Abstract
This study tested if stereotype threat affects people’s choices when answering Implicit Association Test for Race. Stereotype threat is used to describe the psychological phenomenon whereby a negative stereotype about one’s group puts an individual at risk for confirming that negative stereotype (Steele & Aronson, 1995). During President Obama’s inauguration, studies showed that the performance gap between white and black students diminished (Mattimore, 2009). We are interested to know through our study if this change in attitude is reflected by the people’s attitude to the different races as well. Our class gathered 74 participants, 60 females and 14 males, through convenience sampling. The average age of all the participants was 29.19 years old (SD=9.800). Twenty-two of the participants were Caucasians, 18 were African-American and 32 were from other races. The participants were asked to undergo the Implicit Association Test for Race. The time it took the participants to answer the test was recorded. The results showed that stereotype threat does affect people’s choices on IAT for Race. The data showed that the African-American participants were faster than the other races in answering the IAT for Race. Several of the questions from IAT were racial stereotypes on African-Americans and the fact that African-American participants answered the fastest implied that they were more prone to confirming the stereotypes against them. According to Nosek, Greenwald and Banaji (2005), judgment speed is taken as evidence for an implicitly-held attitude toward a social group. However, most participants took longer time in answering trials that held stereotype against other races. This may then be attributed to the Obama Effect.
Keywords: stereotype threat, IAT, Obama Effect, convenience sampling
Introduction
Social psychologists have long been interested in the measurement of human emotions and attitudes. Attitudes reflect a general evaluation of a class of individuals or objects (Smith & Fabringer, 2000). Emotions however are much more powerful according to Eliot Smith and Diane Mackie (2007) because it can translate to group levels. Smith and Mackie developed Intergroup Emotions Theory or IET which emphasizes social emotions in intergroup relations. According to Miller, Smith, and Mackie (2004), understanding IET may result in understanding and thus, reducing, prejudice among certain groups.
Psychologists have traditionally used self-report measures to assess attitudes. Recently, however, researchers have begun to use less direct measures of the cognitive processes underlying judgment. These less direct measures include the use of implicit association tests which were pioneered by Greenwald, McGhee and Schwartz (1998). Implicit association tests (IATs) measure the relative ease with which people are able to make associations between certain groups of people and the concepts of "good" and "bad." Ease of association, measured by judgment speed, is taken as evidence for an implicitly-held attitude toward that social group. For example, researchers would interpret the finding that people are quicker to associate the term "good", with the term "young", rather than with the term "old" as evidence of a generally-held bias in favor of youth. The IAT method is useful for measuring a variety of attitudes including attitudes about sex differences, race, and political constructs (Nosek, Greenwald, & Banaji, 2005).
Several researchers have in fact started to adapt IAT in their studies to measure several factors such as children’s performance on certain subjects. One particular study that can be found in the category of children’s performance on certain subjects is one that focuses on stereotype threat susceptibility in Italian children (Muzzatti and Agnoli, 2007). Another similar study focuses on Math-gender stereotypes in elementary school children (Cvencek, Meltzoff, & Greenwald, 2011). In both studies, the researchers sought to understand the stereotyping of Mathematics as a subject that boys excel in more than girls and its effect on students in general and on girls in particular. Both studies resulted in girls having poorer performance when reminded of the Math-stereotype. Also, the studies showed that the stereotype threat was acquired early on by these students basing on the data from the elementary school students that participated in the study. In the study by Cvencek, Meltzoff, and Greenwald (2011), the researchers used both IAT and self-report measures.
A recent meta-analysis has suggested that the IAT is a better predictor of racial discrimination than traditional 'explicit' self-report methods (Greenwald, Poehlman, Uhlmann, & Banaji, 2009). Despite these findings, however, several issues have been raised that make the interpretations of these findings difficult. Of particular interest is the potential for stereotype threat to influence performance on the IAT for Race.
“Stereotype threat” is used to describe the psychological phenomenon whereby a negative stereotype about one’s group puts an individual at risk for confirming that negative stereotype (Steele & Aronson, 1995). In the IAT for race it is possible that individuals belonging to a particular ethnic group might respond in accordance with the stereotype associated with the group to which they belong. Thus, a Caucasian individual who maintains an implicitly held stereotype that Caucasians are more likely to discriminate may respond in a discriminatory manner as a direct consequence of this stereotype. Therefore, evaluating the results of the IAT in different racial groups may provide additional insight into the implicit stereotypes associated with race.
However, another phenomenon known as the Obama Effect might offset the uncertainties in using IAT due to stereotype threat. The researchers from three American Universities came up with the term Obama Effect when they noticed that the gap between the academic performances of white and black students diminished upon President Obama’s acceptance speech and inauguration (Mattimore, 2009). The change in the performance gap suggests that Obama’s presidency might be the key to diminish stereotype threats on black people and on white people as being discriminating towards other races. Certain studies have been made to support this idea such as the paper submitted by Ray Friedman, David M. Marx and Sei Jin Ko (Dillon, 2009). However, most of the studies pertained to the Obama Effect affecting test-takers or basically, academic performances.
We are interested to know through our study if this change in attitude is reflected by the people’s attitude towards the different races as well.
Participants
Our class used convenience sampling to select 74 people with age varying from 19 to 55 years old to participate in this study. Upon computation, we found out that the mean age of these participants is 29.19 with a standard deviation of 9.800. The majority of them, amounting to 81.1%, are females and the remaining 18.9% are males. The participants were asked to identify themselves based on their race. The choices we have provided were ‘Caucasian’, ‘African-American’ and ‘Others’. Under the category ‘Others’ are races such as Asian Hispanic. The goal of this self-identification is for the class to understand how the participants associated themselves with their race. Self-identification may not be accurate however especially since some participants may have mixed races. For example, a participant may only be one-half Caucasian in reality but chose to categorize his or her self in that race anyway. During the experiment, 22 of the participants identified themselves as ‘Caucasian’, 18 as ‘African-American’ and 32 as ‘Others’.
Experimental Design
The Implicit-Association Test (AIT) used for this study was one that measures the participants’ attitude towards race by following the guidelines set by Anthony Greenwald and Mahzarin Banaji (1995). The class used a 2x3 mixed factorial design. The Independent Variables (IVs) are divided into Between-Subjects and Within-Subjects. The Between-Subjects was marked as IV1 and was about Trial Type. Trial type had two levels: Incongruent and Congruent. The Within-Subject was marked as IV2 and was about Racial Groups. It had three levels: Caucasian, African-American and Other. The Dependent Variable (DV) was the average time it required for the participants to complete the trials.
Materials and Procedure
Participants were instructed to visit the website of the National Science Foundation using a standard desktop computer equipped with internet functions through the link http://opl.apa.org/. The link then showed the website’s welcome page (refer to Figure A1 at Appendix A) where participants needed to click the “Students Begin Here” link. That link then took them an alphabetically arranged list of experiments where they had to find the ‘Implicit Association Test’ and click on it. The page they arrived in asked for a class ID which we provided. The participants were then asked to provide their race, age and sex. After that, they were asked to answer some questions that will help the researchers understand their attitude towards race.
The first sets of questions asked participants to identify a certain picture or trait and categorize them by clicking either ‘European-American/Caucasian’ or ‘African-American’ as shown in Figure B1 (refer to Appendix B) or clicking either ‘good’ or ‘bad’ as seen in Figure B2 (refer to Appendix B).
The second set of questions deals with trial type which means that it is further divided into congruent and incongruent levels. The instruction was the same as the first set. The only difference was that the second set gave combined attributes for each choice. For example, in Figure B3 (refer to Appendix B), the participant had to choose if the picture of a man should be under ‘African-American and good’ or ‘European American and bad’.
This type of trial is known as ‘incongruent trial’ because it goes against the common stereotype. In this experiment, the stereotype taken into account is that ‘white’ people are ‘good’ people. Its counterpart is the ‘congruent trial’ which adheres to the common stereotype. The results of the tests gave us the needed data to determine the relationship between category combinations and the speed to which the participants answered the questions.
Statistical Analysis Strategy
In this study, we used repeated Analysis of Variance (ANOVA) to measure statistically the Within-Subjects factor or trial type as well as the Between-Subjects factor or race. ANOVA was also used to determine if there was an interaction or relationship between Race and Trial type.
Results
The line graph illustrated in Appendix C shows the relationship between the independent variables (trial types and race) as well as the dependent variable (mean time it took for participants to complete the trials). African-Americans answered the fastest and Caucasians answered the slowest. Those under the racial groups ‘Other’ answered faster than African-Americans but slower than Caucasians. The line graph also shows us that regardless of what racial group they are in, all of the participants took longer time in answering congruent trials than in answering incongruent trials. Notice that in the graph, the lines do not intersect or come in contact with each other. The lines not intersecting show us that there is no relationship between race and trial type. Also, you can see from the graph that none of the lines were in a perfect horizontal line. All of them are slanted. Slanted lines mean that a participant’s speed in answering the IAT differs depending on whether the trials were congruent or not. Also the fact that no two lines overlap means that a participant’s racial group has an effect on how fast he or she answered the IAT.
Discussions
The results of the ANOVA measures therefore tell us that the time it took the participants to finish the AIT depended on their race and the type of trial they were answering.
Our data showed that African-American participants answered the fastest on both congruent and incongruent trials. Taking into account the statement of Nosek, Greenwald and Banaji (2005) that judgment speed is taken as evidence for an implicitly-held attitude toward a social group, it can be said that the African-Americans were more prone to confirming the stereotype towards their racial groups by finishing the trials faster than the two other racial groups in this study due to the fact that several of the questions from IAT were racial stereotypes on African-Americans.
However, it is important to note that all three racial groups finished answering incongruent trials faster than congruent trials. As stated before, congruent trials are those that speak of the common stereotype towards certain groups. The fact that in general, it took the participants longer time in answering congruent trials means that they were not as quick to assume certain answers based on stereotypes assigned to them or their group. This would also mean that stereotype threat’s interference on AIT might be lessening.
This change in attitude can be attributed to the Obama Effect especially since President Obama is continuing to be the leader of the United States of America. More and more people are changing their views towards black people seeing that their president came from these people. As said by Sam Dillon (2009) in an article in The New York Times, Obama’s presidency might be the key to diminishing stereotype threats on black people and on white people as being discriminating towards other races.
There are several limitations in this study. One particular limitation is that our class only measured the time it took the participants to answer the AIT. We did not analyze what the answers of the participants were which might have given more clues to their attitude and emotions. We therefore suggest that those who are interested in continuing this study may include the answers the participants made in the factors affecting their results. Another limitation is that although we wanted to relate our results to the Obama Effect, we did not screen our participants to see if they were affected or even aware of the Obama Effect.
Our study may serve as a springboard for more studies on Obama’s Effect reversing the effect of stereotype threat on IAT for Race.
References
Smith, S. M., & Fabringer, L. R. (2000). Attitudes: An overview. In A. E. Kazdin (Ed.),
Encyclopedia of Psychology (pp. 303-305). Washington, DC: APA.
Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998). Measuring individual
differences in implicit cognition: The implicit association test. Journal of Personality and
Social Psychology, 74, 1464-1480.
Greenwald, A. G., & Banaji, M. R. (1995). Implicit social cognition: Attitudes, self-esteem, and
stereotypes. Psychological Review, 102, 4-27.
Nosek, B. A., Greenwald, A. G., & Mahzarin, B. R. (2005). Understanding and using the implicit
association test: II. Method variables and construct validity. Personality and Social
Psychology Bulletin, 31, 166-180.
Greenwald, A. G., Poehlman, T. A., Uhlmann, E., & Banaji, M. R. (2009). Understanding and
using the Implicit Association Test: III. Meta-analysis of predictive validity. Journal of
Personality and Social Psychology, 97, 17–41
Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of
African-Americans. Journal of Personality and Social Psychology, 69, 797-811.
Muzzatti, B., & Agnoli, F. (2007). Gender and Mathematics: Attitudes and Stereotype Threat
Susceptibility in Italian Children. Developmental Psychology, 43(3), 747-759. Abstract
retrieved from Abstracts in Developmental Psychology database. (Accession No.
17484585)
Cvencek, D., Meltzoff, A.N., & Greenwald, A.G. (2011). Math-Gender Stereotypes in
Elementary School Children. Child Development, 82(3), 766-779. Abstract retrieved
Miller, D.A., Smith, E.R., & Mackie, D.M. (2004). Effects of intergroup contact and political
predispositions on prejudice: Role of Intergroup Emotions. Group Processes and
Intergroup Relations, 7, 221-237.
Dillon, Sam. (2009, January 23). Study Sees an Obama Effect as Lifting Black Test-Takers. The
New York Times, pp. A15.
Appendix A
Appendix B
Appendix C
Appendix D
