Psy 310 Gestalt Psychology Reflection

psy 310 gestalt psychology refelction Write a 700- to 1,050-word reflection on the main influences on Gestalt psychology and how they contributed to its development. Include an example of each of the Gestalt principles of perceptual organization. Format your reflection consistent with APA guidelines.

Determine the cost factors (distance, weight, and destiny) that may influence the cost of goods.

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

Volume 15—Number 5 319Copyright r 2004 American Psychological Society at UNIV TEXAS AT TYLER on August 22, 2016pss.sagepub.comDownloaded from

 

http://pss.sagepub.com/

 

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.

320 Volume 15—Number 5

Prejudice From Thin Air

at UNIV TEXAS AT TYLER on August 22, 2016pss.sagepub.comDownloaded from

 

http://pss.sagepub.com/

 

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).

Volume 15—Number 5 321

D. DeSteno et al.

at UNIV TEXAS AT TYLER on August 22, 2016pss.sagepub.comDownloaded from

 

http://pss.sagepub.com/

 

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.

322 Volume 15—Number 5

Prejudice From Thin Air

at UNIV TEXAS AT TYLER on August 22, 2016pss.sagepub.comDownloaded from

 

http://pss.sagepub.com/

 

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

How can you gain a better understanding of the family situation so you can assist in achieving a more harmonious relationship?

1000 to 1200 words

Abnormal Child and Adolescent Psychology with DSM-V Updates by Wicks-Nelson

 

 

You are a counselor in a child and adolescent center. Your boss asks you to see a mother with her 3-year-old son. The mother brings her son to your office, and they are hostile toward each other. She states that he is hyperactive and has ADHD. She is demanding medication for him so she can manage his behavior. You request a session with her son for play therapy. During the 30 minutes of play therapy, he behaves appropriately with the toys in the room with no signs or symptoms of hyperactivity. However, when returned to the room with the mother, he exhibits hyperactivity and argumentative behavior.

Given the aforementioned case, what is your common sense telling you in this situation? You do not need to know theory for this assignment.

Address the following:

  • Identify differences and similarities you understand regarding the diagnosis of ADHD. Consider the possible medication, short-term benefits, and long-term side effects for a 3-year-old male.
  • Discuss how you would use what you know about family relationships to build a bridge in your meetings with this particular family.
  • How can you gain a better understanding of the family situation so you can assist in achieving a more harmonious relationship?

Summarize The Article

Current Directions in Psychological Science 2014, Vol. 23(3) 225 –229 © The Author(s) 2014 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0963721414531599 cdps.sagepub.com

For decades, feminist scholars (e.g., MacKinnon, 1993) have argued that the immense cultural emphasis on women’s physical appearance and sexual features under- lies their objectification by others. Women then internal- ize these cultural standards, leading to self-objectification (Fredrickson & Roberts, 1997). For nearly 15 years, research drawing on objectification theory (Fredrickson & Roberts, 1997) has examined aversive consequences for women resulting from their focus on their own physi- cal appearance. This self-objectification impairs cognitive performance, heightens negative affect, restricts eating, and lessens sexual enjoyment, for instance (see Moradi & Huang, 2008).

Recent work on objectification extends this research in two key ways. It tests objectification as a direct response to a focus on women’s physical features by others. And it tests objectification more literally—whether women are perceived like, and behave like, an object relative to a person (i.e., literal objectification; Goldenberg, 2013; Nussbaum, 1999)—in response to this interpersonal focus on their physical aspects.

Literal Objectification

Evidence across several conceptualizations of humanness (e.g., Leyens et al., 2000) converges in demonstrating that

perceptions of people, including the self, fall on a con- tinuum ranging from human to nonhuman; this includes a continuum from human to object (Gruenfeld, Inesi, Magee, & Galinsky, 2008; Harris & Fiske, 2009; Haslam, 2006). Building on these perspectives, we define literal objectification as any outcome in which a person is per- ceived as, or behaves, objectlike, relative to humanlike. Manifestations of literal objectification include attributing people less of the traits that distinguish people from objects (e.g., warmth, competence), visual and neural markers indicative of perceiving objects relative to peo- ple (e.g., reduced neural activity in the default-mode net- work), and people themselves behaving in more objectlike manners (e.g., speaking less).

Literal objectification is distinct from animal/human conceptualizations of dehumanization (Haslam, 2006; Leyens et al., 2000). Traits attributed to animals and to objects are correlated weakly, if at all (Haslam, Bain, Bastian, Douge, & Lee, 2005). In turn, although women are implicitly associated more with animals than with objects when they are depicted sexually (Vaes, Paladino,

531599CDPXXX10.1177/0963721414531599Heflick, GoldenbergThe Literal Objectification of Women research-article2014

Corresponding Author: Nathan A. Heflick, School of Psychology, Keynes College, University of Kent, Canterbury, Kent CT4 7RL, United Kingdom E-mail: n.a.heflick@kent.ac.uk

Seeing Eye to Body: The Literal Objectification of Women

Nathan A. Heflick1 and Jamie L. Goldenberg2 1University of Kent and 2University of South Florida

Abstract Scholars have long argued that women are denied a basic sense of humanness—are objectified—when focus is directed toward their physical rather than mental qualities. Early research on objectification focused on women’s self-objectification and measured objectification indirectly (as an emphasis on physical appearance). Recent research, however, has provided direct evidence that a focus on the physical aspects of women by others causes women to be perceived like, and act like, objects lacking mind. Manifestations of this literal objectification include attributing women less of the traits that distinguish people from objects and visual-recognition and neural responses consistent with nonhuman-object perception. Women themselves also behave more like objects (by, e.g., speaking less) when they are aware of this focus by others. Real-world implications and ways to defuse literal objectification are discussed.

Keywords objectification, dehumanization, appearance focus, sexualization

at ARKANSAS STATE UNIV on January 29, 2015cdp.sagepub.comDownloaded from

 

http://cdp.sagepub.com/

 

226 Heflick, Goldenberg

& Puvia, 2011), this is indicative of dehumanization, not literal objectification. Relatedly, although sexualized women may be objectified (Loughnan et al., 2010), literal objectification is not specific to a focus on the body that is sexual. Lastly, literal objectification differs from holding negative views of others or the self; traits people perceive as separating humans from objects can be positive or negative (Haslam et al., 2005).

Interpersonal Focus on Women’s Physical Aspects

In their daily experiences (Kozee, Tylka, Augustus- Horvath, & Denchik, 2007) and in the media (Archer, Iritani, Kimes, & Barios, 1983), women are subject to dis- proportionate focus on their physical traits. Scholars have argued that this underlies women’s objectification. Until recently, however, empirical research was limited to self- objectification—and objectification was induced through or measured as a focus on one’s own appearance (e.g., trying on a swimsuit in front of a mirror; Fredrickson, Roberts, Noll, Quinn, & Twenge, 1998). In the newest work, researchers have employed several different manipulations that prompt focus on the physical, relative to the mental, aspects of others or make women aware of this focus by others.

Most directly, these manipulations have involved hav- ing people write about or observe an individual’s physical appearance in contrast to his or her personality (e.g., Heflick, Goldenberg, Cooper, & Puvia, 2011). Using eye- tracker software, Gervais, Holland, and Dodd (2013) found that this prompt increased the amount of time men and women spent looking at women’s body parts (i.e., breasts and hips) and decreased the amount of time spent looking at their faces. Studies in which persons are explic- itly sexualized, usually via the amount of clothes worn (e.g., Bernard, Gervais, Allen, Campomizzi, & Klein, 2012), also highlight the physical rather than mental aspects of a person. In addition, studies in which the pro- portion of people’s bodies relative to their faces is increased in photos (Loughnan et al., 2010) promote more physical, less mental, focus in others. Finally, experienc- ing or recalling prior experiences in which others’ atten- tion is directed toward one’s body is also consistent with our operationalization of interpersonal physical focus.

Building on the evidence that women (but typically not men) experience a myriad of aversive consequences when focusing on their own physical appearance (see Moradi & Huang, 2008), we now examine the evidence that inter- personal focus on women’s physical aspects causes both men and women to literally objectify women. (But we acknowledge that a minority of studies have found that males are similarly objectified; e.g., Loughnan et al., 2010.)

Women Perceived as Objects

Trait attribution

Haslam’s (2006) research has demonstrated that people perceive traits indicative of human nature to separate humans from objects. When people are described as low in human-nature traits (e.g., “How much is this group like robots?”), they are subsequently rated as more objectlike, and vice versa (Loughnan, Haslam, & Kashima, 2009). On this basis, Heflick and Goldenberg (2009) had participants write about a woman’s physical appearance or about the woman as a person before rating her on several traits and rating how essential each trait is to human nature. Within- person correlations between the perceived typicality of each trait for the target person and the perceived human- ness of each trait were less positive when participants focused on the woman’s appearance. This effect repli- cated across female targets and was independent of how positively participants wrote about the woman.

The specific attributes of warmth and competence are also associated with being a human and not an object (Harris & Fiske, 2009). Consistent with this, only images of people perceived as low in warmth and competence (e.g., the homeless) fail to elicit brain activation in the medial prefrontal cortex, an area involved in the recognition and processing of human faces but not nonhuman objects (Harris & Fiske, 2006). Building on this, and on research demonstrating that morality is a component of warmth (Leach, Ellemers, & Barreto, 2007), Heflick et al. (2011) demonstrated that focusing on a woman’s physical appearance, in a video or still image, reduces her per- ceived competence, warmth, and morality. This effect rep- licated across female targets of varying attractiveness, status, familiarity, and race (Heflick et al., 2011), but not in response to comparable male targets. Women are also rated as less intelligent after people view them with more of their body showing relative to their face (Loughnan et  al., 2010) and after people view them in revealing clothes (Rudman & Borgida, 1995). This is true even when the women being evaluated are not the women wearing the revealing clothing (Rudman & Borgida, 1995).

Research into perceptions of “mind” (H. M. Gray, Gray, & Wegner, 2007) indicates that people believe the mind has two primary components: agency (ability to think) and experience (ability to feel). Objects and machines are attributed less agency and experience than humans (H. M. Gray et al., 2007). Likewise, women are perceived to have less agency (K. Gray, Knobe, Sheskin, Bloom, & Barrett, 2011), as well as fewer thoughts (reason, think- ing), intentions (wishes, plans), and perceptions (seeing, hearing), when they are depicted sexually, relative to when they are depicted as fully clothed (Holland & Haslam, 2013; Loughnan et al., 2010; but see K. Gray

at ARKANSAS STATE UNIV on January 29, 2015cdp.sagepub.comDownloaded from

 

http://cdp.sagepub.com/

 

The Literal Objectification of Women 227

et  al., 2011, for a contradictory finding). They are also explicitly perceived as having less of a mind (i.e., in response to an item asking, “How much mind does this woman have?”; Loughnan et al., 2010). Further, women wearing bikinis are attributed fewer thoughts, percep- tions, and intentions when their body is exclusively shown in a photograph than when their face alone or their face and body are shown (Loughnan et al., 2010).

Visual processing and recognition

People are less able to recognize images of humans when they are inverted, but this is not true for objects (Reed, Stone, Bozova, & Tanaka, 2003). Bernard et al. (2012) recently illustrated an exception to this finding: Images of sexualized women (i.e., women wearing swim- suits) are recognized equally well when inverted and right side up. This is in contrast to images of men, sexual- ized or not, and nonsexualized images of women. The authors reasoned that people focus on specific aspects of women’s bodies—like they would objects—when women are sexualized, which impairs configural processing (i.e., the connection of distinct features to form a coherent whole) and subsequent recognition.

Objects are interchangeable (i.e., fungible; Nussbaum, 1999). Consistent with our position, Gervais, Vescio, and Allen (2012) showed people images of women and men and then, in a subsequent task, asked them to match the faces to bodies. Overall, men and women were worse at matching women’s than men’s faces to their bodies. The exception was highly muscular male images, presumably because their muscularity drew attention to their physical bodies. Similarly, Cikara, Eberhardt, and Fiske (2011) found that participants were better able to recognize the bodies, but not the faces, of sexualized women relative to clothed women or sexualized or clothed men. Men and women are also more likely to mistake women’s faces for objects (images created by computers) than men’s faces, and computer-generated faces are more likely to be mis- taken for female than male faces (Balas, 2013).

Neural processing

When people read or hear about ways in which humans are similar to objects, there is reduced activation in a network of brain regions (i.e., the default-mode network) that are highly involved in theory-of-mind reasoning ( Jack, Dawson, & Norr, 2013). Part of this network, the temporoparietal junction, is activated when people read statements about human minds, but not when they read statements about a woman’s physical features (e.g., her height) or about nonhuman objects (e.g., a pot of tea; Saxe & Kanwisher, 2003). In turn, both likening humans to objects and focusing on women’s physical traits

reduces neural activity associated with inferring others’ mental traits. Moreover, when males high in hostile sex- ism view images of scantily dressed, but not fully dressed, women, this results in reduced activation of the medial prefrontal cortex (part of the default-mode network), consistent with neural activity when viewing objects (Cikara et al., 2011).

Women Behaving as Objects

There is also evidence that when women’s appearance is focused on by others (male or female), they literally objectify themselves. Gervais, Vescio, and Allen (2011) had male and female confederates “ogle” female partici- pants, gazing at them from face to body as opposed to gazing at only their face. After the full-body gazing, women performed less competently on a series of math problems. Women also become more passive—like objects—under conditions in which others are focused on their physical bodies, and they are less willing to pro- test for women’s rights (Calogero, 2013) when recalling a past instance of being ogled or receiving sexual com- ments from a man. Finally, women talk less, such as by spending less time introducing themselves, when their body is obviously salient to others (Saguy, Quinn, Dovidio, & Pratto, 2010).

Supporting a foundational premise of self-objectification theory (see Fredrickson & Roberts, 1997), these findings provide direct empirical evidence that self-objectification is a response to a focus on women’s physical aspects by others. Consistent with objectification as literal, women in these studies (and in previous studies, too; e.g., Fredrickson & Harrison, 2005; Fredrickson et al., 1998) behaved in ways consistent with being an object (e.g., restraining their eating and movement).

Real-World Implications

In an experiment conducted weeks prior to the 2008 U.S. presidential election (Heflick & Goldenberg, 2009), par- ticipants were instructed to write about the Republican vice presidential nominee, Sarah Palin, or about her physical appearance. People reported decreased percep- tions of Palin’s competence and reduced intentions to vote for the Republican ticket when they had focused on Palin’s appearance. Moreover, these effects were attribut- able to reductions in her perceived humanness (human- nature ratings). These findings, in conjunction with the media attention to Palin’s appearance, including cover- age of her alleged $150,000 makeover, led us to speculate that literal objectification may have played a role in the outcome of the election (see Heflick & Goldenberg, 2011). In other research, purported female job applicants were viewed as less competent by men who had recently

at ARKANSAS STATE UNIV on January 29, 2015cdp.sagepub.comDownloaded from

 

http://cdp.sagepub.com/

 

228 Heflick, Goldenberg

viewed images of other women who were scantily dressed (Rudman & Borgida, 1995), and women per- formed less well on items from the GRE, a critical factor for admittance into most graduate schools in the United States, after being ogled (Gervais et al., 2012).

Further, the moral concern people afford beings (human or not) is directly attributable to their perception that the beings have humanlike traits (e.g., H. M. Gray et al., 2007). Loughnan and colleagues (2010) asked to what extent people were willing to administer pills that caused pain to hypothetical targets that had either been sexualized or not. People were more willing to give the pain-inducing pills to the sexualized male and female targets. Further, implicit association of women with object words (e.g., tool) is pre- dictive of men’s acceptance of sexual aggression toward women (Rudman & Mescher, 2012). Even playing video games with sexually depicted female characters increases men’s acceptance of sexual aggression (Yao, Mahood, & Linz, 2010). Additionally, when a woman is depicted in a bikini, men and women show her less moral concern; she is also more likely to be blamed for a man’s pinning her down, removing her clothing, and forcing her to have sex (Loughnan, Pina, Vasquez, & Puvia, 2013). Women them- selves also assume less moral standing (i.e., they feel more sinful) when recalling instances of being gazed at sexually (Chen, Teng, & Zhang, 2013). In turn, women may encoun- ter risks to their actual physical safety when they are liter- ally objectified.

Defusing Literal Objectification

Bernard, Gervais, Allen, and Klein (2014) found that reading descriptions emphasizing female warmth and competence counteracted the tendency to perceive sexu- alized women as similar to objects in an image-inversion recognition task. Portraying women with clear signs of competence (i.e., trophies) also made people less likely to gaze at their sexual body parts ( Johnson & Gurung, 2011). In accord with evidence that men with particularly negative views of women are prone to literal objectifica- tion (Cikara et al., 2011), one route to defusing literal objectification could be to promote positive, more human views of women. Other possible routes include a general sociocultural de-emphasis on women’s physical features relative to their mental traits (Heflick & Goldenberg, 2009) and women’s continuing to gain status and power (Gruenfeld et al., 2008), both of which are associated with reduced objectification.

Conclusion

A growing body of evidence indicates that when people focus on women’s physical attributes, women are literally objectified. The ways in which this objectification is

manifested include people’s attributing women less of the traits that distinguish people from objects, visual and neural markers indicative of perceiving objects relative to people, and women themselves behaving in a more objectlike manner. In short, “seeing eye to body” causes women to be perceived, and to behave, more like an object and less like a human being.

Recommended Reading

Fredrickson, B. L., & Roberts, T.-A. (1997). (See References). The original formulation of objectification theory, which sparked nearly all research on self-objectification.

Gervais, S. J. (Ed.). (2013). Objectification and (de)humaniza- tion: 60th Nebraska Symposium on Motivation. New York: Springer. An edited volume that includes contributions from scholars researching the objectification of others.

Haslam, N. (2006). (See References). The original formulation of object-based and animal-based distinctions in dehuman- ization

Nussbaum, M. C. (1999). (See References). A philosophical trea- tise into what it means to be objectified

Declaration of Conflicting Interests

The authors declared that they had no conflicts of interest with respect to their authorship or the publication of this article.

References

Archer, D., Iritani, B., Kimes, D.D., & Barios, M. (1983). Face- ism: Five studies of sex differences in facial prominence. Journal of Personality and Social Psychology, 45, 723–735.

Balas, B. (2013). Biological sex determines whether faces look real. Visual Cognition, 21, 766–788.

Bernard, P., Gervais, S., Allen, J., Campomizzi, S., & Klein, O. (2012). Integrating sexual objectification with object versus person recognition: The sexualized-body-inversion hypoth- esis. Psychological Science, 23, 469–471.

Bernard, P., Gervais, S. J., Allen, J., & Klein, O. (2014). From sex-objects to human beings: Masking sexual body parts and humanization as antidotes to women’s objectification. Manuscript submitted for publication.

Calogero, R. (2013). Objects don’t object: Evidence that objec- tification disrupts women’s social activism. Psychological Science, 24, 312–318.

Chen, Z., Teng, F., & Zhang, H. (2013). Sinful flesh: Sexual objectification threatens women’s moral self. Journal of Experimental Social Psychology, 49, 1042–1048.

Cikara, M., Eberhardt, J. L., & Fiske, S. T. (2011). From agents to objects: Sexist attitudes and neural responses to sexualized targets. Journal of Cognitive Neuroscience, 23, 540–551.

Fredrickson, B. L., & Harrison, K. (2005). Throwing like a girl: Self-objectification predicts adolescent girls’ motor perfor- mance. Journal of Sport & Social Issues, 29, 79–101.

Fredrickson, B. L., & Roberts, T.-A. (1997). Objectification theory: Toward understanding women’s lived experience and men- tal health risks. Psychology of Women Quarterly, 21, 173–206.

Fredrickson, B. L., Roberts, T.-A., Noll, S. M., Quinn, D. M., & Twenge, J. M. (1998). That swimsuit becomes you:

at ARKANSAS STATE UNIV on January 29, 2015cdp.sagepub.comDownloaded from

 

http://cdp.sagepub.com/

 

The Literal Objectification of Women 229

Sex differences in self-objectification, restrained eating, and math performance. Journal of Personality and Social Psychology, 75, 269–284.

Gervais, S. J., Holland, A., & Dodd, M. (2013). My eyes are up here: The nature of the objectifying gaze toward women. Sex Roles, 69, 557–570.

Gervais, S. J., Vescio, T. K., & Allen, J. (2011). When what you see is what you get: The consequences of the objectifying gaze for men and women. Psychology of Women Quarterly, 35, 5–17.

Gervais, S. J., Vescio, T. K., & Allen, J. (2012). When are people interchangeable sexual objects? The effect of gender and body type on sexual fungibility. British Journal of Social Psychology, 51, 499–513.

Goldenberg, J. L. (2013). Immortal objects: The objectification of women as terror management. In S. J. Gervais (Ed.), Motivation perspectives on objectification and (de)human- ization (pp. 73–95). New York, NY: Springer.

Gray, H. M., Gray, K., & Wegner, D. M. (2007). Dimensions of mind perception. Science, 315, 619.

Gray, K., Knobe, J., Sheskin, M., Bloom, P., & Barrett, L. (2011). More than a body: Mind perception and the nature of objec- tification. Journal of Personality and Social Psychology, 101, 1207–1220.

Gruenfeld, D. H., Inesi, M. E., Magee, J. C., & Galinsky, A. D. (2008). Power and the objectification of social targets. Journal of Personality and Social Psychology, 95, 111–127.

Harris, L. T., & Fiske, S. T. (2006). Dehumanizing the lowest of the low: Neuroimaging responses to extreme out-groups. Psychological Science, 17, 847–853.

Harris, L. T., & Fiske, S. T. (2009). Social neuroscience evidence for dehumanised perception. European Review of Social Psychology, 20, 192–231.

Haslam, N. (2006). Dehumanization: An integrative review. Personality and Social Psychology Review, 10, 252–264.

Haslam, N., Bain, P., Bastian, B., Douge, L., & Lee, M. (2005). More human than you: Attributing humanness to the self and others. Journal of Personality and Social Psychology, 89, 228–235.

Heflick, N. A., & Goldenberg, J. L. (2009). Objectifying Sarah Palin: Evidence that objectification causes women to be perceived as less competent and less fully human. Journal of Experimental Social Psychology, 45, 598–601.

Heflick, N. A., & Goldenberg, J. L. (2011). Sarah Palin, a nation object(ifie)s: The role of appearance focus in the 2008 U.S. presidential election. Sex Roles, 65, 149–155.

Heflick, N. A., Goldenberg, J. L., Cooper, D. P., & Puvia, E. (2011). From women to objects: Appearance focus, target gender, and perceptions of warmth, morality and competence. Journal of Experimental Social Psychology, 47, 572–581.

Holland, E., & Haslam, N. (2013). Worth the weight: The objec- tification of overweight versus thin targets. Psychology of Women Quarterly, 37, 462–468.

Jack, A. I., Dawson, A. J., & Norr, M. E. (2013). Seeing human: Distinct and overlapping neural signatures associated with two forms of dehumanization. NeuroImage, 79, 313–328.

Johnson, V., & Gurung, R. (2011). Defusing the objectification of women by other women: The role of competence. Sex Roles, 65, 177–188.

Kozee, H. B., Tylka, T. T., Augustus-Horvath, C. L., & Denchik, A. (2007). Development and psychometric evaluation of the Interpersonal Sexual Objectification Scale. Psychology of Women Quarterly, 31, 176–189.

Leach, C. W., Ellemers, N., & Barreto, M. (2007). Group vir- tue: The importance of morality (vs. competence and soci- ality) in the positive evaluation of in-groups. Journal of Personality and Social Psychology, 93, 234–249.

Leyens, J. P., Paladino, M. P., Rodriguez, R. T., Vaes, J., Demoulin, S., Rodriguez-Perez, A., & Gaunt, R. (2000). The emotional side of prejudice: The attribution of second- ary emotions to ingroups and outgroups. Personality and Social Psychology Review, 4, 186–197.

Loughnan, S., Haslam, N., & Kashima, Y. (2009). Understanding the relationship between attribute-based and metaphor- based dehumanization. Group Processes & Intergroup Relations, 12, 747–762.

Loughnan, S., Haslam, N., Murnane, T., Vaes, J., Reynolds, C., & Suitner, C. (2010). Objectification leads to depersonali- zation: The denial of mind and moral concern to objec- tified others. European Journal of Social Psychology, 40, 709–717.

Loughnan, S., Pina, A., Vasquez, E., & Puvia, E. (2013). Sexual objectification increases rape victim blame and decreases perceived suffering. Psychology of Women Quarterly, 37, 455–461.

MacKinnon, C. (1993). Only words. Cambridge, MA: Harvard University Press.

Moradi, B., & Huang, Y. P. (2008). Objectification theory and psychology of women: A decade of advances and future directions. Psychology of Women Quarterly, 32, 377–398.

Nussbaum, M. C. (1999). Sex and social justice. New York, NY: Oxford Press.

Reed, C. L., Stone, V. E., Bozova, S., & Tanaka, J. (2003). The body-inversion effect. Psychological Science, 4, 302–308.

Rudman, L. A., & Borgida, E. (1995). The afterglow of construct accessibility: The behavioral consequences of priming men to view women as sexual objects. Journal of Experimental Social Psychology, 31, 493–517.

Rudman, L. A., & Mescher, K. (2012). Of animals and objects: Men’s implicit dehumanization of women and male sexual aggression. Personalty and Social Psychology Bulletin, 38, 734–746.

Saguy, T., Quinn, D. M., Dovidio, J. F., & Pratto, F. (2010). Interacting like a body: Objectification can lead women to narrow their presence in social interactions. Psychological Science, 21, 178–182.

Saxe, R., & Kanwisher, N. (2003). People thinking about think- ing people: The role of the temporo-parietal junction in “theory of mind.” NeuroImage, 19, 1835–1842.

Vaes, J., Paladino, P., & Puvia, E. (2011). Are sexualized women complete human beings? Why men and women dehuman- ize sexually objectified women. European Journal of Social Psychology, 41, 774–785.

Yao, M. Z., Mahood, C., & Linz, D. (2010). Sexual priming, gender stereotyping, and likelihood to sexually harass: Examining the cognitive effects of playing a sexually- explicit video game. Sex Roles, 62, 77–88.

at ARKANSAS STATE UNIV on January 29, 2015cdp.sagepub.comDownloaded from

 

http://cdp.sagepub.com/