Character  &  Context

The Science of Who We Are and How We Relate
Editors: Mark Leary, Shira Gabriel, Brett Pelham
Apr 15, 2019

Beliefs that Black People are Poor Predict Opposition Toward Welfare

by Jazmin L. Brown-Iannuzzi & Erin Cooley
Silloueetes of men standing in a long line, various ages and shapes, against a blank background

American attitudes towards welfare and other income redistribution programs are complicated and controversial. We were interested in whether people who dislike these policies do so, in part, because they automatically associate Black people with being poor. As a result, people may assume that these policies benefit Black people over White people, leading them to be less supportive of welfare and redistributive policies.

Research suggests that many people have a stereotype that Black people are poor. Indeed, factors such as slavery, institutionalized racism, and macro-level discrimination have created a gap in wealth between Black and White families on average. Further, opposition toward welfare and other redistributive policies may exist because many people assume poor people are Black. Consistent with this explanation, research shows that the strongest predictor of opposition toward welfare policies is negative attitudes toward Black people. However, research has not investigated whether automatic associations between race and class predict policy attitudes.

Automatic cognitive associations between race and social class are difficult to control consciously. As a result, people may have associations they don’t want to have or don’t want to report. We hypothesized that people automatically associate Black (vs. White) people with being poor and that stronger associations between “Black” and “poor” predict non-Black people’s opposition toward welfare, in part because people assume these policies benefit Black people more than White people.

To test these ideas, we measured people’s automatic associations between race and class. To measure these associations, we used a research task called the Semantic Misattribution Procedure. In this task, participants are shown Chinese symbols on a computer screen and are asked to guess whether each symbol means “poor” or “rich.” Before seeing each symbol, however, participants are quickly shown a picture of a Black man or a White man (see Figure 1). They are told that these faces, which they see only momentarily, are just a distraction and that their task is to determine whether the Chinese symbol means “rich” or “poor.”

This task measures participants’ automatic associations because, if participants tend to interpret the symbols as meaning “poor” more often after seeing images of Black than White men, then this indicates that they have an automatic association between “Black” and “poor.” In essence, the image of the Black man brings thought of “poor” more easily to mind.

Then, we measured participants’ attitudes toward welfare and other similar programs to see whether the degree to which people associated Black with poor predicted their attitudes. We tested our hypotheses in three online studies. Because our hypotheses were specific to non-Black Americans, we limited our sample to people who did not identify as Black American.

Schematic representation of one trial of the Semantic Misattribution Procedure

Figure 1. Schematic representation of one trial of the Semantic Misattribution Procedure. 

As we expected, participants were significantly more likely to associate Black (vs. White) Americans with the concept of poor in all three studies. More importantly, the more that non-Black people associated Black with poor, the more they thought that welfare was designed to benefit Black people more than White people, which predicted less support for welfare.

Finally, when we led people to think of their automatic associations between race and class as invalid, we reduced the association between race/class associations and attitudes toward welfare. Overall, our studies found that non-Black people automatically associate being Black with being poor, and the strength of this automatic race/class association predicted their attitudes toward welfare and other kinds of income redistribution policies.

Moving forward, we are interested in investigating whether strong associations between “Black” and “poor” might mean different things to different people. For example, perhaps Black participants (or anyone else with positive attitudes toward Black people) hold a strong association between “Black” and “poor,” but this association may reflect their knowledge of racism in society. In this case, associations between “Black” and “poor” might result in positive,rather than negative, attitudes toward welfare because welfare may be perceived as a way to combat racism.

In addition, we are interested in studying whether people who live in locations where the majority of poor individuals are White might have less strong associations between Black and poor. In the face of historic levels of economic inequality in the United States, our work may disentangle the ways in which people conflate race with social class to understand the factors that shape people’s attitudes toward welfare and other redistributive policies.


For Further Reading: Brown-Iannuzzi, J. L., Cooley, E., McKee, S. E., & Hyden, C. (2019) Wealthy Whites and poor Blacks: Implicit associations between racial groups and wealth predict explicit opposition toward helping the poor. Journal of Experimental Social Psychology, 82, 26-34.

Jazmin Brown-Iannuzzi is a faculty member at the University of Kentucky who studies why group disparities persist. Erin Cooley is a faculty member at Colgate University who studies intergroup conflict and discrimination.

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Why is this blog called Character & Context?

Everything that people think, feel, and do is affected by some combination of their personal characteristics and features of the social context they are in at the time. Character & Context explores the latest insights about human behavior from research in personality and social psychology, the scientific field that studies the causes of everyday behaviors.  

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