1

Obama and the End of Racial Priming

Nicholas A. Valentino- University of Michigan

Kosuke Imai- Princeton University

L. Matthew Vandenbroek- The University of Texas at Austin

Teppei Yamamoto- Massachusetts Institute of Technology

Abstract

Evidence has begun to emerge that instead of hastening the “end of race,” Barack Obama’s election may have had just the opposite effect: boosting the impact of white’s racial attitudes on public policies that have nothing at all to do with conflict between blacks and whites. The “chronic accessibility” of race, triggered presumably by the simple existence of a black President, is identified as the causal mechanism at work. We utilize several surveys with national Internet samples to test claims about the chronic linkage between racial attitudes and policies such as health care reform and views of the Tea Party movement. Racial priming theory, in particular, suggests racial rhetoric will be powerful in activating racial attitudes only when it is subtle. We find two striking results. First, as other studies have shown, there exists a strong and stable relationship between racial attitudes, measured both explicitly and implicitly, and attitudes about health care, tea party support, and Obama favorability, and other partisan attitude objects across 3 different experiments employing national samples. Second, these powerful linkages remain even when the issue is discussed using an explicitly racist frame. We suspect the racial priming affect fails to emerge because, where they were once decoupled, racism and inegalitarianism have become highly intertwined. As a result, explicitly racist argumentation no longer leads very many whites to reject a message on egalitarian grounds. An alternative explanation, that racial conservatives are simply more likely to dismiss the charge of racism by claiming the news media are biased, is not sustained.

This study was supported by a grant to the first author and Professor Kosuke Imai of Princeton University from the Social Science Directorate, Political Science Division of the National Science Foundation (#0849858). We are indebted to Larry Bobo and participants at the RAIN initiative meeting at Harvard in October of 2012 for helpful feedback. Ted Brader also provided useful feedback. A previous draft of this paper was presented at the American Political Science Association annual meeting in Washington, D.C., September 5th, 2010. Draft. Please do not cite without permission.

2

Introduction

The 2008 election of the nation’s first black president led many to wonder optimistically

if American had transitioned into a post-racial era. The early returns do not seem confirmatory.

Racial attitudes were powerful predictors of support for Obama (Piston 2010; Kinder and Dale-

Riddle 2011), and his policies (Knowles et al. 2009; Knowles et al. 2010; Tesler and Sears

2010). Since the election there have been decreases in perceptions of racial discrimination in

America but increases in opposition to affirmative action (Valentino and Brader 2011). Support

for social justice, a general domain linked to whites racial attitudes in the past (Kaiser et al.

2009), has also declined. Whites who endorsed Obama also seem to increasingly favor their

racial group in policy competition with blacks, perhaps as a result of a “moral licensing” process

(Effron et al. 2009). The logic goes that if the country could elect a black man president, further

effort to balance the playing field is unnecessary and may, in fact, represent unfair bias against

whites. But is there any systematic evidence for such an underlying backlash?

Numerous high-profile partisan incidents also suggest race plays a continuing role, at

least occasionally. Posters emblazoned with racist visuals and speech, such as depicting Obama

or the first lady as an ape or invoking the “n” word, have appeared at Tea Party rallies. Mark

Williams, a leader of one Tea Party group, penned a “letter to Abe Lincoln” that branded the

NAACP as a racist organization dedicated to unfairly redistributing white wealth to “lazy”

blacks. On the day of the healthcare reform vote, several news outlets reported that Tea Party

demonstrators spat upon and shouted racial epithets at African American house members.

Conservative activist Andrew Breitbart received national attention himself for accusing Shirley

Sherrod, an African American Department of Agriculture employee, of racism by carefully

editing a speech she gave to the NAACP on the topic of racial reconciliation. A conservative

3

radio host, Laura Schlesinger, launched an on-air, epithet laden tirade suggesting the use of the

n-word by whites is protected by the First Amendment. Glenn Beck decried Obama’s “deep

seated hatred for white people or the white culture,” and later rallied supporters at the Lincoln

Memorial on the anniversary of MLK’s “I Have a Dream” speech to “reclaim” the civil rights

movement. A California Republican Central Committee member sent an email to co-workers

depicting Obama as a chimpanzee as evidence that he could not have a birth-certificate.

These incidents, in combination with the early returns from more systematic studies on

the impact of Obama’s election, suggest that me may not, in fact, have witnessed the “end of

race” in America. In fact, some have made an even more provocative claim: Obama’s race may

lead many Americans, especially whites, to respond to every policy proposed by his

administration along racial lines (Tessler & Sears 2010). Put differently, this view suggests

impact of race is not minimal, but chronically high, even in policy domains having little directly

to do with racial redistribution. If this is the case, it would represent a significant change in the

historical process whereby racial attitudes came to influence policy views. It suggests the era of

racial priming- whereby subtle racial cues are required to activate powerful racial attitudes in the

minds of white citizens when they are evaluating national issues- may be ending.

In this paper, we systematically test the hypothesis that racial attitudes have become more

chronically powerful predictors of even non-racial policy preferences. We focus primarily on

healthcare reform, a highly salient issue during our data collection, and which other studies

suggest has become “racialized” (Knowles et al. 2010; Tesler 2010), but also examine views on a

variety of contemporary political figures (Obama, Palin, Glenn Beck) and the Tea Party

Movement. In three national studies, we test the classical racial priming paradigm by comparing

the impact of racial attitudes across three experimental conditions: Implicit racial cues, explicit

4

racial cues, and a neutral control. We find that racial attitudes (measured both implicitly and

explicitly) powerfully predict opinions on a wide variety of partisan and policy topics. Moreover,

unlike in previous studies of racial priming, the predictive power of racial attitudes is robust to

the presence of explicit racist arguments previously shown to neutralize their effects. We explore

several alternatives for the failure of the standard model of racial priming and find evidence for a

striking explanation: Whereas prior to 2008 many white Americans felt both resentful toward

blacks and strongly bound by the norm of egalitarianism, far fewer held this combination of

views in 2010. Instead, highly racially resentful whites also espoused less egalitarian views. As a

result, the ambivalence whites once felt as a result of the opposing pull of these two forces seems

to have have decreased.

Racial Priming Reviewed

Abundant evidence from psychology indicates that recent or frequent activation of ideas

in memory automatically facilitates their use in subsequent judgment tasks (Higgins et al 1985;

Higgins et al 1977; Srull and Wyer 1979; Bargh 1996). This notion is consistent with a view of

memory as organized in an associative network of “schemas,” or related opinion nodes

(Anderson 1983). One salient node activates other relevant nodes in memory, a process dubbed

“spreading activation” (Collins and Loftus 1975). Given the complexity of the political world, it

is hardly surprising citizens typically base candidate evaluations, policy opinions, and the like on

considerations that are most accessible or at the “top of the head” (Taylor and Fiske 1978;

Iyengar and Kinder 1987; Kinder 2003). Experimental studies have shown media messages are a

particularly powerful means of altering the criteria by which citizens evaluate politics (e.g.

Iyengar and Kinder 1987). The association between attitudes and candidate evaluations (or

policy opinions) in a condition where priming occurred is greater than that among a group

5

receiving no prime. Media priming is driven by the “mere attention” of the news to some issues

rather than others (Kinder, 2003, p. 365).

Racial priming, or more generally “group priming” (Jamieson 1992), proposes that subtle

racial cues in news coverage, political advertising or candidate speech activate group attitudes,

boosting their effects on candidate evaluation or policy opinion (Mendelberg 1997, 2001;

Valentino 1999; Valentino et al 2002; Domke 2001; White 2007). At the heart of racial priming

is a societal shift away from explicit elite claims of biogenetic inferiority of blacks and the rise

egalitarian norms (Mendelberg 2001).

Recent evidence abounds that racial stereotypes are activated automatically and often

operate unconsciously (Kawakami et al 1998; Perdue et al 1990; Dovidio et al 1986; Eberhardt et

al 2004; Fazio et al 1995). In fact, it has been suggested such negative stereotypes can be

suppressed only with attention and cognitive effort (Devine 1989; Devine et al 1991). The

racialization of elite discussions of social welfare policy (Gilens 1999; Gilliam 1999) and crime

(Gilliam and Iyengar 2000; Graham and Lowery 2004; Hurwitz and Peffley 2005) has been well-

documented, and suggest that a wealth of subtle media cues may serve as racial primes.

Cue subtlety, in fact, is crucial to Mendelberg’s (2001) Implicit-Explicit (IE) model of

racial priming. A basic premise of her theory is that many whites feel ambivalent about matters

of race because they are pulled in opposite directions by two powerful forces. On the one hand,

there is persistent resentment toward blacks for their perceived refusal to adopt basic American

values such as individualism and hard work, forming the basis of the symbolic racism belief

system (Sears and Kinder 1971; McConahay and Hough 1976; Kinder and Sears 1981; Kinder

and Sanders 1996; Sears and Henry 2003). On the other hand, since the Civil Rights era, a strong

“norm of equality” exerts pressure for whites to reject racially biased or insensitive justifications

6

for a given policy stand. As a result, the theory suggests that racial attitudes will powerfully

effect policy views only if racial cues are subtle, or “implicit.”

Mendelberg (2001) operationalizes the implicit/explicit distinction dichotomously;

explicit messages contain overtly racial wording such as “black” and “African-American,” while

implicit messages cue race only with visual images of African-Americans. Implicit racial

messages may also employ racially coded language such as “inner city,” “poverty” or “welfare”

(see Valentino 1999; Valentino et al 2002; Huber and Lapinski 2006; White 2007). The IE model

has also found support in cross-sectional survey data from presidential campaigns. Jamieson

(1989; 1992) and Mendelberg (1997; 2001) both find strong evidence that coded appeals in the

1988 presidential election—most notably the “Willie Horton” ad aired on behalf of the George

Bush campaign—activated white voters’ racial predispositions. However, whites rejected the

Horton message after media accounts explicitly identified its racist undertones (Mendelberg

2001).

Huber & Lapinski (2008), attempt to replicate the basic predictions of the IE model using

an experiment performed on a large national sample. They test whether an issue advertisement

that explicitly discusses race in its appeal to end welfare primes racial attitudes more powerfully

either than a message which does so implicitly (by not using racial language but which contains a

visual race cue) or one that does not discuss race at all (a neutral message about getting out the

vote). They find no support for the IE model. Instead, their results indicate that racial attitudes

are quite powerful predictors of policy views regardless of whether the message is implicit or

explicit. Their explanation for this null finding has to do with variation in the priming effect

across levels of education. The most educated automatically bring their racial beliefs (and other

predispositions) to bear on their policy views regardless of the message. The least educated can

7

be primed, but they do not reject explicit racial messages so their racial beliefs are triggered

either way.

While a plausible explanation for the null results they find, Huber & Lapinski’s

explanation is not the only possible one, and they hint at another in their paper without testing it.

In their discussion, the authors mention that perhaps Mendelberg’s subjects “had a stronger

attachment to the norm of equality than our respondents, and therefore reacted more negatively

to the explicit appeal” (p. 436). We take up this possibility more explicitly, and suggest that this

reduced pull of egalitarianism might not simply be a function of sampling differences. Instead, it

is possible that resentment has become increasingly tied to inegalitarian views in the population

as a whole.1

Our first goal, then, is to systematically test the classic racial priming paradigm in the

post Obama era. Our hypotheses are drawn directly from the racial priming literature. The

standard model predicts racial attitudes will powerfully affect views of a variety of political

targets (including attitudes toward health care reform and evaluations of partisan leaders such as

Obama, Glenn Beck, and Sarah Palin), but only when racial cues are subtle (implicit). When

racial arguments are made explicit, the influence of racial attitudes should diminish precipitously

as a result of the pull of egalitarian norms. Our experimental design is simple and parallels those

in the racial priming literature discussed above. We will compare the impact of racial attitudes in

conditions exposed to three different frames, one containing explicitly race cues, one containing

implicit race cues, and a control group containing no race cues.

1 Mendelberg (2008) criticizes Huber & Lapinski’s conclusions on a number of methodological grounds. In particular, Mendelberg expresses concern about the potential for a “failure to treat” problem in the large internet-based experiment Huber and Lapinsky perform. The null result, in other words, could also occur if subjects in both explicit and implicit conditions failed to receive or pay attention to the advertisement. We do not take a stand on that debate, but instead replicate the basic tests and explore a distinct substantive explanation for the null result Huber & Lapinski discover.

8

Statistically speaking, we will regress each dependent variable against our racial attitudes

measures and dummy variables for experimental condition in this simple 3 group design:

𝒀 =

𝒃𝟎 + 𝒃𝟏(𝑹𝒂𝒄𝒊𝒂𝒍 𝑨𝒕𝒕𝒊𝒕𝒖𝒅𝒆) + 𝒃𝟐(𝑹𝒂𝒄𝒊𝒂𝒍 𝑨𝒕𝒕𝒊𝒕𝒖𝒅𝒆 ∗ 𝑰𝒎𝒑𝒍𝒊𝒄𝒊𝒕 𝑪𝒖𝒆 ) +

𝒃𝟑(𝑹𝒂𝒄𝒊𝒂𝒍 𝑨𝒕𝒕𝒊𝒕𝒖𝒅𝒆 ∗ 𝑵𝒐 𝒓𝒂𝒄𝒆 𝑪𝒖𝒆) + 𝒃𝟒(𝑰𝒎𝒑𝒍𝒊𝒄𝒊𝒕 𝑪𝒖𝒆) + 𝒃𝟓(𝑵𝒐 𝒓𝒂𝒄𝒆 𝒄𝒖𝒆) + 𝒆. The

excluded group in these models is the explicit racial cue. The IE model predicts that the sum of

𝒃𝟏 and 𝒃𝟐, which measures the total influence of race among the implicit group, will be

significantly larger in magnitude than the standalone 𝒃𝟏, which captures the total effect of racial

attitudes for the explicit group. A small or insignificant 𝒃𝟐, meanwhile, suggests that the explicit

cues failed to activate the norm of equality sufficiently to mitigate the slope on racial attitudes.

For example, in the case of support for new healthcare reforms, the IE model predicts that 𝒃𝟐

will be negatively signed and statistically significant, while 𝒃𝟏will be much smaller in magnitude

because it represents the effect of racial attitudes in the explicit race condition.

Methods

To examine the IE model and racialized discussion of healthcare reform, we conducted

three survey experiments on national samples between May and August 2010 through

YouGov/Polimetrix. Rather than interacting with a live interviewer in person or by telephone,

respondents answered questions over the internet, which we suspect reduces social desirability

pressures and produce greater candor in the interviews. YouGov/Polimetrix uses a sample

matching technique which, although in its infancy, is gaining popularity in academic research

applications, has been shown to produce samples that meet or exceed the quality of those based

on traditional telephone polling (Berrens et al 2003; Sanders et al 2007).1

9

The stimuli for all three experiments were styled after a newspaper website stories

datelined in the Hartford metropolitan area, a region we chose for its civic nickname, “The

Insurance Capital of the World.” Also, the district incumbent, John Larson, is a multi-term

Democrat who voted in favor of the House version of the healthcare bill. An actual Associated

Press story detailing preparations for the 2014 Winter Olympics in Sochi, Russia, was employed

as a control to subject group. All three stories were approximately the same length and did not

differ in layout, author byline or dateline. The stimuli are described in detail below, and in the

Appendix.

Independent variables

In all three experiments, we measured symbolic racism using the standard four-

proposition agree-disagree battery employed by the National Elections Study, indexed to a 0-1

scale (see appendix for details). The measure performed very consistently, with the samples

strongly skewed toward higher levels of symbolic racism. In the third study, which contained the

largest sample, the mean was .66 (s.d.=.29) and a median of .75. The highest possible score of 1

was the modal category (17.6%, n=402). At the opposite end of the scale, just 59 respondents

(2.6% of the sample) received the lowest possible score of zero.

In all three studies, we measured respondents’ automatic preferences for blacks or whites

using a brief version of the Implicit Association Test (hereafter BIAT) developed by Sriram and

Greenwald (2009).2 For this task, respondents categorized photographs and words using their

computer keyboards. After a couple of warm-up exercises, respondents were shown randomized

valence words (Wonderful, Best, Superb, Excellent and Awful, Horrible, Terrible, Worst) and

grayscale headshots of whites and African-Americans.3 In one trial, participants categorized 20

stimuli as either “EUROPEAN AMERICAN or GOOD” or “Anything Else.” The other trial

10

followed the same procedure, but with the new pairing of “AFRICAN AMERICAN or GOOD.”

The order of these trials was randomized, with response times recorded in milliseconds from the

appearance of the word or photo and first keystroke. The BIAT predicts that individuals with an

automatic preference for whites should be slower to categorize stimuli in the non-stereotypical

(black/good) pairing than the stereotypical (white/good) pairing. To eliminate noise from the

data, individuals who averaged more than two seconds per stimulus were discarded as outliers.4

In Study 3 the measure revealed on average a slight prejudice for whites, with a mean difference

in response times of 34 ms, skewed slightly toward white preferences (median 32 ms). The

results were similar in the other two experiments.

In Study 3, respondents’ attitudes toward equality norms were summed in a 0-1 index

built from three standard NES questions, detailed in the appendix. Despite the prevalence of

symbolic racism in this national sample of whites, egalitarian norms enjoyed strong, but hardly

universal, endorsement. A slight majority of our sample (53%) scored at the neutral point or

higher, with about 6% (136) scoring the lowest possible of zero and 11% (254), reaching the

upper bound of 1. The sample mean was .56 (s.d.=.29) with a median of .58.

Dependent Variables

We constructed four distinct measures of healthcare opinion: general approval of the bill,

support for specific provisions that had been proposed during the debate, anticipated effects of

the passed legislation, and anger toward the health bill in general (Study 3 only). The first of

these is the most direct, asked on a five-point approve-disapprove scale (1. strongly approve; 2.

somewhat approve; 3. neither approve nor disapprove; 4. somewhat disapprove; 5. strongly

disapprove):

11

As you have probably heard, health care reform legislation has just been passed by the Congress and signed into law. In general, how strongly do you approve or disapprove of this new legislation?

Support for specific healthcare provisions was similarly gauged on a 5 point scale (Strongly

Oppose to Strongly Support, with a neutral category):

We would like to get your opinion on a few specific health care proposals that have been discussed. Please indicate whether you support or oppose each of the following proposals….

• Creating a government insurance plan for people who cannot afford or are unable to get private insurance (The Public Option)

• Creating insurance cooperatives, sometimes referred to as a Health Care Exchange, from which individuals can buy coverage for prices similar to those paid by employer plans

• Requiring insurance companies to sell insurance to all people, even if they have pre-existing conditions

• Allowing young adults to remain on their parents’ health insurance up to the age of 27, even if they no longer live at home or are in school.

Support for the four provisions was summed to a single (0-1) index. We also measured

respondents’ optimism toward the new healthcare reform law on a 5-point scale (1. Make things

much better; 2. Make things a little better; 3. No difference; 4. Make things a little worse; 5.

Make things much worse):

“Considering the health care legislation that has just become law, for each of the following do you think it would actually make things better for your family, make things worse, or make no difference at all?

• The ability of people with pre-existing medical conditions to get health insurance • Health insurance coverage for people who currently do not have it • Medicare benefits for senior citizens • The overall cost of health care for all Americans • Taxes on the middle class • Taxes on the rich • The quality of health care for families other than your own

These seven effects were indexed to a single, interval-level measure. In Study 3, we also

measured respondents’ anger toward the “healthcare bill in general,” (1. I feel this emotion

strongly; 2. I feel this emotion somewhat; 3. I feel this emotion a little; 4. I do not feel this

12

emotion at all). Finally, we measured respondents’ favorability toward President Barack Obama,

the Tea Party Movement, Glenn Beck and Sarah Palin (Study 3 only).

Results

Study 1

Study 1 was administered May 18-19 to 311 subjects (234 whites). The stimuli depict a

clash between protestors on both sides of the healthcare debate on the day of House vote. In the

implicit condition, the pro-reform group is described as predominantly from Hartford’s urban

core, and depicted in a photograph of actual African-American protestors, while Tea Party

demonstrators are described as being mostly from more affluent suburban areas. The explicit

condition textually identifies the two groups as predominantly black and white, with the photo

caption also mentioning the pictured marchers are in a black neighborhood of West Hartford.

There are 14 implicit/explicit cue pairings in study 1 stimuli, including the headline and

photo caption, as detailed in Table A1. The explicit story uses the word “black” eight times, the

term “African-American” three times, and the word “white” seven times. The explicit condition

defines the terms of the healthcare debate in Hartford as forming around racial dynamics, while

the implicit describes the cleavage as city vs. outlying areas. The most extreme cue in the explicit

condition is when protestors are quoted as chanting “Go home (n-words), no handouts here,”

substituting “freeloaders” in the implicit condition. The expectation of the IE model is that such

an extreme racial cue would trigger the norm of equality and thus suppress the use of racial

attitudes in evaluations of health care reform and contemporary political figures.

The top panel of Table 1 displays the OLS coefficients for the IE models using the

symbolic racism measure as the racial moderator. The top row coefficients are the effect of

13

symbolic racism in the “explicit” conditions, the second row represents the slope deviation from

those effects among those in the “implicit” condition and the third row represents the slope

deviation for the control group. Two patterns are immediately evident: First, across the board in

the explicit condition, symbolic racism is powerfully correlated with conservative attitudes

toward the healthcare bill, Obama, the Beck thermometer, and support of the Tea Party. Second,

we do not find any support for the IE model here. We expected the effect of symbolic racism to

be smaller and perhaps statistically insignificant in the explicit conditions, but larger in the

implicit conditions. However, none of the interaction term coefficients is statistically discernable

from zero, and are substantively tiny. The insignificance of the third row coefficients is also

unexpected. Even in the control group, who read an innocuous feature about the Olympics, the

power of racial attitudes to predict these dependent phenomena was gigantic.

--Table 1 about here--

While resentment stemming from the belief that blacks have been unfairly privileged by

government is clearly linked to judgments of both policies and contemporary political actors, the

BIAT measure allows us to evaluate the impact of more automatic racial prejudice. The BIAT

also serves as an alternative measure of racial attitudes that may not be susceptible to the same

criticisms as symbolic racism: The automatic preference of white over black faces is unlikely to

be related to non-racial ideology or the preference for small government. To test this, we ran the

same regression models replacing symbolic racism with the BIAT scores as the moderator in the

IE regressions. The bottom panel of Table 1 suggests the relationship between automatic racial

preferences and policy views is in the same direction as that of symbolic racism in the explicit

condition. These results are merely suggestive, however, as none of the top row coefficients

attains statistical significance. As with the symbolic racism measure, we found no support for the

14

IE model using the BIAT. If anything, the opposite pattern seemed to emerge. The interactions,

while not significant, are all in the opposite direction of that predicted by the IE model. For

example, reading the implicit story actually eliminates the negative relationship between

automatic prejudice against blacks and approval of healthcare reform present in the explicit

condition. Indeed this pattern holds across all the dependent variables: the sign on the interaction

coefficient in each case indicates the effect of prejudice is smaller, not larger, in the implicit

condition than it is in the explicit condition.

These results are puzzling, since they fall so far from the expectations of the standard

racial priming model. In the case of explicitly measured racial attitudes like symbolic racism, the

frame does not modify its effects on policies or political figures in any way. Even more

surprising is the strong correlation between racial attitudes and the dependent phenomena among

the control group. For the BIAT measure, the pattern is, if anything, the opposite of expectations.

We ran a second study to determine whether the first study or sample was somehow

idiosyncratic.

Study 2

Given the first experiment’s failure to trigger the norm of equality, we redesigned the

stimuli for Experiment 2, which was administered June 17-18 to 321 subjects, this time all white.

The new stories described outrage about a campaign advertisement aired by a fictitious Tea

Party-backed candidate named Tim Stassney seeking the Republican nomination for the 1st

Congressional District of Connecticut.5 To avoid possible participant judgments of media bias—

the explicit condition in the first study had forced the journalist to insinuate whether protesters

were racially motivated, we framed the story around a political ad, with the “journalist” herself

refraining from personal commentary.

15

We also increased the severity of the explicit cues in an effort to activate the norm of

equality more powerfully. In total, there are 15 implicit/ explicit cue pairings in the story

(including headline, photo text and photo caption), which are detailed in Table A2. The explicit

condition includes five uses each of the words “black” and “white,” plus three uses of “African-

American.” The implicit condition still leans heavily on racially coded dichotomies of

urban/suburban and rich/poor. The text of both the implicit and explicit stimuli extensively

details an advertisement entitled “Bleeding us Dry,” in which healthcare supporters are shown

celebrating passage of healthcare reform—represented by the same photograph of African-

American demonstrators edited to appear as a screen shot. In both versions, the ad’s tagline is

“Guess who’s paying for their party.” In the ad, Stassney vows to overturn the healthcare bill,

which he decries as “Congressional Democrats’ giveback” to either “labor unions (implicit)” or

“African-American voters and groups like ACORN and the NAACP (explicit).” In the explicit

condition, Stassney ties the healthcare bill with racialized entitlement programs like welfare and

food stamps, while the comparisons in the implicit condition are “bailouts” and “the stimulus.”

As with the Study 1 stimuli, the fictitious ad described in the story alternates actual

claims made by right wing pundits that the healthcare bill is a form of tyranny or reparations for

slavery. The explicit condition quotes Stassney: “(W)e’re not going to let Big Government make

us pay reparations for slavery now.” The implicit counterpart is “(W)e’re not going to let Big

Government bring tyranny back now.” Underscoring this language, the screen shot photo in the

implicit condition has a graphic reading “Socialist Tyranny,” and the explicit condition reads

“Reparations for slavery.”

The remainder of the story describes complaints about the ad. To avoid activating

subjects’ partisanship, we specifically avoided having any of the critics represent Democratic,

16

African-American or healthcare reform interests. Instead, we ascribed the outcry to “a bipartisan

watchdog group convened by the Connecticut League of Women Voters and the Interfaith

Alliance, a multidenominational church group,” and Stassney’s opponent for the Republican

primary, Mark Zydanowicz.6 In the implicit condition, the bipartisan group complains that the ad

is “unproductive,” while in the explicit condition the group directly calls the ad “racist.”

Zydanowicz is quoted as saying Republicans should not be “pitting whites against blacks” in the

explicit story and “pitting rich against poor” in the implicit story. The story also describes

Stassney as defending his ad, contrasting whites (suburbanites) as those who “play by the rules,

go to work and have insurance” with blacks (city people) who “want the rest of us to foot the bill

for their healthcare.” We also included in the explicit treatment an account of Stassney laughing

off a supporter shouting the “n-word” at a Tea Party rally; The supporter in the implicit treatment

shouts “bums” and “freeloaders.” In summary, if the explicit invocation of race (including

inflammatory epithets) activates the norm of equality and causes respondents to decouple racial

considerations from evaluations of healthcare or political figures, this story should do the trick.

The top panel of Table 2 shows a nearly identical pattern to the one we observed in the

first study. Even the more intense explicit story did not suppress the power of symbolic racism.

Even with the revised news stories, the results for the symbolic racism measure were unchanged;

race remained highly salient, irrespective of condition. Only 3 out of the 7 dependent variables

displayed interaction terms in the theoretically expected direction, and none was close to

statistically significant.

--Table 2 about here--

The results for the BIAT measure (displayed in the bottom panel of Table 2), were

different than those for SR, and different than what we found for the BIAT in Study 1. These

17

tests, in fact, provided modest support for the IE model. The model predicts a weak relationship

between automatic preferences for whites and opinions about various policies and political

figures in the explicit condition, and that is what we found. The BIAT is uncorrelated with any of

the DV’s in the explicit condition. However, in these models the interactions were all in the

expected direction, and were statistically significant in two cases (overall healthcare bill and

Obama approval). These results are the only instance, across all three studies and different

measures of racial attitudes, where the IE model’s predictions were even marginally apparent.

Since this pattern was in the direction suggested by the model, we decided to replicate it with a

larger sample in order to determine whether our resolution of these effects could be improved.

Study 3

Study 3 employed identical stimuli as Study 2, but with a much larger sample in order to

estimate the effect more precisely, and to determine whether the timing of the measurement of

racial attitudes (in the pre-test as opposed to the post test) would alter the result. YouGov/

Polimetrix interviewed a sample of 2,394 voting-age Americans from July 16 to August 8, with

71% of the interviews beginning Aug 1.2

The top panel of Table 3 displays the OLS coefficients for the IE models of dependent

variables administered in Study 3 with symbolic racism as the moderator. It is again clear that

the expectations of the IE model were unmet. Across all dependent variables, the predictive

power of racial resentment is gigantic, with all coefficients in the expected direction and

statistically significant at p < .001. Again, none of the interaction terms is statistically significant,

2 This experiment also employed a measurement design manipulation in which we altered the timing of the measurement of racial attitudes in the pre-test versus the post-test. This is a potentially important distinction, because while the post-test measurement design might suffer from endogeneity bias (the treatment could affect the distribution of responses to the racial attitude measure), the pre-test measurement design also has drawbacks (asking about racial attitudes in the pretest could prime racial sentiments among all subjects, thus eliminating any effect of the prime). In these studies, however, we found very similar results in both pre- and post-test measurement designs. To conserve power, we pool the results across these two designs.

18

indicating the implicit condition and even the control did not increase the association between

racial attitudes and any of the dependent variables shown. Needless to say, these results do not

show evidence of racial priming in the presence of subtle racial media cues. On the contrary,

they tell a story of the very large influence of racial attitudes regardless of the frame with which

healthcare is discussed, or if any frame at all is present.

--Table 3 about here--

The positive BIAT results from Study 2 were also not replicated here. The bottom panel

of Table 3 shows the coefficient for the standalone BIAT measure is in the expected direction in

every regression model of Study 3, and attains conventional statistical significance in all but one

(provisions, p=.11). The results are especially strong for anger toward the healthcare bill—hardly

surprising given the visceral nature of both measures, support for the Tea Party and favorability

toward Sarah Palin. None of the interaction term coefficients comes close to statistical

significance.

Discussion

Our primary conclusion is similar to that given by Huber & Lapinksi (2008): Support for

the IE model failed to materialize across three national experiments with separate (and in one

case very large) samples. The impact of racial attitudes appeared strong and persistent across

conditions, even in the control condition where no information about health care was presented

at all. What explains these null results?

One possibility is a failure to treat: respondents may simply not have been reading the

news story at all. Treatment efficacy problems can loom large in studies such as these: If subjects

are able to avoid reading the news story then racist sentiments would not be rejected. However,

this problem did not occur in the current study. Subjects answered several manipulation checks

19

to identify the topic and frame of the stories they read with high accuracy. From five response

categories—taxes, the mortgage crisis, the Iraq War, healthcare reform, and the Olympics—

about 90% of the implicit and explicit subjects (90.4% and 89.4%) correctly named healthcare as

the main topic. Moreover, about 7% of the subjects in these two groups named taxes, versus

trivial response rates for the remaining categories, suggesting a rhetorical interpretation of the

healthcare debate rather than factual misunderstand of the story. The correct “Olympics”

response was returned by 95.9% of the control group. Additionally, explicit subjects were

significantly more likely than implicit subjects to believe their story emphasized racial conflict as

much or more than class conflict (92% to 53%, p<.001).

Another possible explanation for the failure of the racial priming hypothesis in these

studies is that racial conservatives have begun to reject the calling out of racism in political

communications. In other words, these citizens may simply dismiss the charge of racism as the

work of a biased, “politically correct” news media. If this were the case, then subjects high in

racial resentment should be particularly critical of the explicit racial story: They should feel it is

especially biased, unfair, offensive, disgusting, etc.

Table 4 shows Experiment 3 subjects’ mean ratings of the stories they read on several

dimensions and their correlations between symbolic racism.7 Unsurprisingly, those with

symbolic racism scores over the midpoint of .5 were considerably more critical of the stories

compared to racial liberals, finding them unfair, sensationalized and biased in favor of healthcare

reform. However, racial conservatives and racial liberals exhibited very similar reactions to the

explicitly racial frame compared to the implicit one. For example, regardless of whether a subject

was high or low on SR, the explicit story was considered less fair, more sensationalized, biased,

offensive and disgusting. If racial conservatives were simply dismissing explicit frames

20

compared to implicit ones at a higher rate than liberals, we would see large differences in these

reactions to each condition. Since this was not the case, we must conclude that the rejection of

the story simply because the journalist was “playing the race card” is not the explanation for

finding no racial priming effects in these studies.

--Table 4 about here--

A final explanation for the failure of the racial priming hypothesis in these studies is that

there has been a shift in public norms regarding race and equality. To put it simply, in order for

explicit racial cues to function as predicted by the IE model, the correlation between

inegalitarianism and racial resentment cannot be very high. The reason is that, according to the

theory, highly racially resentful citizens will reject explicitly racist messages because they also

believe in the norm of egalitarianism. These individuals are, then, both above average in

egalitarianism and in racial resentment. As the proportion of the citizenry who has these joint

characteristics of resentment and yet egalitarian norms increases, the correlation between

inegalitarianism and resentment should decrease. One explanation for the lack of a standard

priming effect is that inegalitarianism and racial resentment have become much more tightly

linked since the election of Barack Obama. If this the case, when racially resentful citizens

become aware of the racism in the message, they would not be as likely to reject the message

because they would not be bound by the norm of egalitarianism to do so.

Figure 1 displays the correlation between egalitarianism and racial resentment over time.

The instrumentation throughout the time series is identical for both measures (See Appendix for

exact question wording). From 1986 until just before Obama’s election (in the pre-election

interview of the 2008 ANES), the correlation is moderate. At the beginning of the period, and

fluctuates from a low of .27 (in 1986) to a high of .42 (in 1992). Even in the pre-election poll of

21

the 2008 ANES, the correlation between racial resentment and egalitarianism was only .37- quite

significant but not overwhelming. In the 2010 study, however, the correlation rises to .58, as

very substantial increase. These data suggest that rather than a secular increase in the strength of

this orthogonal correlation, Obama’s election itself marked a strong increase in the linkage

between racial resentment and inegalitarianism.

-Figure 1 about here-

If our hunch is correct, this increase in the linkage between racial resentment and

inegalitarianism must come almost exclusively from a decline in the proportion of these samples

that is high in BOTH egalitarian values and racial resentment. Figure 2 displays a scatterplot of

data from 1990 and 2010 to allow such a test. The left panel depicts the distributions of the same

symbolic racism and egalitarianism measures taken in the 1990 National Elections Study. As

Figure one showed, the correlation rose from -.32 in 1990 to -.58 in 2010, an increase of 82%.

The key to this increase is the lower density of cases in the upper right quadrant of the graph: the

“egalitarian racial resenters”. While very few individuals in 1990 scored below the median on

both egalitarianism and racial resentment (3.2%), a very large proportion in 1990 scored above

the median on both (57.4%). In fact, when we examine the entire time series from 1986 to 2010,

we find that in every survey before Obama’s election, a majority of respondents (between 57%

and 66% of white respondents) score above the median on BOTH racial resentment and

egalitarianism. In 2010, however, things change. A much smaller proportion scored above the

median on both dimensions (35.9%). In other words, the increase in the correlation between

1990 and 2010 was nearly entirely due to the drop in the frequency of highly egalitarian yet

racially resentful respondents. Explicit invocations of racist sentiment cannot trigger strong

backlash and rejection of such arguments if racially resentful respondents are not simultaneously

22

motivated by a norm of egalitarianism. The first leg of Mendelberg’s theory of racial priming-

the ambivalence created by the combination of resentment and the norm of equality in the white

mind- has dissipated.

--Figure 2 about here--

Conclusion

The standard racial priming model suggests that overt expressions of racial hostility are

no longer acceptable, and will make the reader aware of the possibility of the charge of racism,

leading to a move away from the racist position. This process will render racial attitudes

impotent to influence evaluations of issues, candidates and political groups, unless the racial cue

remains subtle. However, the evidence we have collected in three separate studies suggests the

nature of acceptable racial discourse in America may be changing. Regardless of how racially

inflammatory the news coverage of opposition to the recent healthcare reform legislation

championed by Obama was, racial attitudes were strong predictors of opinion. Only in one study

and using one measure of racial attitudes (the Brief Implicit Attitudes Test) did the IE model’s

expectations emerge. Racial resentment and the BIAT were consistent and powerful predictors of

opinions about healthcare, evaluations of Obama, Palin, Beck, and the Tea Party Movement.

It is too early to say whether these findings represent a temporary shift toward the

acceptability of racially inflammatory rhetoric in American politics. The anecdotal evidence still

suggests that leaders and pundits who offer such remarks are still censured and often forced to

resign. Our evidence suggests one possible culprit: News media credibility. Our subjects may

have dismissed explicitly racist news stories as sensationalist and biased, and this might have

ironically allowed them to justify the continued application of racially conservative attitudes in

evaluations of healthcare, Obama, and conservative leaders and movements.

23

These findings add to a growing body of work suggesting Obama’s election, though

appropriately viewed as a healthy sign for U.S. race relations by many, did not greatly diminish

the impact of race in American politics. In fact, it is possible that the social stigma once attached

to racially insensitive and inflammatory rhetoric may have begun to erode as a result of a decline

in the norm of egalitarianism among racial conservatives. Future research might pursue this

avenue much further. Perhaps perceptions of media bias now undermine the application of the

norm of equality: It is the charge of racism itself that has become unfair.

24

References

Anderson, J. R. (1983). The Architecture of Cognition. Harvard University Press, Cambridge,

MA.

Bargh, J. A. (1996). Social Psychology: Handbook of Basic Principles, ed. E. Tory Higgins and

Arie W. Kruglanski, chap. Principles of automaticity. Guilford, New York.

Collins, A. M. and Loftus, E. F. (1975). A spreading activation theory of semantic processing.

Psychological Review 82, 407–428.

Devine, P. G. (1989). Stereotypes and prejudice: Their automatic and controlled components.

Journal of Personality and Social Psychology 56, 1, 680–690.

Devine, P. G., Monteith, M. J., Zuwerink, J. R., and Elliot, A. J. (1991). Prejudice with and

without compunction. Journal of Personality and Social Psychology 60, 6, 817–830.

Domke, D. (2001). Racial cues and political ideology: an examination of associative priming.

Communication Research 28, 6, 728–801.

Dovidio, J. F., Evans, N., and Tyler, R. B. (1986). Racial stereotypes: The contents of their

cognitive representations. Journal of Experimental Social Psychology 22, 1, 22–37.

Eberhardt, J. L., Goff, P. A., Purdie, V. J., and Davies, P. G. (2004). Seeing black: Race, crime,

and visual processing. Journal of Personality and Social Psychology 87, 6, 876–893.

Effron, Daniel A., Jessica S. Cameron, and Benoit Monin. 2009. “Endorsing Obama Licenses

Favoring Whites.” Journal of Experimental Social Psychology 45: 590-93.

Fazio, R. H. (2001). On the automatic activation of associated evaluations: An overview.

Cognition and Emotion 15, 2, 115–141.

Fazio, R. H., Jackson, J. R., Dunton, B. C., and Williams, C. J. (1995). Variability in automatic

activation as an unobtrusive measure of racial attitudes: A bona fide pipeline? Journal of

25

Personality and Social Psychology 69, 6, 1013–1027.

Fazio, R. H. and Olson, M. A. (2003). Implicit measures in social cognition research: Their

meaning and use. Annual Review of Psychology 54, 297–327.

Gilens, M. (1999). Why Americans Hate Welfare. University of Chicago Press, Chicago.

Gilliam, F. D. (1999). The “welfare queen” experiment: How viewers react to images of African-

American mothers on welfare. Nieman Reports 53, 2, 112–119.

Gilliam, F. D. and Iyengar, S. (2000). Prime suspects: The influence of local television news on

the viewing public. American Journal of Political Science 44, 3, 560–573.

Graham, S. and Lowery, B. S. (2004). Priming unconscious racial stereotypes about adolescent

offenders. Law and Human Behavior 28, 5, 483–504.

Higgins, E., Bargh, J., and Lombardi,W. (1985). The nature of priming effects on categorization:

Learning, memory, and cognition. Journal of Experimental Psychology 21, 1, 59–69.

Higgins, E., Rholes, W. S., and Jones, C. R. (1977). Category accessibility and impression

formation. Journal of Experimental Social Psychology 13, 2, 141–154.

Huber, G. A. and Lapinski, J. S. (2006). The “Race Card” revisited: Assessing racial priming in

policy contests. American Journal of Political Science 50, 2, 421–440.

Huber, G. A. and Lapinski, J. S. (2008). Testing the implicit-explicit model of racialized political

communication. Perspectives on Politics 6, 1, 125–134.

Hurwitz, J. and Peffley, M. (2005). Playing the race card in the post-Willie Horton era. Public

Opinion Quarterly 69, 1, 99–112.

Iyengar, S. (1991). Is Anyone Responsible: How Television Frames Political Issues. The

University of Chicago Press, Chicago.

Iyengar, S. and Kinder, D. R. (1987). News that matters: Television and American Opinion. The

26

University of Chicago Press, Chicago.

Iyengar, S., Peters, M. D., and Kinder, D. R. (1982). Experimental demonstrations of the “not-

so-minimal” consequences of television news programs. American Political Science

Review 76, 4, 848–854.

Jamieson, K. H. (1989). Context and meaning in campaign advertising. American Behavioral

Scientist 32, 4, 415–424.

Jamieson, K. H. (1992). Dirty Politics. Oxford University Press, Oxford.

Kaiser, Cheryl R., Benjamin J. Drury, Kerry E. Spalding, Sapna Cheryan, and Laurie T. O’Brien.

2009. “The Ironic Consequences of Obama’s Election: Decreased Support for Social

Justice.” Journal of Experimental Social Psychology 45: 556-59.

Kawakami, K., Dion, K. L., and Dovidio, J. F. (1998). Racial prejudice and stereotype activation.

Personality and Social Psychology Bulletin 24, 4, 407–416.

Kinder, D. R. (1993). Oxford Handbook of Political Psychology, eds. David O. Sears, Leonie

Huddy, and Robert Jervis, chap. Communication and Politics in the Age of Information.

Oxford University Press, New York.

Kinder, D. R. and Sanders, L. M. (1996). Divided by Color: Racial Politics and Democratic

Ideals. The University of Chicago Press, Chicago.

Kinder, D. R. and Sears, D. O. (1981). Prejudice and politics: Symbolic racism versus racial

threats to the good life. Journal of Personality and Social Psychology 40, 414–431.

Kinder, Donald R., and Allison Dale-Riddle. 2011. The End of Race? Obama, 2008, and Racial

Politics in America. Forthcoming, Yale University Press.

Knowles, Eric D., Brian S. Lowery, and Rebecca L. Schaumberg. 2009. “Anti-Egalitarians for

Obama? Group-dominance Motivation and the Obama Vote.” Journal of Experimental

27

Social Psychology 45: 965-69.

Knowles, Eric D. Brian S. Lowery, Rebecca L. Schaumberg. 2010. “Racial prejudice predicts

opposition to Obama and his health care reform plan.” Journal of Experimental Social

Psychology, 46, (2): 420-423.

Lenz, G. S. (2008). Learning and opinion change, not priming: Reconsidering the priming

hypotheses. American Journal of Political Science 53, 4, 827-37.

McConahay, J. B. and Hough, J. (1976). Symbolic racism. Journal of Social Issues 32, 32–36.

Mendelberg, T. (1997). Executing Hortons: Racial crime in the 1988 presidential campaign.

Public Opinion Quarterly 61, 2, 134–157.

Mendelberg, T. (2001). The Race Card: Campaign Strategy, Implicit Messages, and the Norm of

Equality. Princeton University Press, Princeton, NJ.

Mendelberg, T. (2008). Racial priming revived. Perspectives on Politics 6, 1, 109–123.

Perdue, C. W., Dovidio, J. F., Gurtman, M. B., and Tyler, R. B. (1990). Us and them: Social

categorization and the process of intergroup bias. Journal of Personality and Social

Psychology 59, 3, 475–486.

Piston, Spencer. 2010. ‘‘How Explicit Racial Prejudice Hurt Obama in the 2008 Election.’’

Political Behavior 32(4):431–51.

Pyszczynski, Tom, Carl Henthorn, Matt Motyl, Kristel Gerow. (2010). Is Obama the Anti-

Christ? Racial priming, extreme criticisms of Barack Obama, and attitudes toward the

2008 US presidential candidates. Journal of Experimental Social Psychology 46, 5, 863-6

Sears, D. O. and Henry, P. (2003). The origins of symbolic racism. Journal of Personality and

Social Psychology 85, 2, 259–275.

Sears, D. O. and Kinder, D. R. (1971). Los Angeles: Viability and Prospects for a Metropolitan

28

Landscape, ed. Werner Z. Hirsch, chap. Racial Tensions and Voting in Los Angeles.

Praeger, New York.

Srull, T. K. and Wyer, R. S. (1979). The role of category accessibility in the interpretation of

information about persons: Some determinants and implications. Journal of Personality

and Social Psychology 37, 1660–1672.

Taylor, S. E. and Fiske, S. (1978). Advances in Experimental Social Psychology, ed. Leonard

Berkowitz, chap. Salience, Attention, and Attribution: Top of the Head Phenomena, 249–

288. Academic Press, New York.

Tesler, Michael, and David O. Sears. 2010. Obama’s Race: The 2008 Election and the Dream of

a Post-Rcial America. Chicago: University of Chicago Press.

Valentino, N. A. (1999). Crime news and the priming of racial attitudes during evaluations of the

president. Public Opinion Quarterly 63, Fall, 293–320.

Valentino, N. A., Hutchings, V. L., Banks, A. J., and Davis, A. K. (2008a). Selective exposure in

the internet age: Emotions as triggers for contemporary political information seeking.

Political Psychology

Valentino, N. A., Hutchings, V. L., Banks, A. J. B., and Davis, A. K. (2008b). Is a worried

citizen a good citizen? Emotions, political information seeking, and learning via the

internet. Political Psychology 29, 2, 247–273.

Valentino, N. A., Brader, T., Groenendyk, E., Gregorowicz, K., and Hutchings, V. L. 2011.

“Election Night’s Alright for Fighting: The Role of Emotions in Political Participation.”

The Journal of Politics 73(1): 156-170.

Valentino, N. A., Hutchings, V. L., and White, I. K. (2002). Cues that matter: How political ads

prime racial attitudes during campaigns. American Political Science Review 96, 1, 75–90.

29

Valentino, N. A. and Brader, T. (2011). “The Sword’s Other Edge: Perceptions of

Discrimination and Racial Policy Opinion after Obama.” Public Opinion Quarterly,

75(2): 201-226

Washington Post. 'Tea party' protesters accused of spitting on lawmaker, using slurs. Paul Kane

Saturday, March 20, 2010.

White, I. K. (2007). When race matters and when it doesn’t: Racial group differences in response

to racial cues. American Political Science Review 101, 2, 339–354.

Wittenbrink, B., Judd, C. M., and Park, B. (1997). Evidence for racial prejudice at the implicit

level and its relationship with questionnaire measures. Journal of Personality and Social

Psychology 72, 2, 264–274.

30

Table 1. Study 1 Results Comparing the Impact of Racial Attitudes in Implicit vs. Explicit Race Cues in Healthcare Reform News

Note: All variables are coded 0-1.

Symbolic RacismHC Bill

ApprovalHC

Provisions

Predict Negative Effects

Obama Approval

Tea Party Approval

Beck Approval

Symbolic Racism -.94*** -.58*** .64*** -.94*** 1.01*** .95***(.16) (.11) (.12) (.17) (.15) (.18)

SR x Implicit .09 -.01 -.07 .02 -.07 -.12(.21) (.15) (.16) (.22) (.20) (.23)

SR x Control .16 -.02 -.21 -.03 -.22 -.12(.20) (.14) (.16) (.22) (.19) (.22)

Implicit -.09 -.00 .07 -.05 .07 .07(.15) (.11) (.11) (.16) (.14) (.17)

Control -.07 .03 .13 .05 .10 -.01(.15) (.11) (.11) (.16) (.14) (.17)

Constant .99*** .98*** .08 1.03*** -.12 -.12(.12) (.08) (.09) (.13) (.11) (.14)

r-squared .35 .43 .31 .37 .40 .37N 226 226 186 222 226 190

BIAT ScoreHC Bill

ApprovalHC

Provisions

Predict Negative Effects

Obama Approval

Tea Party Approval

Beck Approval

BIAT Score (-1 to 1) -.25 -.15 .18 -.25 .13 .10(.20) (.14) (.15) (.21) (.20) (.20)

BIAT x Implicit .35 .34 -.09 .34 -.13 -.16(.30) (.22) (.23) (.33) (.30) (.32)

BIAT x Control -.05 -.15 -.03 -.01 .17 .01(.27) (.20) (.21) (.29) (.17) (.27)

Implicit -.02 -.02 .01 -.03 -.03 -.02(.07) (.05) (.06) (.08) (.07) (.08)

Control .08 .05 -.03 .08 -.11 -.13^(.07) (.05) (.05) (.07) (.07) (.07)

Constant .34*** .58*** .52*** .39*** .60*** .55***(.05) (.04) (.04) (.06) (.05) (.05)

r-squared .03 .04 .02 .03 .03 .03N 217 216 178 213 217 185Cells are Unstandardized OLS Coeff icients (se) ^p<.10, *p<.05, **p<.01, ***p<.001

31

Table 2. Study 2 Comparing the Impact of Racial Attitudes in Implicit vs. Highly Explicit Race Cues in Healthcare Reform News

Note: All variables are coded 0-1

Symbolic RacismHC Bill

ApprovalHC

Provisions

Predict Negative Effects

Obama Approval

Tea Party Approval

Beck Approval

Palin Approval

Symbolic Racism -.97*** -.49*** .54*** -1.05*** 1.06*** .78*** .86***(.11) (.08) (.09) (.12) (.11) (.11) (.12)

SR x Implicit .01 -.13 .11 .06 -.07 .06 -.05(.16) (.12) (.12) (.16) (.15) (.15) (.16)

SR x Control .20 -.07 .00 .11 -.10 .02 -.03(.16) (.12) (.13) (.17) (.16) (.16) (.17)

Implicit .01 .08 -.03 -.07 .05 -.06 -.00(.12) (.09) (.09) (.12) (.11) (.11) (.12)

Control -.13 .01 .01 -.11 .05 .01 .01(.12) (.09) (.09) (.12) (.11) (.12) (.13)

Constant 1.00*** .92*** .16* 1.10*** -.13 -.05 -.13(.08) (.09) (.06) (.08) (.08) (.08) (.09)

r-squared .40 .30 .33 .42 .46 .35 .33N 309 307 274 307 309 307 309

BIAT ScoreHC Bill

ApprovalHC

Provisions

Predict Negative Effects

Obama Approval

Tea Party Approval

Beck Approval

Palin Approval

BIAT Score (-1 to 1) .20 .08 -.05 .26 -.11 -.08 -.20(.18) (.13) (.14) (.19) (.19) (.17) (.18)

BIAT x Implicit -.62* -.30 .28 -.62* .35 .39 .33(.28) (.20) (.21) (.30) (.28) (.26) (.28)

BIAT x Control -.27 -.13 .12 -.16 .05 .07 -.03(.28) (.20) (.21) (.30) (.28) (.26) (.28)

Implicit .03 -.01 .02 .00 .00 -.02 -.02(.06) (.04) (.04) (.06) (.06) (.05) (.06)

Control .01 -.04 .01 -.02 -.00 .04 .01(.06) (.04) (.04) (.06) (.06) (.05) (.05)

Constant .34*** .60*** .54*** .38*** .58*** .47*** .44***(.04) (.03) (.03) (.04) (.04) (.04) (.04)

r-squared .02 .01 .01 .02 .01 .01 .01N 306 303 266 301 306 305 306Cells are Unstandardized OLS Coeff icients (se) ^p<.10, *p<.05, **p<.01, ***p<.001

32

Table 3. Study 3 Comparing the Impact of Racial Attitudes in Implicit vs. Highly Explicit Race Cues in Healthcare Reform News on Large Sample

Symbolic RacismHC Bill

ApprovalHC

Provisions

Predict Negative Effects

Angry at HC Bill

Obama Approval

Tea Party Approval

Beck Approval

Palin Approval

Symbolic Racism -.81*** -.47*** .47*** .75*** -.87*** .84*** .74*** .74***(.03) (.03) (.02) (.04) (.04) (.03) (.03) (.04)

SR x Implicit .02 .03 -.03 -.05 .03 -.04 -.01 -.07(.05) (.04) (.04) (.06) (.05) (.05) (.05) (.05)

SR x Control .06 .01 -.06 -.01 -.08 .01 .03 -.07(.07) (.05) (.05) (.08) (.07) (.07) (.07) (.07)

Implicit -.01 -.01 .02 .04 -.01 .02 .00 .02(.03) (.03) (.03) (.04) (.04) (.03) (.03) (.04)

Control -.01 -.00 -.01 .01 .07 -.03 -.03 .02(.05) (.04) (.04) (.06) (.05) (.05) (.05) (.05)

Constant .89*** .91*** .22*** .05 .94*** .01 -.03 -.05(.02) (.02) (.02) (.03) (.03) (.02) (.02) (.03)

r-squared .36 .25 .24 .25 .39 .39 .33 .28N 2281 2259 2214 2259 2282 2280 2279 2276

BIAT ScoreHC Bill

ApprovalHC

Provisions

Predict Negative Effects

Angry at HC Bill

Obama Approval

Tea Party Approval

Beck Approval

Palin Approval

BIAT Score (-1 to 1) -.14* -.08 .12* .16* -.14* .17* .24*** .21**(.07) (.05) (.05) (.08) (.07) (.07) (.07) (.07)

BIAT x Implicit .03 .05 -.06 -.04 .03 -.03 -.10 -.09(.10) (.07) (.07) (.11) (.10) (.10) (.09) (.10)

BIAT x Control -.09 -.06 -.03 -.10 -.10 -.01 -.06 -.05(.15) (.10) (.10) (.16) (.15) (.15) (.14) (.14)

Implicit -.02 -.01 .01 .02 -.01 .01 .01 -.01(.02) (.01) (.01) (.02) (.02) (.02) (.02) (.02)

Control .02 -.01 -.04* .01 .01 -.01 .01 -.02(.03) (.02) (.02) (.03) (.03) (.03) (.02) (.03)

Constant .38*** .61 .51 .52 .39*** .54*** .44*** .42***(.01) (.01) (.01) (.01) (.03) (.01) (.01) (.01)

r-squared .01 <.01 .01 <.01 .01 .01 .01 .01N 2059 2035 2000 2044 2058 2058 2055 2054Cells are Unstandardized OLS Coeff icients (se) ^p<.10, *p<.05, **p<.01, ***p<.001

33

Table 4. Correlations of Study 3 News Judgments of Stimuli with Symbolic Racism

34

Figure 1.

Note: Data for years 1986-2008 are from ANES face-to-face surveys. Data for 2010 is from the YouGovPolimetrix Internet Sample.

.27

.33 .35

.42

.32

.40 .41

.37

.58

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.55

0.6

1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

R

Correlation Between Inegalitarianism and Racial Resentment 1986-2008

Note: Data missing in years without markers

35

Figure 2. Scatterplot of Symbolic Racism and Norm of Equality in the 1990 National Elections Study and Study 3

0.5

1S

ymbo

lic R

acis

m

0 .5 1Equality

1990 NES

0.5

1S

ymbo

lic R

acis

m

0 .5 1Equality

2010 Experiment Survey

r =-.32*** 39% high on both dimensions r =-.58*** 26% high on both dimensions

36

Appendix Table 1A: Textual Cues in Implicit/ Explicit Stories (Study 1)

Explicit (Black vs. White)

Implicit (City vs. Suburb)

Headline: In World’s Insurance Capital, Blacks and Whites Clash over Passage of Health Care Bill

Headline: In World’s Insurance Capital, Residents Clash over Passage of Health Care Bill

Caption: Dozens of health reform advocates celebrate in a black neighborhood of West Hartford.

Caption: Dozens of health reform advocates celebrate in their West Hartford neighborhood.

And racial tensions are running high. And tensions are running high. Hartford is more than 38 percent African-American, and non-coverage is especially concentrated in decaying African-American neighborhoods…

Hartford has a poverty level of almost 30 percent, and non-coverage is especially concentrated in decaying urban core neighborhoods…

…said Margaret Hall, who despite working a pair of part-time jobs is among the black inner-city residents without insurance.

…said Margaret Hall, who despite working a pair of part-time jobs is among the inner-city residents without insurance.

The simmering racial intensity surrounding the reform debate threatened to boil over at a Tea Party protest held on the day of the House vote…

The simmering emotional intensity surrounding the reform debate threatened to boil over at a Tea Party protest held on the day of the House vote…

Racist tempers flared and taunts flew outside Larson’s office in suburban West Hartford.

Tempers flared and taunts flew outside Larson’s office in suburban West Hartford.

South Main Street acted as an uneasy no man’s land separating white and black protestors

South Main Street acted as an uneasy no man’s land separating anti-reform and pro-reform protestors

One white protester argued his community should not have to support blacks from the inner city. The man, who refused to give his name, said “many of these people are criminals, drug addicts, and have bad credit, so why should they get free health care from us?”

According to a recent health department report, many of the uninsured have past histories of arrests, substance abuse, and even bad credit, all of which limit opportunities for the kind of jobs that provide benefits.

Meanwhile, county estimates show coverage is widespread in mostly white suburban and outlying areas. This racial dynamic forms the battle lines in the debate.

Meanwhile, county estimates show coverage is widespread in affluent suburban and outlying areas. This dynamic forms the battle lines in the debate.

Several whites chanted racial epithets: “Go home (n-words), no handouts here.”

Several Tea Party protestors chanted angry epithets, “Go home freeloaders, no handouts here.”

Another white protester exclaimed: “Do I have to spell it out for you? It’s a giveback to all the blacks who got them elected,” West Hartford resident Robert McFadden said… “Between welfare, food stamps and all that, the government is bleeding us dry. At some point blacks are going to have to stop looking for handouts and take responsibility for themselves.”

“Do I have to spell it out for you? It’s a giveback to all the unions and special interests who got Democrats elected,” West Hartford resident Robert McFadden said… “Between the bailouts, the stimulus and all that, the government is bleeding us dry. At some point Democrats are going to have to look out for all Americans.”

Glen Beck... likened the Democratic Party’s healthcare initiative to reparations for slavery.

Glen Beck… likened the Democratic Party’s healthcare initiative to socialism.

“This is about the African-American pressure groups downtown trying to get something for nothing,” said Tim Stassney of the Connecticut Tea Party Patriots. “Why is it that all whites seem to play by the rules, get jobs and have insurance, but black people want the rest of us to foot the bill?”

“This is about the urban and labor pressure groups downtown trying to get something for nothing,” said Tim Stassney of the Connecticut Tea Party Patriots. “Why is it that all of those outside the city play by the rules, get jobs and have insurance, but the city people want the taxpayers to foot the bill?”

37

Table 2A: Cues in Implicit/ Explicit Stories (Experiments 2 and 3) Implicit

(City vs. Suburb) Explicit

(Black vs. White)

Headline: Critics Demand Conn. House Candidate Remove ‘Inflammatory’ Ad

Headline: Critics Demand Conn. House Candidate Remove ‘Racist’ Ad

Photo Caption: Critics have accused the Tea Party-backed Stassney of stoking urban-suburban tensions…

Photo Caption: Critics have accused the Tea Party-backed Stassney of stoking racial tensions...

Photo Text: Socialist Tyranny Photo Text: Reparations for Slavery …one of the candidates is being accused by others of exploiting fault lines between city and suburb.

…one candidate is being accused by others of exploiting fault lines between blacks and whites.

The one minute spot juxtaposes the musical hit “Dancing in the Streets” with images of Hartford residents

The one minute spot juxtaposes the Motown hit “Dancing in the Streets” with images of black Hartford residents…

Stassney appears on camera vowing to repeal the healthcare bill, calling it Congressional Democrats’ giveback to labor unions.

Stassney appears on camera vowing to repeal the healthcare bill, calling it Congressional Democrats’ giveback to African-American voters and groups like ACORN and the NAACP.

“Between the bailouts, the stimulus and all that, the government is bleeding us dry,” Stassney says.

“Between welfare, food stamps and all the other entitlements, they’re bleeding us dry,” Stassney says.

The ad concludes with Stassney… likening healthcare reform to socialism.

The ad concludes with Stassney… likening healthcare reform to reparations for slavery.

“…we’re not going to let Big Government bring tyranny back now.”

“…we’re not going to let Big Government make us pay reparations for slavery now.”

…Zydanowicz respondend that the ad just reopens tensions between poor residents of the city and wealthy suburbanites.

…Zydanowicz responded that the ad is a blatantly racist appeal that reopens tensions between black residents of the city and white suburbanites.

“We don’t want to win by pitting rich against poor…” “We don’t want to win by pitting whites against blacks…” Hartford has a poverty level of almost 30 percent, and non-coverage is especially concentrated in decaying urban core neighborhoods… coverage is widespread in affluent suburban and outlying areas.

Hartford is more than 38 percent African-American, and non-coverage is especially concentrated in decaying African-American neighborhoods… coverage is widespread in mostly white suburban and outlying areas.

A bipartisan watchdog group… has condemned the ad as unproductive…

A bipartisan watchdog group… has condemned the ad as racist…

“Why is it that we suburbanites play by the rules, go to work and have insurance, and then the city people want the rest of us to to foot the bill for their health care?”

“Why is it that the white Hartforders seem to play by the rules, go to work and have insurance, but black people want the rest of us to foot the bill for their health care?”

Stassney… drew criticism for laughing off one supporter’s shouting “bums” and “freeloaders” at a group of pro-reform protestors.

Stassney… drew criticism for laughing off one supporter’s shouting of the n-word at a group of pro-reform protestors.

Racial Resentment Measures:

• The Irish, Italians, Jews and many other minorities overcame prejudice and worked their way up. Blacks should do the same without any special favors.*

• It is really a matter of not trying hard enough; if Blacks would only try harder they could be just as well off as Whites.*

38

• Generations of slavery and discrimination have created conditions that make it difficult for Blacks to work their way out of the lower class.

• Over the past few years, Blacks have gotten less than they deserve. *(Scale Reversed)

Norm of Equality Measures:

• Our society should do whatever is necessary to make sure that everyone has an equal opportunity to succeed.

• If people were treated more equally in this country we would have many fewer problems. • The country would be better off if we worried less about how equal people are.**(Scale

Reversed)

39

Notes 1 Respondents are recruited into the firm’s large volunteer pool. Subjects receive small

incentives. From this pool, subjects are selected by matching to a theoretical “target matrix”- a

truly random sample drawn from a commercial sampling frame with good coverage of the U.S.

population. Each subject from the target matrix is matched to a member of the pool via a

number of characteristics (age, gender, education, party ID, ideology, and political interest).

2 Our most significant change to Sriram and Greenwald’s (2009) BIAT protocol was in

categorization. Their BIAT uses photographs of insects and flowers paired with the GOOD and

ANYTHING ELSE groupings, while we used racial words and photographs of racially

identifiable faces. Also, our IAT uses the F and J keys, rather than the E and I. Our procedure

used slightly different screen colors slightly from the original and our instructions for which key

to press remained onscreen throughout each task. Further information about the BIAT is

available at http://www.millisecond.com/download/samples/v3/IAT/.

3 The photographs were downloaded from stimulus sets made available to researchers by Project

Implicit, Harvard University http://www.projectimplicit.net/stimuli.php.

4 We lost BIAT data for 10-15% of cases in each experiment, but sufficient cases remained for

analysis.

5 We are grateful to Adam Berinsky for his helpful comments on drafts of the implicit and

explicit stimuli used in Experiments 2 and 3.

6 Mark Zydanowicz was an actual candidate for the 1st District race Republic Primary.

7 Responses were scaled 1-5, from “Describes very well” to “does not describe the story at all.”