1. Hard White: Outgroup Hostility and the Trump 2016 Vote Sanford F
Hard White: Outgroup Hostility and the Trump 2016 Vote Sanford F. Schram Hunter College, CUNY Presentation for the Behavior and Identities Workshop, Duke University, February 21, 2019.

2. This presentation is based on research for the book project, Hard White: The Mainstreaming of Racism in America by Richard C. Fording and Sanford F. Schram (currenty under review at Oxford University Press, editor Angela Chnapko).

3. “Racism” and Trump’s Victory
“Racial Resentment”
“White Nationalism”
”White Identity”
“Xenophobia”
”Islamophobia”
“Populism”
“Authoritarianism”

4. Goals Did racial attitudes matter?
If so, to what degree did they matter?
Compared to other factors in 2016
Compared to racial attitudes in previous elections
How did racial attitudes matter?
Backlash vs. polarization
mobilization

5. Data ANES 2016 Time Series Study (November 2016)
ANES 2016 Pilot Study (January 2016)
CCES 2016
VOTER Survey 2016

6. What Do We Mean by “Racial” Attitudes in the Study of U.S. Elections?
“Single Group” Approach
African Americans (Valentino and Sears 2005; Tesler and Sears 2010; Tesler 2016)
Latino immigrants (Abrajano and Hajnal 2015)
“Multi-Group” Approach
Ethnocentrism (Kinder and Kam)
o Stereotypes of Asians, Blacks, Hispanics

7. Our Approach to Measuring Ethnocentrism
In-group favoritism
White Identity scale
Outgroup Hostility:
African Americans (Racial Resentment Scale)
Latino immigrants (Opposition to Immigration Scale)
Muslims (Feeling thermometer score for Muslims)

8. Outgroup Hostility (Fording & Schram) and Ethnocentrism (Kinder & Kam)
are Distinct Concepts

9. Factor Analysis Results for Racial Hostility Scales
Outgroup
Hostility
Kinder and Kam’s Ethnocentrism
Affect Items
Factor Loadings (Pooled )
Racial Resentment
.83
-.06
Opposition to Immigrants Scale
.80
.04
Hostility Toward Muslims (FT)
.73
.06
Asians (FT Difference)
.89
Blacks (FT Difference)
.87
Hispanics (FT Difference)
.88
Sample Size ( )
8,035
Election Year
Conformatory Factor Analysis Results
Coefficient of Determination
2004 (N=687)
.64
2008 (N=1,165)
.61
2012 (N=3,144)
.67
.84
2016 (N=2,526)
.90
Note: The sample for this analysis includes white (non-Hispanic) voters and is taken from the American National Election Time Series Study. Columns 1 and 2 of panel 1 report factor loadings for the first two factors that returned an Eigen-value >1.0. The factor analysis was conducted using principal-components factors and oblique rotation to allow for correlated factors. Panel 2 presents results from conformatory factor analyses of each set of racial affect items, for each election year.

10. Outgroup Hostility is more strongly correlated with authoritarianism and white identity

11. Outgroup Hostility has become increasingly correlated with measures of partisan-directed emotion (anger, enthusiasm)

12. How Angry Does the Federal Government Make You?5
How Angry Does the Federal Government Make You?
(ANES Panel Study, N=732)
Anger Toward Federal Government 4
May 2009 3 2
January 2008 1 .1 .2 .3
Outgroup Hostility .7 .8 .9 1

13. Outgroup Hostility is more strongly related to vote choice than ethnocentrism and white identity (ANES 2016)

14. White Identity and Outgroup Hostility: 2016 ANES
White Identity Item
Correlation with Racial Resentment
Correlation with Outgroup Hostility
“How important is being white to your identity?”
.18
.27
“How likely is it that many whites are unable to find a job because employers are hiring minorities instead?”
..48
.54
“How important is it that whites work together to change laws that are unfair to whites?”
.29
“How much discrimination is there in the United States today against each of the following groups? (whites)”
.33
.35
White identity scale (based on above 4 items)
.42
.48
Sample Size (Whites only)
2,482
2,439

15. The Effect of White Identity on Support for Trump by Different Measures of White Identity-ANES 2016  
Independent
Variable
“How important is being white to your identity?”
“How much discrimination is there in the United States today against whites?”
White Identity
Scale (4-items)
Feeling thermometer (whites)
White Racial
Identity
-.817
.984 (p=.12)
-1.221
.758
Outgroup Hostility
6.002**
5.496**
6.390**
5.850**
Sexism Scale
1.668*
1.831**
2.000**
1.597*
Social Attitudes Scale
1.710**
1.723**
1.839**
1.608**
Party Identification
5.29**
5.252**
5.216**
5.351**
Ideological Identification
4.548**
4.901**
4.865**
4.608**
Economic Evaluation
(National)
2.730**
3.191**
3.121**
2.802**
(Pocketbook)
1.117
1.087
1.342*
1.085
Sample Size
1,476
1,461
1,443
1,482

16. All models are logit models (vote for Trump =1, 0=otherwise), utilizing 2016 ANES data. In addition to the variables listed in the table, the model also includes controls for gender, income, education, marital status, union household, church attendance and age. The sexism scale is the Ambivalent Sexism Scale. The Social Attitudes Scale is based on three items measuring support for abortion, gay marriage and transgender rights. All variables have been rescaled to range from 0-1.
Discussion: White identity is measured in each case such that higher values indicate greater levels of white identity. White identity is never significantly related to vote for Trump, regardless of the specific indicator used. The closest it comes to being statistically significant is for the discrimination-based item. Note that the sign of the coefficient is actually negative for the importance-based item and the identity scale (though statistically insignificant). The direction of the estimated effect for the feeling thermometer measure is positive, but the effect is not statistically significant. Alternatively, outgroup hostility exhibits a strong positive and significant effect on Trump support, regardless of how white identity is measured. Since all variables in the table are measured on a 0-1 scale, we see that the effect of OGH is always the strongest of all the variables.

17. Independent
Variables
Net Trump Warmth
Outgroup
Hostility
Party ID
Modern Social Total
Sexism Issues Effect
Outgroup Hostility
0.331**
---
0.186** .
.40**
(0.028)
(0.035)
White Racial Identity
0.004
0.224**
-0.012
0.156**
0.072**
.12**
(0.021)
(0.017)
(0.027)
(0.022)
Party Identification
0.377**
.38**
(0.018)
Modern Sexism
Scale
0.129**
0.0354
.14**
Social Issues Scale
0.116**
0.124**
.16**
Ideology
0.239**
0.357**
0.738**
0.304**
0.438**
.79**
(0.030)
(0.013)
Authoritarianism
0.069**
0.146**
.08**
(0.011)
(0.015)
Nat’l Economy
0.160**
0.148**
0.075**
0.154**
.30**
(0.014)
(0.019)
Personal Finances
0.056**
0.041*
0.023
0.037
0.003
.09**
(0.0170)
R-squared
.77
.60
.33
.58

18. on Net Support for Trump
Path Diagram of Direct and Indirect Effects of Outgroup Hostility and White Racial Identity
on Net Support for Trump
Party
Identification
.38**
Net
Trump
Support
.19**
.22** .
33**
White
Racial
Identity
Outgroup
Hostility

19. Regression Results for Effect of Outgroup Hostility on Republican Support, 2008-2016
Independent Variables
DV = Vote for Republican (Logit)
DV = Net Republican Warmth (OLS)
Outgroup Hostility
4.884***
4.483***
6.077***
0.291***
0.123***
0.352***
(1.028)
(0.820)
(0.970)
(0.0349)
(0.0276)
(0.0293)
Party Identification
4.400***
5.909***
5.484***
0.305***
0.322***
0.380***
(0.487)
(0.450)
(0.534)
(0.0228)
(0.0174)
(0.0215)
Ideological Identification
3.172***
2.476***
4.284***
0.133***
0.140***
0.222***
(0.798)
(0.626)
(0.946)
(0.0320)
(0.0260)
(0.0308)
Christian Fundamentalist
1.828**
2.995***
2.552***
0.117***
0.143***
0.106***
(0.604)
(0.494)
(0.0263)
(0.0177)
(0.0161)
Feminists (Warmth)
-0.398
-1.176
-2.754***
***
-0.135***
(0.722)
(0.611)
(0.676)
(0.0294)
(0.0209)
(0.0191)
Economic Evaluation
-0.828
3.625***
3.074***
-0.110***
0.134***
0.166***
(National)
(0.926)
(0.517)
(0.0282)
(0.0193)
-0.716
0.185
0.757
0.0252
0.0664***
(Personal)
(0.419)
(0.431)
(0.620)
(0.0162)
(0.0141)
(0.0172)

20. Church Attendance
(Baseline=Never)
Few times per year
0.0496
-0.240
(0.324)
(0.375)
(0.313)
(0.0159)
(0.0110)
(0.0107)
1-2 times per month
-0.402
0.0508 * *
(0.404)
(0.467)
(0.422)
(0.0196)
(0.0149)
(0.0131)
Almost every week
-0.370
0.931**
-0.282
0.0189 *
(0.383)
(0.340)
(0.354)
(0.0140)
(0.0121)
(0.0114)
Every week
3.057**
0.423
0.329
0.111
0.0149 *
(1.041)
(0.282)
(0.374)
(0.112)
( )
(0.0111)
Union Household
-0.343
0.396
0.0146
(0.320)
(0.295)
(0.297)
(0.0104)
(0.0100)
Education
(Baseline=H.S. or less)
College Degree
0.297
0.0187*
(0.323)
(0.273)
(0.288)
(0.0133)
( )
( )
Graduate Degree
0.619
0.292
-0.471
0.0258*
(0.412)
(0.388)
(0.0150)
( )
Family Income
0.0618*
0.0375* *
(0.0283)
(0.0151)
(0.0183)
( )
( )
( )
Married
0.475
0.357
0.258
0.0102
0.0161*
(0.276)
(0.214)
(0.268)
(0.0124)
( )
( )
Age ** *
( )
( )
( )
( )
( )
( )
Female
0.0745
-0.140 *
***
(0.250)
(0.228)
(0.242)
( )
( )
( )
Constant
-7.689***
-10.52***
-9.721***
0.0919*
0.0592*
(1.371)
(0.935)
(1.162)
(0.0433)
(0.0246)
(0.0285)
Observations
682
2,263
1,518
859
2,827
2,039

21. (6) Trump won despite a significant decrease in Outgroup Hostility between 2012 and 2016
.65
Outgroup Hostility .6
.55 .5
2004
2008
2012
2016
year

22. (6) Trump won despite a significant decrease in Outgroup Hostility between 2012 and 2016.7
Outgroup Hostility .6 .5 .4
2004
2008
2012
2016
year
Strong Democrats
Independents
Strong Republicans

23. Outgroup Hostility, 2004-2016 2.5 2 1.5 Density 1 .5 .2 .4 .6
2016 Mean
2012 Mean .5 .2
.4 .6
Outgroup Hostility .8 1
kernel = epanechnikov, bandwidth =
2012
2016

24. Why did Trump Win?
If 2016 was more about polarization than backlash, then how did Trump win? Wouldn’t the votes of racial liberals cancel out the votes of racial conservatives?
Two factors:
Mobilization
Electoral geography

25. Predicted Support for Republican Presidential Primary Candidates by Outgroup Hostility, 2016

26. Predicted Support for Democratic Presidential Primary Candidates by Outgroup Hostility, 2016

27. The Effect of Outgroup Hostility on Vote for Republican Presidential Candidate, 2004-2016

28. Economic Pessimism (National)
Outgroup Hostility vs. Economic Pessimism 2016 General Election 1 1 .8 .8
Pr(Vote for Trump)
Pr(Vote for Trump) .6 .6 .4 .4 .2 .2 .2
.4 .6
Outgroup Hostility .8 1 .2
.4 .6
Economic Pessimism (National) .8 1

29. Did Outgroup Hostility Help Trump Win?
If So, How?

30. Swing States in 2016 (Politico, June 2016)
Colorado
Florida
Iowa
Michigan
New Hampshire
North Carolina
Ohio
Pennsylvania
Nevada
Virginia
Wisconsin

31. (7) How did Trump win? Trump won because he was especially successful in mobilizing racial conservatives in key swing states.

32. Turnout in Noncompetitive States.9
Predicted Probability of Voting
Predicted Turnout by Outgroup Hostility .8
2016 .7
2012 .6 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
Outgroup Hostility

33. Turnout in Swing States 2012-2016
.85
2016
Predicted Turnout by Outgroup Hostility .8
Probability of Voting
.75
2012 .7
.65 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
Outgroup Hostility

34. Summary of Results for 2016 Vote Choice
Magnitude of effects (change in probability of vote for Trump):
Economic pessimism: .19
Outgroup Hostility: .39
Partisan identification: .41
Ideological identification: .28

35. Summary of Results for 2016 Vote Choice
Economic evaluations
Economic pessimism (nat’l economy) had a positive effect on vote for Trump
Ethnocentrism scale – no significant effect
White Racial Identity Scale – no significant effect
Outgroup Hostility Scale – Powerful effect on vote choice

36. Conclusion
Racial attitudes are more important than ever in understanding American politics.
However, the specific racial attitudes that matter have changed and become more inter-correlated, in part due to the candidacy of Donald Trump.
Ironically, Trump won in a year when the mean level of outgroup hostility declined.
This points to the importance of the relationship between outgroup hostility and mobilization as the key to Trump’s success.
The attitudinal backlash that occurred in 2016 was actually a backlash among racial liberals against Trump’s platform rooted in outgroup hostility.
This may be the source of the ”blue wave” that is predicted to lead to Democratic success in the midterm elections.

37. Polarization in American politics – the new ethnocentrism as an important source due to the candidacy and election of Donald Trump.
This was intentional. And it worked.
One unfortunate consequence: The “mainstreaming” of the extreme, racist right (not discussed here but is in our book)!
Trump has continued to stoke outgroup hostility since taking office.
One byproduct of this strategy is ”built-in” resistance to persuasion among Trump’s supporters, due to disproportionate representation of low cognition voters and the connection between outgroup hostility, anger and resistance to new information.
Trump’s election has led to a counter-mobilization among racial liberals that is likely to lead to major change in 2018.