Pundits and politicians debated whether race was implicated in the rancorous public forums and demonstrations over health care reform. Research suggests that for many white Americans, racial predispositions play a greater role in their opinions on health care than non-racial predispositions. Building on this work, I examine the extent to which anger uniquely activates white racial attitudes and increases their effect on preferences for health care reform. My theory suggests this effect occurs because anger and thoughts about race are tightly linked in memory. Using a nationally representative experiment over two waves, I induced several emotions to elicit anger, fear, enthusiasm, or relaxation. The results show that anger uniquely pushes racial conservatives to be more opposing of health care reform while it triggers more support among racial liberals. On the other hand, anger does not enhance the effect of race-neutral principles on health care reform.
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In fact, Price et al. (2006) find that people dissatisfied with the nation’s health care system feel more strongly about health care policy.
The whole sample was more likely to react with dissatisfaction (48 %) as opposed to anger (19 %). Of those that reacted with anger, they were most angry about “the government not representing the people” and “health care reform.”
This accusation came from an interview on NBC Nightly News with Brian Williams. http://www.msnbc.msn.com/id/3032619/ns/nightly_news#32867107.
What differentiates appraisal theory from the AI model in terms of anger is the issue of blame. The AI model is silent on the issue of blame, perhaps, because the aversion dimension includes other negative emotions like disgust and contempt. Besides the disposition system, Marcus et al. (2000) also propose the surveillance system. Under this system, anxiety stems from novel threats and prompts greater attention and cognitive engagement.
Participants in the Knowledge Network panel are recruited by telephone through random digit dialing. Respondents that do not have access to the Internet are provided access through Web TV, free of charge. The response rate for wave 1 was 71 and 78 % for wave 2.
Several subjects were dropped from the analysis because they failed to follow proper instructions. The results are similar substantively and statistically if these respondents are included.
I use weights since my goal is to estimate the effect of the manipulation for the entire population under study. Knowledge Networks (KN) provides post-stratification weights, which are derived from distributions for gender, age, race, education, Census Region, metropolitan area, and Internet access. The distributions are adjusted based on data from the U.S. Census Bureau’s Current Population Survey. More information about KN procedures can be obtained from their website (www.knowledgenetworks.com).
This design has a potential drawback of its own related to biased mortality between the first and second waves. If some racially conservative respondents are turned off by the measures of racial attitudes in the pre-test, they might have been more likely to opt out of the second wave. Fortunately, the mortality rate was equivalent across the two waves—no biases occurred between waves 1 and 2 on variables such as symbolic racism (chi-squared =11.21, p=.796) and partisanship (chi-squared=1.23, p =.541).
For the relaxed condition, there was no image. Paul Ekman’s archival of emotional expression did not include an image of someone who was relaxed. The prompt for the relaxed condition stated “Now we would like you to describe in general things that make you feel RELAXED. It is okay if you don't remember all the details, just be specific about what exactly it is that makes you RELAXED and what it feels like to be RELAXED. Please describe the events that make you feel the MOST RELAXED, these experiences could have occurred in the past or will happen in the future. If you can, write your description so that someone reading it might even feel RELAXED.”
The reliability of the coders was high: Cronbach’s alpha for anger = .90, fear = .93 and enthusiasm = .91. The output across conditions in the emotion induction task was nearly identical, as subjects in the anger condition wrote an average of 30 words in comparison to 33 words for the fear condition, 28 words for the enthusiasm condition, and 27 words for the relaxed condition.
Because my hypothesis is concerned with the effect of anger relative to no emotional state, I use the relaxed condition as the baseline group.
When I take out the control variables the direction and magnitude of the coefficients are essentially the same. Furthermore, when I control for partisanship, my key effects still hold up across the different models. The variables are described in the “Measurement Appendix”.
I calculate the predicted probabilities by manipulating the emotion variables while holding all the other independent variables at their own values observed in the data and then averaging over all of the cases. (See Hanmer and Kalkan 2013 for a more detailed description of this approach).
A similar shift (86-points) occurs for respondents in the fear condition.
To determine if these differences were statistically significant, I ran a direct test of the differences in the estimated probabilities of those scoring high in symbolic racism for the anger and control conditions. The test shows that the effect of the anger group is statistically different from the control group for whites at the very high end of the symbolic racism scale. The difference between the two groups is .09 with a confidence interval between .002 and .178. Since the confidence interval does not overlap with zero, I can conclude that the effect is statistically significant at the 90 % confidence interval.
Similar to the difference test for those high in symbolic racism, I find that the effect of the anger condition is statistically different from the control condition (−.12) among those low in symbolic racism. This effect has a confidence interval between −.246 and −.024. Since this effect doesn’t overlap with zero, it is statistically significant at the 90 % confidence interval.
However, it is important to note that the interactive effect between the fear condition and ideology comes close to be statistically significant (p value = .127).
These results are available from the author upon request.
In this study, the correlation between symbolic racism and ideology is .40 (p ≤ .001)
The difference between the anger condition and the control condition for those at the very high end of the symbolic racism scale is significant at the 87 % confidence interval.
The difference between the anger condition and the fear condition for those high in symbolic racism is significant at the 90 % confidence interval.
I also found no significant effects when looking at race-neutral ideological principles.
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The author thanks Sanata Sy-Sahande and Kerry Jones for excellent research assistance, and Daniel Biggers, Christina Greer, Eric Groenendyk, Michael Hanmer, Vincent Hutchings, Karen Kaufmann, Eric McDaniel, and Nicholas Valentino, as well as attendees of the American Politics Workshop at Georgetown University for helpful feedback. Time-Sharing Experiments for the Social Sciences collected the data.
Facial Expressions Used in Emotion Induction Task
For Table 2, Anger and Fear are dummy variables, where 1=if subjects are in the treatment condition and 0= if subjects are in the relaxed condition. In column 1 of Table 3, the control group was the enthusiasm condition. In column 2 of Table 3, enthusiasm is a dummy variable, where 1=if subjects are in the treatment condition and 0= if subjects are in the relaxed condition.
Symbolic Racism is recoded on a 0-1 scale where a higher value is the more racially conservative position. The specific items included: “Generations of slavery and discrimination have created conditions that make it difficult for blacks to work their way out of the lower class”, “It is really a matter of some people not trying hard enough; if blacks would only try harder they could be just as well off as whites”, “Irish, Italian, Jewish and many other minorities overcame prejudice and worked their way up. Blacks should do the same without any special favors”, and “Over the past few years, blacks have gotten less than they deserve”.
Ideology is recoded onto a 0-1 scale where the highest value corresponds to identifying as extremely conservative. The specific item was “In general, do you think of yourself as… extremely liberal, liberal, slightly liberal, moderate, slightly conservative, conservative, extremely conservative”.
Limited government is recoded onto a 0-1 scale where 0= increase government spending and 1=reduce government spending. The specific item is “Some people think the government should provide fewer services in order to reduce spending. These people are at point 1 of the scale. Other people feel it is important for the government to provide more services even if it means an increase in taxes. These people are at point 7 of the scale. Where would you place yourself on this scale, or haven’t you thought much about this?”
Health Care Reform is a dummy variable recoded 0-1 with 1 equals opposition to reform. The specific item is “As of right now, do you favor or oppose Barack Obama and the Democrats’ Health Care reform bill”. The response options were yes =I favor the health care bill or no =I oppose the health care bill.
Employed is recoded onto a 0-1 scale where 0=unemployed, .5=unemployed but retired or disabled, and 1=employed.
Urban is a dummy variable where 1=lives in a metro area and 0=does not live in a metro area.
South is a dummy variable, where 0=non-southern resident and 1=southern resident. The southern states are Alabama, Arkansas, Delaware, D. C., Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia.
Income is recoded onto a 0-1 scale where the higher value corresponds to highest income bracket.
Own Home is a dummy variable where 0=does not own home and 1=own home.
Political Discussion is a measure of several political topics respondents’ mention in their open-ended responses to the emotion inductions. I had two research assistants code for whether respondents mentioned eight political or racial issues: crime, welfare, civil rights (e.g. voting rights, free speech, and freedom of religion), terrorism, education, health care, foreign policy, and economy (e.g. inflation, jobs, unemployment, recession). The Cronbach’s alpha (.70) reveals a high level of reliability across the two coders.
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Banks, A.J. The Public’s Anger: White Racial Attitudes and Opinions Toward Health Care Reform. Polit Behav 36, 493–514 (2014). https://doi.org/10.1007/s11109-013-9251-3
- Health care reform
- Public opinion