired discriminability (see Payne,
2001). The main effect of sample was significant, F(1, 74) ⫽
21.59, p ⬍ .001. As in Study 1, police officers more effectively
discriminated between armed and unarmed targets (M ⫽ 2.27) than
did the community members (M ⫽ 1.43). The police advantage
was evident both for Black targets, F(1, 74) ⫽ 26.93, p ⬍ .001,
and for White targets, F(1, 74) ⫽ 10.54, p ⬍ .002. There was no
overall effect of target race on d⬘, F ⬍ 1, suggesting that participants, in general, were equally able to discriminate White and
Black targets. However, target race did interact marginally with
sample, F(1, 74) ⫽ 2.81, p ⬍ .10. Community members were
equally sensitive to both White and Black targets, F ⬍ 1, but
officers showed marginally greater sensitivity for Black, rather
than White, targets, F(1, 31) ⫽ 3.53, p ⫽ .07 (see Figure 3). The
results from Study 1 similarly indicated better sensitivity among
officers than civilians, particularly for the Black targets.
Reaction-time analyses. Previous work has consistently found
that reducing the time window eliminates the race-bias effect in
response times, presumably because it reduces variance in the
latencies (see Correll et al., 2002). Consistent with those findings,
bias in response times was not significant on average in Study 2,
F ⬍ 1, nor did the magnitude of bias depend on sample, F ⬍ 1.
Discussion
Like Study 1, Study 2 revealed critical differences between the
performance of police officers and that of civilians. These differences emerged both in the participants’ ability to discriminate
armed from unarmed targets and in the criterion for the decision to
shoot. Civilians consistently set a lower threshold for the decision
to shoot (c) than did the officers, and this difference was particularly evident for Black targets. In both studies, officers showed
greater sensitivity (d⬘), and again this tended to be particularly true
with Black targets. In sum, then, Study 2 replicated the signaldetection findings of Study 1, and it did so using a paradigm that
forced participants to respond very quickly, resulting in a greater
number of errors and, so, more stable SDT estimates.
Taken together, the response-time results from Study 1 and the
signal-detection results from both Studies 1 and 2 reveal intriguing
differences between trained police officers and civilians who live
in the communities those officers serve. The latencies suggest that
officers and community members both experienced difficulty processing stereotype-incongruent targets. Like community members,
police were slower to make correct decisions when faced with an
1017
unarmed Black man or an armed White man. It is important to
note, however, that the officers differed dramatically from the
civilians in terms of the decisions they ultimately made. Community members showed a clear tendency to favor the shoot response
for Black targets (relative to both White targets and relative to a
neutral or balanced criterion of zero). Police, however, showed no
bias in their criteria. Moreover, they showed greater discriminability and a less trigger-happy orientation in general (i.e., for both
Black and White targets). These results seem to suggest that
expertise improves the outcome of the decision process (increasing
sensitivity and reducing the unwarranted tendency to shoot, particularly for Black targets), even though it may not eliminate
processing difficulties associated with stereotype-inconsistent targets.
We have suggested that this reduction in bias may reflect the
impact of training. In Study 3 we attempted to examine this
possibility more systematically by providing practice on the video
game task to a sample of undergraduates. On the basis of the
results of Studies 1 and 2, we expected that repeated play would
improve sensitivity (facilitating discrimination between armed and
unarmed targets) and reduce racial bias in the placement of the
decision criterion (Plant et al., 2005). But we expected that practice
would not reduce bias in response times. Like the officers, participants with more practice on the task should demonstrate improvements in their ultimate decisions in spite of persistent difficulty
with the processing of stereotype-incongruent targets.
Study 3
Method
Participants. Fifty-eight students (29 female, 22 male, 7 missing gender; 40 White, 1 Black, 3 Asian, 3 Latina/o, 1 Native
American, 2 Other, 8 missing ethnicity) participated in Study 3
either in partial completion of a course requirement or for $15 pay.
Four additional students were included in the original sample but
failed to return for Day 2 and thus are excluded from all analyses.
Video game simulation and procedure. In Study 3, participants played the video game twice on each of 2 days separated by
48 hr. At each round of play, they completed an 80-trial shoot/
don’t-shoot video game, which was essentially the same as the task
performed in Study 1. This game again used a timeout window of
850 ms. Thus, the design included four factors: 2 (Day) ⫻ 2
(Round of Play) ⫻ 2 (Race) ⫻ 2 (Object), with repeated measures
on all four variables. This design allowed us to examine the
effects of repeated play within a day and also to assess whether
any improvement in performance would carry over from Day 1
to Day 2.
Results
We computed SDT estimates and average reaction times for
correct responses as in Studies 1 and 2.
Signal-detection analyses. We analyzed the SDT estimates as a
function of day (1 vs. 2), round of play (1 vs. 2), and target race (Black
vs. White) using 2 ⫻ 2 ⫻ 2 repeated-measures ANOVAs for both c
and d⬘. Analyses of c revealed that, on average, participants set a
lower criterion to shoot for Black targets than to shoot White targets,
F(1, 57) ⫽ 10.76, p ⬍ .002. It is critical, however, that the effect of
1018
CORRELL ET AL.
The analysis of sensitivity, or d⬘, revealed only a main effect of
round, F(1, 57) ⫽ 7.09, p ⬍ .01, reflecting greater discriminability
during the second game each day. No other effects in this analysis
were statistically significant, all Fs(1, 57) ⬍ 1.06, ps ⬎ .30 (see
Figure 4). As predicted, practice enhanced sensitivity and seemed
to have equivalent effects for both Black and White targets. Moreover, the increase in sensitivity occurred each day, and there was
no evidence that the increase carried over from Day 1 to Day 2.
Reaction-time analyses. Latencies were analyzed as a function
of day (1 vs. 2), round of play (1 vs. 2), target race (Black vs.
White), and object type (gun vs. nongun) using a 2 ⫻ 2 ⫻ 2 ⫻ 2
repeated-measures ANOVA. As usual, we observed a main effect
of object, F(1, 57) ⫽ 409.19, p ⬍ .001, such that participants
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race depended on round, F(1, 57) ⫽ 5.08, p ⬍ .03, such that bias
decreased in the latter round each day. That is, the race difference in
the criterion (i.e., bias) was significant at Round 1 on both Day 1,
t(57) ⫽ 2.41, p ⬍ .02, and on Day 2, t(57) ⫽ 2.53, p ⬍ .02. But bias
fell to nonsignificant levels at Round 2 on both days: for Day 1,
t(57) ⫽ 0.17, p ⫽ .86; for Day 2, t(55) ⫽ ⫺0.06, p ⫽ .95 (see Figure
4). Moreover, the Round ⫻ Race interaction did not depend on day,
F(1, 57) ⫽ 0.04, p ⫽ .84. No other effects in this analysis were
statistically significant, all Fs(1, 57) ⬍ 1.04, ps ⬎ .31. As predicted
then, practice reduced bias in the decision to shoot, and it did so on
each of the two days. It is interesting that there appeared to be no carry
over in bias reduction from Day 1 to Day 2. We return to this issue in
the Discussion section.
Figure 4. Decision criterion placement (c) and sensitivity (d⬘) for Black and White targets as a function of day
and round of play (Study 3).
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THIN BLUE LINE
1019
Figure 5. Response times to Black and White armed and unarmed targets as a function of day and round of
play (Study 3).
responded more quickly on gun trials than on nongun trials. This
effect was qualified by an interaction between target race and
object type, F(1, 57) ⫽ 95.65, p ⬍ .001, representing significant
racial bias. Our primary concern, however, involved the degree to
which this pattern changed as participants gained experience with
the task. Most interesting, from our perspective, was the question
of whether repeated play altered the magnitude of racial bias in the
speed with which participants could make shoot/don’t-shoot decisions. In stark contrast to the SDT results, bias in reaction times
did not change as a function of round: The three-way interaction
was not significant, F(1, 57) ⫽ 0.01, p ⫽ .93. Similarly, neither the
Day ⫻ Race ⫻ Object three-way interaction, F(1, 57) ⫽ 0.01, p ⫽
.92, nor the Round ⫻ Day ⫻ Race ⫻ Object four-way interaction
was significant, F(1, 57) ⫽ 0.00, p ⫽ .95. In essence, the magnitude of this bias did not change over the course of the study.
Further, latency bias was significant in both Round 1, F(1, 57) ⫽
33.76, p ⬍ .001, and Round 2, F(1, 57) ⫽ 28.52, p ⬍ .001, on Day
1, as well as Round 1, F(1, 57) ⫽ 27.04, p ⬍ .001, and Round 2,
F(1, 57) ⫽ 17.14, p ⬍ .001, on Day 2 (see Figure 5).5 So although
practice decreased racial bias in the decision criteria and improved
overall discriminability (as shown by the SDT analyses), practice
did not attenuate racial bias in reaction times.
Discussion
Participants in Study 3 showed a number of changes as a
function of practice. Most important, practice with the task reduced SDT bias and increased sensitivity to the presence or absence of a weapon. Practice did not, however, affect the magnitude
of racial bias in latencies. Across repeated plays of the video game
simulation, these developing “experts” continued to struggle with
the stereotype-incongruent targets, responding more slowly on
incongruent (compared with congruent) trials.
The effects of training observed in this study with a sample of
undergraduates largely replicate the differences observed between
police officers and civilians in Studies 1 and 2. Undergraduates in
the initial round of Study 3, like members of the Denver community, showed bias both in latencies and in their criteria for the
decision to shoot. These effects were evident on both Day 1 and
Day 2. After receiving practice on the shoot/don’t-shoot simulation
task, however, bias in the placement of the criterion diminished,
but bias in reaction times did not change. As a consequence of this
shift, our “expert” participants began to look less like community
members and more like police officers.
However, a single round of practice with our video game task
(which takes roughly 12 min–15 min) differs dramatically from the
training that police receive. As noted above, Denver police recruits
spend approximately 72 hr in weapons training during their time at
the academy. This extended, in-depth practice likely results in
much greater consolidation of the skills necessary to exert control
over their behavior than did the minimal practice afforded to
participants in Study 3. Consistent with this, participants in Study
3 showed pronounced within-day improvements (reductions in
bias and increases in discriminability), but they showed no evidence that this training carried over from Day 1 to Day 2. Upon
entering the lab on Day 2 (48 hr after the Day 1 session), partic5
A number of less theoretically interesting effects that did not involve
race and object were present in this analysis. Overall, participants were
faster on Day 2 than Day 1, F(1, 57) ⫽ 46.94, p ⬍ .001, marginally faster
at Round 2 than Round 1, F(1, 57) ⫽ 3.40, p ⫽ .07, and the Day ⫻ Round
interaction was significant, F(1, 57) ⫽ 11.76, p ⬍ .002, such that the
Round 1 to Round 2 decrease in mean latencies was really only present on
Day 1. (It is interesting that this increase in speed again mirrors sample
differences between the police and community participants in Studies 1 and
2.) The object main effect (faster times to gun trials) was qualified by a
number of interactions. The difference in gun versus no-gun trials was
greater on Day 1 than Day 2, F(1, 57) ⫽ 15.69, p ⬍ .001, for the Day ⫻
Object interaction, greater at Round 1 than Round 2, F(1, 57) ⫽ 6.64, p ⬍
.02, for the Round ⫻ Object interaction, and the shift from Round 1 to
Round 2 was really only present on Day 1, F(1, 57) ⫽ 4.16, p ⬍ .05, for
the Day ⫻ Round ⫻ Object interaction. All of these effects reflect
accelerations in classification speed (for all responses or for the particularly
slow no-gun responses). This acceleration is most pronounced at early
stages of the study and weakens over time, presumably because of a floor
effect.
CORRELL ET AL.
1020
ipants behaved like novices. On Round 1 of their second day, they
demonstrated racial bias in both response times and SDT criteria.
With additional training on Day 2, this bias dropped once again.
But the reemergence of bias in Round 1 of Day 2 suggests more
extensive training is necessary if participants are to more permanently overcome bias in behavioral responses. The fact that police
officers in Studies 1 and 2 showed no SDT bias during their initial
performance on the video game task may be a testament to their
training and expertise.
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General Discussion
We began this research with two primary goals: examining
police officers in a first-person shoot/don’t-shoot task and comparing their performance with that of a community sample. This
investigation assessed overall proficiency and the role that a target’s race plays in the decision-making process. Police differed
from the community members in terms of several critical variables.
On average (ignoring target race), the officers clearly outperformed the community sample. They were faster to make correct
responses; they were better able to detect the presence of a weapon
(as measured by d⬘); and they set a significantly higher criterion (c)
for the decision to shoot, indicating a less “trigger-happy” orientation.
Most important for our hypothesis, the officers also differed
from the community sample in the role that a target’s race played
in the placement of SDT criteria for the decision to shoot. This
difference primarily affected Black targets. When the target was
White, all of the samples (Denver community, Denver police, and
national police) set a relatively high criterion, and none of the
samples differed from one another. But when the target was Black,
the community set a significantly lower (more trigger-happy)
criterion than the officers. This was true both in Study 1, which
used a relatively long timeout window, and in Study 2, in which
the timeout window was substantially reduced (yielding much
higher error rates).
In spite of the fact that police showed minimal bias in the SDT
analysis, the officers were similar to the community sample (and to
literally hundreds of past participants in this paradigm) in the
manifestation of robust racial bias in the speed with which they
made shoot/don’t-shoot decisions. Accurate responses to targets
congruent with culturally prevalent stereotypes (i.e., armed Black
targets and unarmed White targets) required less time than did
responses to stereotype-incongruent targets (i.e., unarmed Black
targets and armed White targets). Evidence of bias in response
latencies was consistent and robust across all of the samples
examined in Study 1: the national sample and the Denver sample
of police officers, as well as the Denver community sample, drawn
from the neighborhoods that the Denver officers serve.
The results from Study 3, in which we trained novice college
students on the task, revealed similar effects. Across two rounds of
play, student participants showed a significant decrease in racial
bias, as measured by the decision criterion, accompanied by an
increase in sensitivity. But they showed no change in the magnitude of bias as measured by response latencies. An identical
pattern was obtained when students returned for a second day,
during which they again completed two rounds of the video game
task. In the first round of play, student performance mirrored that
of the community; By Round 2, it mirrored that of the police
officers.
The performance of the officers and the expert students in these
studies raises an important set of questions about the processes that
differentiate bias in response times from bias in the threshold to
shoot. Typically, errors and latencies follow a similar pattern, such
that greater difficulty on a given trial increases both response time
and the likelihood of a mistake, as observed in the performance of
community members and novice college students. The officers and
experts, by contrast, showed clear bias in latencies, but target race
had no impact on their ultimate decisions.
To the extent that longer latencies reflect difficulty, the persistent bias in reaction times suggests that even experts have some
trouble processing stereotype-incongruent targets. The visual complexity of the stimuli may essentially require participants to engage
in an effortful, serial search for relevant information about the
object (Shiffrin & Schneider, 1977). At the same time, the salience
and automaticity that generally characterize psychological processing of racial cues (Cunningham et al., 2004; Ito & Urland,
2003) suggest that— during the course of that search—participants
are likely to encode target race. In combination with tenacious
racial stereotypes (e.g., Devine & Elliot, 1995), race-based processing may impede responses to counterstereotypic targets. In line
with this possibility, Study 1 showed that officers from urban,
high-crime, predominantly minority districts (environments likely
to reinforce stereotypes about Black people) showed greater racial
bias in their latencies.
For officers (and, temporarily, for trained undergraduates), however, the stereotypic interference ended with reaction times. The
bias evident in their latencies did not translate to the decisions they
ultimately made. This separation of effects may reflect the officers’ ability to override automatic associations (Kunda & Spencer,
2003), perhaps as a function of their training and expertise. Police
(with extensive training) and “expert” undergraduates (with minimal training) were able to reduce bias in the SDT criteria for
Black and White targets. Were these individuals able to avoid snap
judgments on ambiguous trials, such as those posed by counterstereotypic targets, and wait for a more complete understanding?
Such a delay when responding to difficult-to-process counterstereotypic targets would presumably yield bias in reaction times
(consistent with the data). At the same time, it would minimize
bias in the decision criteria and increase overall accuracy. Anecdotally, this explanation matches officers’ intuitions about the
process. In a conversation about the effects reported here, one
officer stated that the findings “make sense” because police are
trained to hold their fire if they are uncertain – to wait for greater
clarity.
The possibility that expertise and practice enhance control resonates with research beyond the realm of racial stereotyping.
Green and Bavelier (2003) have shown that practice with visually
complex video games enhances visual attention (but practice with
visually simple games does not). And, although practice on a
simple decision task generally promotes automaticity (Bush et al.,
1998; Shiffrin & Schneider, 1977), practice on more complicated
interference tasks or on challenging working-memory tasks can
actually increase control (Olesen et al., 2004; Weissman et al.,
2002). On the basis of functional magnetic resonance imaging,
these studies show that extended practice on difficult tasks leads to
increased activation of the medial and middle frontal gyri—areas
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THIN BLUE LINE
associated with control-based conflict resolution and top-down,
rule-based processing. We suggest, then, that police training and
on-the-job experience in complex encounters may allow officers to
more effectively exert executive control in the shoot/don’t-shoot
task, essentially overriding response tendencies that stem from
racial stereotypes. As noted above, the correlational analyses from
Study 1 identified several environmental factors that were associated with increases in latency bias for the officers (i.e., serving in
urban, high-crime, and predominantly minority districts). It is
interesting to note that these same variables had no impact on the
SDT criteria the officers used.
We do not want to suggest that the minimal training provided in
Study 3 parallels the sort of training that police officers receive.
However, the possibility that police function as highly trained
subjects is intriguing. In the current research, evidence for this
possibility relies on cross-sectional comparisons (Studies 1 and 2)
and on parallels between samples that differ in numerous ways
(i.e., the “expert” students in Study 3 and the police officers). It
would be informative to follow police recruits as they enter the
academy, as they receive training, and as they cope with their first
years of patrol duty. We have begun data collection on such a
project. At present, we have data from 39 recruits in the first weeks
of training at the police academy (prior to any weapons training).
It is striking that these recruits show statistically significant racial
bias in both reaction times and in the decision criteria. Upon
entering the academy, then, recruits behave very much like the
community samples (Studies 1 and 2) and the novice student
sample (Study 3): They set a lower criterion for Black targets than
for White targets. These data are entirely consistent with the
possibility that the reduction in SDT bias among police officers
represents an expertise effect. These data also argue against the
suggestion that police academies or departments indoctrinate their
members into a culture of anti-Black sentiment (Teahan, 1975a), at
least with respect to the sort of judgments studied here.
We must note that our results are only partially consistent with
prior work. Consistent with Eberhardt et al. (2004), we found that
officers orient more quickly to Black people when processing
danger-related stimuli. With respect to reaction times, our results
(like theirs) suggest a bias in attentional focus and processing. But
our data are not consistent with those of Plant and Peruche (2005),
who found that officers showed racial bias in the SDT criteria for
the decision to shoot. Although these officers learned to eliminate
bias over the course of the study, the presence of the initial bias is
inconsistent with our results. Officers in the current studies never
showed significant evidence of bias.6
This partial correspondence may stem from a variety of factors.
We explore two. First, Plant and Peruche (2005) sampled 50
officers from Florida; in Study 1, we sampled 237 officers from
Colorado and 14 other states. It is possible that the differences
between our findings reflect regional differences between Florida
and other areas of the country. Second, it is possible that the results
reflect differences between the paradigms employed. Plant and
Peruche’s stimuli are, arguably, further removed from the training
and experience of police officers than are the stimuli presented in
our simulation. Plant and Peruche presented Black and White male
faces on which objects (e.g., a gun or wallet) had been superimposed. Our stimuli involve full-body images of men holding guns
and other objects. These images are embedded in scenes, such as
parks or cityscapes. To the extent that our stimuli more closely
1021
mirror police training (e.g., Firearms Training System or firing
range encounters) and on-the-job experiences, an officer’s expertise should be more likely to generalize to our task. To the extent
that Plant and Peruche’s paradigm is less similar to the officers’
previous experiences, their participants may have had to learn what
was, in essence, a novel task.
As we discussed in the introduction, sociologists have studied
the question of racial bias in police shootings for many years. The
sociological literature provides a rich, if complicated, context in
which to view the results of the current studies. One account that
has received substantial attention is that police shoot Black suspects more often than White suspects, per capita, because Black
people are disproportionately likely to be involved in crime (particularly violent crime). The Department of Justice (2001) report
shows that, just as Black suspects are five times more likely than
White suspects to die at the hands of police, police officers are five
times more likely to die at the hands of a Black suspect than a
White suspect. In a similar vein, Reisig et al. (2004) found that the
use of nonlethal force (which seems to depend on suspect race)
may actually reflect race-based differences in the suspect’s propensity to resist arrest or engage in belligerent behavior toward
officers. It is the suspect’s hostility, they argue—not race—that
prompts a hostile response from the officer. And Inn et al. (1977)
report that the number of Black suspects shot by police is proportionate to the number of Black suspects arrested. They tentatively
conclude that it is the prevalence of criminal activity among Black
people that drives the differential shooting rates. (The authors note,
however, that arrest rates themselves may reflect biases held by the
police and thus do not provide a perfect standard of comparison.)
In line with this reasoning, in Study 1, officers from the national
sample who reported working in communities with (a) high levels
of violent crime and (b) high proportions of minority residents
showed particularly strong patterns of bias in their latencies. Did
their experiences with minority suspects foster associations that
made counterstereotypic trials particularly difficult to process?
The situation is almost certainly more complex. It is clear from
the analysis of Study 1 that officers serving in heavily (more
densely) populated communities also showed greater anti-Black
bias in their reaction times. In combination, these variables seem to
suggest that racial bias in the decision to shoot may reflect the
disproportionate representation of Black people (and perhaps other
ethnic minority groups) in low-income, poverty-stricken, and highcrime areas. Geller (1982) and Smith (2004) presented evidence
that a greater number of police shootings occur in disadvantaged
neighborhoods and that members of ethnic minorities are more
likely to be killed in these incidents. Using regression models to
predict officer-involved shootings, Terrill and Reisig (2003)
showed that, once neighborhood risk is taken into account, the
6
In light of Plant and Peruche’s (2005) findings, we explored the
possibility that police officers in the current studies showed a decrease in
bias over the course of the shooter task. To examine this possibility, we
reanalyzed the data from Studies 1 and 2, separating the 100 trials into two
50-trial blocks and analyzing SDT estimates (both c and d⬘) as a function
of sample, target race, and block (first half vs. second half). Neither
three-way interaction was significant, and controlling for block did not
alter the findings reported in the text. These data provide no evidence that
police showed less bias than community members because they were better
able to improve their performance over the course of the task.
CORRELL ET AL.
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1022
effect of suspect race or ethnicity is no longer statistically reliable.
This research builds on the ecological contamination hypothesis,
first advanced by Werthman and Piliavin (1967), which suggests
that the reputation of a neighborhood distorts perceptions of its
inhabitants. To the extent that a community is seen as a “bad area,”
police may perceive the individuals who live there (or anyone they
happen to encounter there) as a potential threat. If members of
minorities are more likely to live and spend time in disadvantaged
neighborhoods (Sidanius & Pratto, 1999), they may also be more
likely to fall victim to this context-based contamination. As a
consequence, police may be more likely to shoot a Black suspect
because of the context in which the encounter occurs, not because
of racial bias, per se (Fyfe, 1981). In an interesting wrinkle of this
argument, Sampson and Raudenbush (2004) conducted an extensive investigation of the factors that predict perceived community
disorder—the causal variable proposed by ecological contamination. They found that the mere presence of Black people in a
community is sufficient to evoke the perception of disadvantage.
That is, controlling for objective factors (e.g., prevalence of graffiti, broken windows, and abandoned buildings), the greater the
number of Black people living in an area, the greater the disorder
perceived by both Black and non-Black citizens. If Black people
evoke the perception of neighborhood disadvantage, they may
experience harsher treatment by police—not because the police are
biased to treat Black people in a hostile fashion, but because Black
neighborhoods seem more threatening.
The data presented here suggest that, although police officers
may be affected by culturally shared racial stereotypes (i.e., showing bias in their response times), they are no more liable to this bias
than are the people who live and work in their communities.
Further, at least on the simulation used here, the officers’ ultimate
decisions about whether or not to shoot are less susceptible to
racial bias than are the decisions of community members. The data
suggest that the officers’ training and/or expertise may improve
their overall performance (yielding faster responses, greater sensitivity and reduced tendencies to shoot) and decrease racial bias in
decision outcomes. We feel that this research represents a valuable
melding of basic social psychological processes with an issue of
great importance to our society. By examining the influence of
race in the automatic processing of danger-related stimuli, and the
capacity of expertise to moderate this effect, these findings touch
on a topic of great interest to social psychologists, sociologists,
police, and community groups, alike. The investigation of racial
bias in police use of force presents a unique opportunity to apply
experimental social psychological methods to an issue that is vital
to the members of increasingly diverse neighborhoods and communities.
References
Amodio, D. M., Harmon-Jones, E., Devine, P. G., Curtin, J. J., Hartley,
S. L., & Covert, A. E. (2004). Neural signals for the detection of race
bias. Psychological Science, 15, 88 –93.
Birnboim, S. (2003). The automatic and controlled information-processing
dissociation: Is it still relevant? Neuropsychology Review, 13, 19 –31.
Bush, G., Whalen, P. J., Rosen, B. R., Jenike, M. A., McInerney, S. C.,
Rauch, S. L. (1998). The counting Stroop: An interference task specialized for functional neuroimaging—Validation study with functional
MRI. Human Brain Mapping, 6, 270 –282.
Christopher, W. (1998). Report of the Independent Commission on the Los
Angeles Police Department. Darby, PA: DIANE Publishing.
Cohen, J. D., MacWhinney, B., Flatt, M., & Provost, J. (1993). PsyScope:
An interactive graphic system for designing and controlling experiments
in the psychology laboratory using Macintosh computers. Behavior
Research Methods, Instruments, & Computers, 25, 257–271.
Correll, J., Park, B., Judd, C. M., & Wittenbrink, B. (2002). The police
officer’s dilemma: Using ethnicity to disambiguate potentially threatening individuals. Journal of Personality and Social Psychology, 83,
1314 –1329.
Correll, J., Park, B., Judd, C. M., & Wittenbrink, B. (2007). Stereotypes
and racial bias in the decision to shoot. Manuscript submitted for
publication.
Correll, J., Urland, G. L., & Ito, T. A. (2006). Event-related potentials and
the decision to shoot: The role of threat perception and cognitive control.
Journal of Experimental Social Psychology, 42, 120 –128.
Cunningham, W. A., Johnson, M. K., Raye, C. L., Gatenby, J. C., Gore,
J. C., & Banaji, M. R. (2004). Separable neural components in the
processing of Black and White faces. Psychological Science, 15, 806 –
813.
Department of Justice. (2001). Policing and homicide, 1976 –98: Justifiable homicide by police, police officers murdered by felons (NCJ
180987). Washington, DC: Bureau of Justice Statistics.
Devine, P. G., & Elliot, A. J. (1995). Are racial stereotypes really fading?
The Princeton trilogy revisited. Personality and Social Psychology Bulletin, 21, 1139 –1150.
Eberhardt, J. L., Goff, P. A., Purdie, V. J., & Davies, P. G. (2004). Seeing
black: Race, crime, and visual processing. Journal of Personality and
Social Psychology, 87, 876 – 893.
Fyfe, J. J. (1981). Who shoots? A look at officer race and police shooting.
Journal of Police Science and Administration, 9, 367–382.
Geller, W. A. (1982). Deadly force: What we know. Journal of Police
Science and Administration, 10, 151–177.
Green, C. S., & Bavelier, D. (2003, May 29). Action video game modifies
visual selective attention. Nature, 423, 534 –537.
Greenwald, A. G., Oakes, M. A., & Hoffman, H. G. (2003). Targets of
discrimination: Effects of race on responses to weapons holders. Journal
of Experimental and Social Psychology, 39, 399 – 405.
Hamilton, D. L., & Trolier, T. K. (1986). Stereotypes and stereotyping: An
overview of the cognitive approach. In J. F. Dovidio, & S. L. Gaertner
(Eds.), Prejudice, discrimination, and racism (pp. 127–163). San Diego,
CA: Academic Press.
Inn, A., Wheeler, A. C., & Sparling, C. L. (1977). The effects of suspect
race and situation hazard on police officer shooting behavior. Journal of
Applied Social Psychology, 7, 27–37.
Ito, T. A., & Urland, G. R. (2003). Race and gender on the brain:
Electrocortical measures of attention to the race and gender of multiply
categorizable individuals. Journal of Personality and Social Psychology,
85, 616 – 626.
Jansma, J. M., Ramsey, N. F., Slagter, H. A., & Kahn, R. S. (2001).
Functional anatomical correlates of controlled and automatic processing.
Journal of Cognitive Neuroscience, 13, 730 –743.
Kelly, A. M. C., & Garavan, H. (2004). Human functional neuroimaging of
brain changes associated with practice. Cerebral Cortex, 15, 1089 –
1102.
Kunda, Z., & Spencer, S. J. (2003). When do stereotypes come to mind and
when do they color judgment? A goal-based theory of stereotype activation and application. Psychological Bulletin, 129, 522–544.
MacLeod, C. M. (1998). Training on integrated versus separated Stroop
tasks: The progression of interference and facilitation. Memory & Cognition, 26, 201–211.
MacLeod, C. M., & Dunbar, K. (1988). Training and Stroop-like interference: Evidence for a continuum of automaticity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14, 126 –135.
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