Determine the cost factors (distance, weight, and destiny) that may influence the cost of goods.
Question 1 (Due Friday)
I am stakeholder in a Fortune 50 company. You will need to build a business case demonstrating why the project is needed in one of those Fortune 50 companies that you selected and what the benefits of the project will be when completed.
Sections that are usually required in a business case are:
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Order Paper Now1. Executive Summary
2. Introduction
3. Statement of the problem
4. Analysis
5. Discussion of Possible Options
· The benefits: why it would be a good idea to do it, including how far it addresses the problem;
· The costs, including resource requirements. It’s often helpful to include figures and graphs here;
· The likely time-scale for the project, and to see a return on the investment, with reasons; and
· The risks, both of doing it, and that might prevent successful implementation.
As far as possible, these should be realistic, and preferably supported by solid data. Where you have estimated, this should be based on a reasonable source, which you should cite if possible.
6. Recommendation
7. Details of your Chosen Option
Question 2 (Due Thursday)
Identify a company on the Internet that use at least two mode of transporting goods.
Determine the cost factors (distance, weight, and destiny) that may influence the cost of goods.
Does the company have warehousing for their goods (Is it for general or distribution)?
Make sure you provide source(s).
Question 3 (Due Monday)
See research article attached (Prejudice From Thin Air)
Identify in the article:
What type of control techniques used?
If any what are the counterbalancing, participant and experimental effects
Research Article
Prejudice From Thin Air The Effect of Emotion on Automatic Intergroup Attitudes David DeSteno,1 Nilanjana Dasgupta,2 Monica Y. Bartlett,1 and Aida Cajdric1
1 Northeastern University and
2 University of Massachusetts–Amherst
ABSTRACT—Two experiments provide initial evidence that spe-
cific emotional states are capable of creating automatic prej-
udice toward outgroups. Specifically, we propose that anger
should influence automatic evaluations of outgroups because of
its functional relevance to intergroup conflict and competition,
whereas other negative emotions less relevant to intergroup
relations (e.g., sadness) should not. In both experiments, after
minimal ingroups and outgroups were created, participants
were induced to experience anger, sadness, or a neutral state.
Automatic attitudes toward the in- and outgroups were then
assessed using an evaluative priming measure (Experiment 1)
and the Implicit Association Test (Experiment 2). As predicted,
results showed that anger created automatic prejudice toward
the outgroup, whereas sadness and neutrality resulted in no
automatic intergroup bias. The implications of these findings for
emotion-induced biases in implicit intergroup cognition in par-
ticular, and in social cognition in general, are considered.
Since the heyday of frustration-aggression and scapegoating theories
of prejudice (e.g., Dollard, Doob, Miller, Mowrer, & Sears, 1939),
social psychologists have recognized that intergroup relations, and the
stereotypes and prejudices that inevitably accompany them, are in-
fluenced by perceivers’ emotional states. As in the case of attitudes
more generally, emotions have been found to influence when, and to
what extent, people express positive or negative attitudes toward, and
beliefs about, members of in- and outgroups (Bodenhausen, Muss-
weiler, Gabriel, & Moreno, 2001; Fiske, 1998; cf. Petty, DeSteno, &
Rucker, 2001). For example, anger and happiness are known to en-
hance heuristic processing of social information that, in turn, ex-
acerbates stereotypic judgments of outgroups (Bodenhausen, Shep-
pard, & Kramer, 1994; Tiedens & Linton, 2001). Sadness, however,
has been shown to promote systematic processing of information that,
in turn, decreases stereotypic judgments (Lambert, Khan, Lickel, &
Fricke, 1997). These and similar findings have led to wide
acceptance of the view that specific emotions can influence people’s
beliefs about social groups.
It is important to note, however, that thus far, the growing corpus of
research on emotion and intergroup cognition has focused exclusively
on the effects of emotion on self-reported, or explicit, judgments of
social groups (for a review, see Bodenhausen et al., 2001). Such
judgments involve conscious deliberation and are, therefore, clearly
under perceivers’ voluntary control. Indeed, if people suspect that
incidental emotion may unduly influence an unrelated judgment, they
often correct for the perceived bias (Lambert et al., 1997; cf. DeSteno,
Petty, Wegener, & Rucker, 2000). Moreover, happy individuals, who
typically engage in heuristic processing, are able to process system-
atically when instructed to do so (Queller, Mackie, & Stroessner,
1996) or when counterstereotypic information motivates them to do so
(Bless, Schwarz, & Wieland, 1996). Such control, however, is not
available for all types of judgments, especially automatic ones (Banaji
& Dasgupta, 1998; Greenwald & Banaji, 1995). In the domain of
intergroup cognition, automatic attitudes stand as an unconscious
analogue to self-reported or conscious attitudes; that is, they rep-
resent evaluations of social groups whose initiation and modification
typically operate without volitional control (Fazio & Towles-Schwen,
1999; Greenwald & Banaji, 1995). Understanding the conditions that
lead to the formation and exacerbation of automatic prejudice is im-
portant not only because of its pervasiveness, but also because of
accumulating evidence that automatic prejudice does not remain
confined to mental life—it diffuses into people’s behavior toward
outgroup members (Dovidio, Kawakami, & Gaertner, 2002; Fazio,
Jackson, Dunton, & Williams, 1995; McConnell & Leibold, 2001).
We believe that people’s emotional states at the time of intergroup
judgment ought to influence their automatic evaluations of social
groups by moderating or even creating intergroup biases outside of
awareness. This hypothesis stems from a functional view of emotions
as phenomena designed to increase adaptive responding to en-
vironmentally significant stimuli (Damasio, 1994; Keltner & Gross,
1999; LeDoux, 1996). 1 From an adaptiveness standpoint, it seems
The first two authors contributed equally to this work. Address correspondence to David DeSteno, Department of Psychology, Northeastern University, Boston, MA 02115, e-mail: d.desteno@ neu.edu, or to Nilanjana Dasgupta, Department of Psychology, Tobin Hall, 135 Hicks Way, University of Massachusetts, Amherst, MA 01003, e-mail: dasgupta@psych.umass.edu.
1 The influence of emotion on cognition and behavior is theorized to produce
adaptive responses that prepare organisms to meet environmental challenges. However, the influence of emotions may also diffuse into new situations; that is, a preexisting or incidental emotion may influence interactions with a sub- sequent target (cf. Bodenhausen et al., 2001; Petty et al., 2001). Any biases that stem from the influence of incidental emotions on judgments of subsequent targets need not represent an adaptive response.
PSYCHOLOGICAL SCIENCE
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reasonable to expect that specific emotions should facilitate people’s
ability to evaluate social groups quickly and automatically, as well as
slowly and carefully. We predict that to the extent that outgroups often
signify sources of conflict, competition, or blockage of goals (Brewer &
Brown, 1998; Neuberg & Cottrell, 2002), and to the extent that
emotions help individuals meet environmental challenges by acti-
vating goal-driven action tendencies (Frijda, 1986; LeDoux, 1996),
emotions that prepare organisms to meet challenges related to conflict
or competition (e.g., anger) should bias automatic intergroup evalua-
tions in accord with these functional goals.
EMOTION AND AUTOMATIC INTERGROUP ATTITUDES
Although no evidence directly bears on this hypothesis, findings from
three lines of research lend credence to the idea that emotion ought to
shape automatic attitudes toward social groups. First, cognitive neu-
roscience research has begun to identify subcortical structures in-
volved in automatic evaluative appraisals of social groups (Phelps
et al., 2000) and has found these structures to be reciprocally linked
to both cortical and subcortical regions of the brain involved in the
experience of emotion (Ochsner, Bunge, Gross, & Gabrieli, 2002).
Such reciprocal pathways suggest not only that automatic appraisals of
particular stimuli can trigger emotion, but also that extant emotional
states can influence subsequent appraisals. Given these linkages, it is
possible that an emotional state renders individuals more vigilant
against certain threats in the environment and that such vigilance
modulates subsequent automatic evaluations of relevant social stim-
uli. Because automatic evaluations facilitate rapid responses when
strategic analysis is unavailable, it seems reasonable to expect that
these responses may be an important medium through which emotions
allow organisms to meet environmental challenges; for example, cer-
tain emotion-driven automatic responses may act as the first line of
defense against threatening stimuli.
Second, the functional view of emotion readily extends into the
realm of intergroup relations. Recent work has begun to find that
appraisals of social groups evoke specific emotional states, goals, and
action tendencies that facilitate the successful negotiation of group
interactions (Mackie & Smith, 2002). Given this link between social
groups and specific emotions, it is conceivable that the experience of
such emotions, even when their source is incidental to intergroup
relations, may influence people’s perceptions of in- and outgroups in
accord with their functional significance.
Finally, for emotion-based moderation of automatic intergroup at-
titudes to occur, such attitudes must show some degree of flexibility.
Recent research has supported this view, providing evidence that
automatic beliefs and attitudes toward groups are not as immutable as
previously theorized, but rather are quite sensitive to external cues
such as social context (Dasgupta & Greenwald, 2001; Wittenbrink,
Judd, & Park, 2001). Consequently, emotion, given its context-rel-
evant signaling value, ought to act as an internal cue capable of
moderating automatic intergroup attitudes.
EXPERIMENT 1
We used a minimal-group procedure to provide an initial test of the
hypothesis that specific emotions can bias automatic attitudes toward
social groups. Minimal groups provided a clean assessment of the
primary hypothesis because participants had no preexisting attitudes
or emotional reactions toward them. Thus, any automatic preference
for one group over another could be interpreted as a new attitude. 2 To
the extent that outgroups signify sources of conflict and competition,
they may evoke feelings of anger and contempt (cf. Brewer & Brown,
1998; Neuberg & Cottrell, 2002). We propose that just as anger can
originate from current interactions with groups, so may incidental
feelings of anger from an unrelated situation affect automatic ap-
praisals of social groups in a subsequent situation because the emo-
tion signals a hostile environment and prepares individuals to act
accordingly. Specifically, we propose that incidental feelings of anger
are likely to increase automatic bias against an outgroup because
anger increases negativity toward the outgroup, decreases positivity,
or both. According to a functionalist perspective, the emergence of
outgroup bias should be specific to feelings of anger as opposed to
other negative emotions that are typically less relevant to intergroup
relations (e.g., sadness). To examine this hypothesis, we assigned
participants to minimal groups, induced one of three emotional states
(i.e., anger, sadness, neutrality), and then assessed participants’ au-
tomatic attitudes toward these groups with an evaluative priming task.
Method
Participants
A community sample of 87 New York City residents (50 females, 37
males) participated in exchange for $10.
Manipulations and Measures
Creation of Minimal Groups. To create minimal groups, we had par-
ticipants complete a bogus personality test in which they estimated
the frequency of various events (e.g., ‘‘How many people ride the New
York subway every day?’’). After they completed the test, the computer
ostensibly analyzed their responses and informed them that they were
either an ‘‘overestimator’’ or an ‘‘underestimator.’’ In reality, each
participant had been randomly assigned to one of these two groups. To
ensure that participants remembered their group membership
throughout the experiment, we instructed them to wear wristbands
designating their group: red wristbands for underestimators and blue
ones for overestimators. Participants were then shown pictures of 6
ingroup members and 6 outgroup members. 3 The backdrops of these
pictures were color-coded red for underestimators and blue for over-
estimators. By matching participants’ wristbands to the color of the
photographs, we sought to make group membership readily rec-
ognizable by a visually salient characteristic.
Assessment of Automatic Intergroup Attitudes. An evaluative priming
task was used to measure automatic intergroup attitudes (elements of
this priming task were borrowed from Fazio et al., 1995, and Payne,
2001). In the first block of 12 trials, participants categorized the
pictures of in- and outgroup members that they had seen previously
during the minimal-group assignment procedure as belonging to the
2 There is debate about whether evaluative biases captured by response la-
tency measures ought to be interpreted as personal attitudes or as cultural associations learned by exposure to particular stimulus pairings in the en- vironment (Karpinski & Hilton, 2001). The evaluative biases captured in the present experiments cannot be attributed to cultural associations given that the target stimuli were experimentally created minimal groups.
3 Individual pictures assigned to the overestimator and underestimator
groups were counterbalanced.
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ingroup (‘‘us’’) or outgroup (‘‘them’’). These images were presented one
at a time in a random order and later served as target stimuli. In the
second block of 12 trials, participants learned to classify valenced
words as good or bad; these later served as primes. The third block of
24 trials allowed participants to practice the standard evaluative
priming procedure. In each priming trial, several stimuli were pre-
sented in rapid succession in the following order: (a) an orienting
stimulus (n) for 500 ms, (b) a word prime for 200 ms, (c) a target
picture for 200 ms, and (d) a gray mask that stayed on screen until
participants pressed the appropriate key on a computer keyboard to
indicate whether the target picture belonged to their ingroup (‘‘us’’) or
outgroup (‘‘them’’). A 500-ms pause separated individual trials. Par-
ticipants were instructed to attend to all stimuli presented on screen,
but to categorize only the pictures. For each trial, the prime and target
were selected randomly from a pool of 12 primes and 12 targets. Once
practice was over, participants experienced the emotion induction
(described in the next paragraph). They then completed two blocks of
45 data-collection trials each, received a second round of the emotion
induction, and finally completed two more blocks of 45 data-collection
trials (total of 180 critical trials).
Emotion Induction. The emotion-induction task was introduced as a
study of people’s memories. Participants were asked to write in detail
about an autobiographical event from the past that had made them
very angry, very sad, or emotionally neutral (control condition). The
duration of the initial writing task was 4 min. Participants were told
that they would have an opportunity later to continue writing about
their memory. In the second round of the induction procedure, par-
ticipants were told to continue writing from where they had left off for
another 2 min. 4
Emotion Manipulation Check. Emotional states were assessed using
5-point adjective rating scales known to tap sadness and anger
(DeSteno et al., 2000). The anger subscale consisted of angry, an-
noyed, frustrated, and irritated (a 5 .90). The sadness subscale con- sisted of sad, gloomy, and down (a 5 .91).
Procedure
Participants arrived at the lab for what they thought was an experi-
ment on people’s personalities. They first completed the minimal-
group assignment task, which they believed to be a measure designed
to determine their personality type. Immediately following this ma-
nipulation, participants completed the evaluative priming task, which
served as a measure of their automatic attitudes toward the ingroup
and outgroup. This task was introduced as a measure of ‘‘hand-eye
coordination’’ that was allegedly necessary to serve as a baseline
because of individual differences in people’s speed of responding to
visually presented stimuli. As noted earlier, the emotion induction was
embedded before the first and again before the third data-collection
blocks of this priming task. After the priming task, participants
completed an emotion-manipulation check and were debriefed. All
data were collected and instructions and stimuli presented via com-
puter using MediaLab (Jarvis, 2002) and Inquisit (Draine, 2000).
Results and Discussion
Manipulation Check
The emotion manipulations were successful in producing the expected
3 (emotion-induction condition) � 2 (emotion rating) interaction, F(2, 85) 5 15.04, p < .001. That is, participants in the angry condition
reported more anger (M53.32) than sadness (M52.57), t(30)53.01,
p < .01, d 5 0.54; participants in the sad condition reported more
sadness (M 5 3.28) than anger (M 5 2.36), t(24) 5 3.35, p < .01,
d 5 0.67. Neutral participants reported low levels of both emotions
(Msadness 5 1.40, Manger 5 1.53).
Automatic Attitudes Toward Social Groups
A 3 (emotion) � 2 (prime) � 2 (target) mixed analysis of variance revealed that the experience of specific emotional states differentially
influenced automatic attitudes toward the target groups, as indicated
by the three-way interaction, F(2, 85)52.50, p5 .08 (see Fig. 1). 5 A
Prime � Target interaction emerged among angry participants, in- dicating that, as predicted, the outgroup became a strongly valenced
attitude object, F(1, 30)54.95, p5 .03, d50.57. 6 More specifically,
angry participants were slower to associate positive attributes than
negative attributes with the outgroup, t(30)52.35, p5 .03, d50.42.
There was no difference in the speed with which they associated
positive versus negative attributes with the ingroup (t < 1), indicating
a neutral evaluative stance toward this group. Moreover, as expected,
no intergroup bias (i.e., Prime � Target interaction) emerged for neutral or sad participants (Fs < 1.3). These data suggest that anger
exerted a functional influence on automatic attitudes and, in so doing,
created automatic prejudice where none had previously existed.
However, before placing confidence in this finding, we wanted to at-
tempt a cross-method replication, especially given that the omnibus
test of the three-way interaction did not reach the conventional level
of statistical significance.
EXPERIMENT 2
In this experiment, we used a different measure to assess the effect of
emotion on automatic attitudes—the Implicit Association Test (IAT).
We used the IAT for two reasons. First, it provided the opportunity to
conduct a cross-method validation of the findings of Experiment 1.
Evaluative priming and the IAT share several commonalities: (a) Both
tasks assume that if an attitude object evokes a particular evaluation,
it will facilitate responses to stimuli that are evaluatively congruent
versus neutral or incongruent, and (b) both tasks interpret response
facilitation as a measure of the strength of association between the
object and attribute (Bargh, Chaiken, Govender, & Pratto, 1992;
4 To avoid confounding the anger induction with the priming of information
related to intergroup conflict, we screened participants’ responses for memories that were intergroup in nature. None of the memories involved intergroup themes; all were interpersonal.
5 Analyses involving response latencies were conducted using log-trans-
formed values to normalize the distributions. For easier interpretation, how- ever, we present descriptive statistical information using the millisecond metric.
6 We were agnostic about whether increased intergroup bias would be driven
by less positivity or greater negativity toward the outgroup. Previous work on automatic prejudice in particular, and automatic evaluations in general, has typically relied on the existence of significant Prime � Target interactions, as opposed to absolute comparisons of response latencies across different types of trials, to indicate the existence of an evaluative bias because such individual comparisons can be compromised by confounding factors that differentially influence responses to specific types of stimuli (see Bargh, Chaiken, Govender, & Pratto, 1992; Duckworth, Bargh, Garcia, & Chaiken, 2002; Fazio et al., 1995; Glaser & Banaji, 1999; Klauer, Rossnagel, & Musch, 1997).
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Dasgupta, McGhee, Greenwald, & Banaji, 2000; Fazio, Sanbonmatsu,
Powell, & Kardes, 1986; Greenwald, McGhee, & Schwartz, 1998).
However, there are procedural differences between these two tasks.
Thus, replicating Experiment 1 using the IAT would demonstrate the
robustness of the predicted effect. Second, some data suggest that
compared with priming techniques, the IAT may be more sensitive to
individual and group differences and somewhat more reliable across
time (Bosson, Swann, & Pennebaker, 2000). We therefore expected
that this task might be better able to capture the predicted pattern of
emotion-induced moderation of intergroup bias.
Method
Participants
Eighty-one students (51 females, 30 males) participated in this ex-
periment in partial fulfillment of requirements for a psychology
course.
Procedure and Measures
The procedure and measures used were identical to those of Experi-
ment 1 with two exceptions: Automatic attitudes were assessed using
an IAT instead of evaluative priming, and participants’ self-reported
attitudes toward the ingroup and outgroup were also measured to
ensure the success of the minimal-group manipulation.
In the IAT task, participants first completed three practice blocks
during which they categorized four types of stimuli (pictures rep-
resenting in- and outgroup members and positive and negative
words) using two designated response keys. Specifically, participants
classified (a) valenced words for 20 trials, (b) pictures of in- and
outgroup members for another 20 trials, and then (c) all four types of
stimuli simultaneously (20 trials). These practice tasks were coun-
terbalanced such that half the participants learned to categorize
ingroup and good stimuli using the same key and outgroup and bad
stimuli using a different key. The remaining participants learned the
opposite stimulus pairing. Participants then completed the first round
of emotion induction, which was followed by a data-collection block
of the IAT that was identical to the last practice block, only longer
(50 trials).
Next, additional practice was given so that participants could learn
to categorize stimuli in the combination opposite to what they had
learned before. During this practice, they first classified pictures of in-
versus outgroup members using response keys opposite to those they
had used previously (20 trials). Next, they classified all four types of
stimuli simultaneously such that, for example, those participants who
had previously paired ingroup with good and outgroup with bad
learned to associate ingroup with bad and outgroup with good (20
trials). Participants then completed another round of emotion induc-
tion to reinstantiate their feeling state, followed by a second data-
collection block of the IAT (50 trials). Next, participants reported their
attitudes toward the groups using a five-item, 7-point semantic dif-
ferential scale (unintelligent-intelligent, bad-good, unpleasant-pleas-
ant, dishonest-honest, awful-nice); their responses were averaged into
a single attitudinal index (a5.87). Participants’ emotional states were assessed at the end as in Experiment 1.
Results and Discussion
Manipulation Checks
The emotion manipulations were successful, as indicated by the
Emotion Induction � Emotion Rating interaction, F(2, 79) 5 13.14, p < .001. Participants in the sad condition reported more sadness
(M 5 3.63) than anger (M 5 2.98), t(25) 5 2.89, p < .01, d 5 0.57;
participants in the angry condition reported more anger (M 5 3.64)
than sadness (M 5 3.21), t(27) 5 2.46, p 5 .02, d 5 0.46. Neutral
Fig. 1. Reaction time in the evaluative priming task (Experiment 1) as a function of emotion, prime, and target. Error bars represent standard errors.
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participants reported low levels of both emotions (Msadness 5 1.57,
Manger 5 2.05).
Analysis of participants’ self-reported attitudes verified the success
of the group-assignment procedure. As in previous minimal-group
research, participants reported more positive attitudes toward their
ingroup (M54.90) than their outgroup (M54.46), F(1, 79)511.21,
p 5 .001, d 5 0.75. 7
Automatic Attitudes Toward Social Groups
Automatic attitudes were measured as the differential speed with
which participants classified outgroup with good stimuli and ingroup
with bad stimuli compared with the reverse combinations; larger
difference scores correspond to stronger bias against the outgroup
relative to the ingroup. Participants’ emotional states differentially
biased their intergroup evaluations, F(1, 79) 5 4.03, p < .05, d 5
0.54. 8 As shown in Figure 2, only participants in the angry condition
showed strong automatic prejudice against the outgroup and relative
preference for the ingroup, t(27)53.32, p < .01; those in the sad and
neutral conditions showed no intergroup bias (both ts < 1). Further
analyses revealed that the interaction effect was driven by slower
responses to outgroup 1 good/ingroup 1 bad classifications for par-
ticipants in the angry condition compared with those in the neutral
and sad conditions, F(1, 79) 5 3.91, p 5 .05. Response latencies for
ingroup 1 good/outgroup 1 bad classifications did not differ signifi-
cantly across emotion conditions (F < 1). Thus, as in Experiment 1,
anger created automatic outgroup bias where none had previously
existed.
GENERAL DISCUSSION
Using different measures of automatic attitudes, two experiments
support our contention that incidental feelings of anger can create
automatic prejudice against outgroups. Because this effect was not
produced by a different negative emotion that is functionally less
relevant to intergroup cognition (e.g., sadness), the results are in-
consistent with a simple valence-based interpretation of emotional
bias. We believe that anger, because of its basic association with in-
tergroup competition and conflict, evoked a psychological readiness to
evaluate outgroups negatively vis-à-vis ingroups, thus creating an
automatic prejudice against the outgroup from thin air. To our
knowledge, the present findings stand as the first evidence that spe-
cific emotions are capable of shaping people’s automatic evaluations
toward social groups in accordance with their functional value.
In everyday life, anger-induced psychological readiness is likely to
prepare one to deal rapidly with possible aggression or resource
competition. Although the exact mechanism underlying this exacer-
bation of prejudice remains unknown at present, we speculate that it
is likely to involve the activation of emotion-specific action tenden-
cies and the accompanying cascade of physiological and psycholog-
ical sequelae that result from the occurrence of specific emotional
states (cf. Frijda, 1986; LeDoux, 1996). Given this functional view, it
seems plausible that the ability of extant emotional states to bias
automatic evaluation may not be limited to intergroup cognition, but
may occur for many types of automatic appraisals. Emotions, in each
case, might function to shunt automatic appraisals toward goal-spe-
cific outcomes.
It is important to note, however, that anger may not be the only
negative emotion that can influence automatic attitudes toward known
social groups. Although anger is a fundamental emotion associated
with intergroup conflict, it is clear that negative feelings toward dif-
ferent outgroups do indeed vary in emotional tone. Envy, fear, disgust,
or some other negative emotion may be a salient component of an
individual’s phenomenological experience with a specific outgroup,
depending on that outgroup’s power, status, or other qualities in re-
lation to the perceiver’s ingroup (Mackie & Smith, 2002). Thus, an
important goal of future research is to determine if other discrete
emotions associated with specific groups can alter automatic attitudes
toward those groups even when these emotions are evoked by an
unrelated source. At present, however, the current findings extend
previous research on the interplay between emotion and intergroup
relations into a new realm by providing evidence that emotions are
capable of shaping automatic attitudes relevant to one of the central
adaptive challenges in contemporary society—negotiating intergroup
interactions.
Acknowledgments—This research was supported by National Sci-
ence Foundation Grants BCS-0109105 and BCS-0109898.
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(RECEIVED 11/13/02; REVISION ACCEPTED 2/24/03)
324 Volume 15—Number 5
Prejudice From Thin Air
at UNIV TEXAS AT TYLER on August 22, 2016pss.sagepub.comDownloaded from
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