Bryan Tony
Texas Christian University
Is all equal in love and politics?
Introduction
In 2010, about 15% of all new marriages in the United States were between spouses of a
different race or ethnicity from one another, more than double the share in 1980 of 6.7% (Wang
2012). The increasing popularity of intermarriage may point to a more tolerant and accepting
American society. However, in the wake of the shootings of Michael Brown, an unarmed black
teenager, in Ferguson, Missouri by a white cop and a similar episode featuring Trayvon Martin, a
Florida teen, racial tensions continue to loom large in the United States. On the other hand,
racism could be deemed an issue that has always been swept under the rug since the Civil Rights
movement and is now resurfacing. This is why it is important to investigate not only racism as it
exists today, but also the secondary effects of racism found in society, economics, and politics.
While the number of interracial marriages is increasing, this is an area where its political
effects have yet to be considered, which is what this research will be assessing. We already know
candidate spouses have a significant impact on public opinion based upon how active they are,
but we do not yet know the impact based on the color of their skin (Burrell 2011). To examine
this, I ask: how does the likelihood to vote for a candidate vary based on the race of his spouse? I
argue that if the spouse of the candidate is racially different than the candidate, voters will be less
likely to vote for him. This argument points to the implicit racism found in the United States.
Secondly, among interracial marriages, there will be more support for minorities with white
spouses than whites with minority spouses. This case hinges on the development of black culture
and stereotyping of black candidates because presumably a white candidate who marries a black
spouse adopts some of the stereotypes associated with black culture. Finally, I argue that males
will be more likely to vote for a candidate with a spouse of the same race than a candidate with a
spouse of a different race. Among females, the race of the spouse will not be significant in their
likelihood to vote for the candidate. To study this, I will look at the research on males and the
authoritarian personality.
For the purpose of this investigation, minorities will be defined as African Americans.
Although it may be true that people view other minority races more or less favorably in the
United States than African Americans, by looking at the relationship of white and black
interracial marriages, my analysis will be more focused and culturally relevant when we think of
racism today.
In what follows, I discuss the current literature on numerous factors that could affect how
voters analyze interracially married candidates. I then use these factors to form the three
mentioned earlier. Next, I test my hypotheses by distributing a survey experiment with randomly
assigned conditions. The results then indicate how candidates married to minority spouses would
or would not be supported by voting and the confidence held in the candidate by voters. Finally,
the concluding discussion dissects the results by the races of the candidate and spouse and the
gender of the survey respondents before closing with meaningful implications, limitations, and
areas for future research.
Implicit Racism, Cognitive Dissonance, and Interracial Distrust
Without a doubt, the United States has come a long way from 50 years ago and the
beginning of the Civil Rights movement. Over the past 40 years alone, public opinion polls have
revealed substantial declines in whites’ endorsement of prejudiced views towards minority
groups, and blacks in particular, in the United States (Pearson 2009). Regrettably, overt racism
aside, three factors justify the idea that racism still exists and impacts the way people behave
politically: implicit racism, cognitive dissonance, and interracial distrust.
Implicit racial attitudes are those existing outside of our own conscious awareness. This
can be evidenced by disparities and discrimination in the areas of healthcare, employment,
housing, and education. For example, job applicants with European-sounding first names are
preferred (by 50 percent) over applicants with identical resumes but African American-sounding
names (Bertrand 2004). Further research has begun to examine the relationship between implicit
attitudes and their effect on behavior, surmising that implicit attitudes predict race-related
behaviors. Dovidio (2002) found that whites’ implicit attitudes predicted their non-verbal
behavior toward blacks in a classroom setting. Moreover, Towles-Schwen and Fazio (2006)
found that the implicit attitudes of white college freshmen with randomly assigned black
roommates predicted the stability and duration of the roommate relationships. Studies like these
may suggest that implicit racism would negatively affect voting behavior for interracially
married candidates because they show that racism, implicit or explicit, has real effects.
In 1957, Leon Festinger put forth the theory of cognitive dissonance. It is defined as the
mental stress or discomfort experienced by an individual who holds two or more contradictory
beliefs, ideas, or values at the same time, or is confronted by new information that conflicts with
existing beliefs, ideas, or values. As a result, individuals tend to become uncomfortable and
attempt to reduce this dissonance, even by actively avoiding situations and information that
would otherwise increase it. This is relevant to our study because it also leads to a fear or anxiety
of breaking social norms. For a long time, interracial marriages were seen as breaking the social
norm, and given that still only 15 percent of marriages today are interracial, it remains outside of
social norms. The idea of a politician in an interracial marriage represents an enormously public
and visible display of a changing social norm. Thus, this cognitive dissonance causes fear and
anxiety for the voter who, therefore, will choose to note vote for a candidate engaged in the
interracial marriage in order to mitigate the demonstration of the evolving norm, interracial
couples.
Finally, the fear of interracial couples may further be exacerbated by Rudolph’s study in
2010 that shows how interracial trust falls among whites as minorities grow in economic
privilege and power. The resulting increase in perception of black power then leads to interracial
distrust. If a candidate married to a minority was to successfully win an election, it could signal a
positive shift in minority power, and voters would view the candidate as less trustworthy.
Implicit racism, cognitive dissonance, and the interracial trust issue experienced by voters could
lead to them not voting for a candidate married interracially.
For these three reasons, I first hypothesize that if the spouse of a candidate is racially
different than the candidate, then voters will be less likely to vote for him.
Stereotypes of Black Culture and Candidates
African-Americans remain underrepresented at all levels of the United States
government. In the 113th Congress, there are 44 African-Americans (8.1% of total membership)
and only sixteen black women, while African Americans make up 13.2% of the United States
population (Manning 2013). There are many factors contributing to this underrepresentation, but
one factor is skin color (Williams 1989). Even when whites report a willingness to vote for a
qualified black candidate, they are far more likely to believe that a white candidate would be
more effective and more qualified than a black candidate (Williams 1989). As such, if a white
candidate was married to a black spouse, then his or her credibility could be further brought into
question and voters may be less likely to vote for the candidate because of the candidate’s
proximity to black culture. In other words, in the eyes of the voters, by marrying into the black
culture, the candidate has adopted some of its traits that make the candidate appear less qualified.
Furthermore, African Americans are fighting the stereotypes of black culture when they
run for public office or are associated with someone running for public office through marriage.
Peffley and Hurwitz (1997) found that black work ethic and black hostility is viewed more
negatively than white work ethic and white hostility. Eventually, if a black politician achieves
success, Schnieder and Bos (2011) argue that they then are viewed more positively, but point out
the path to public office for blacks is much more difficult because they have to overcome other
common stereotypes like laziness. The aforementioned study on interracial trust also shows how
the stereotypes of black culture lead to the stereotyping of black candidates because they are seen
as less competent and electable when compared to their white peers (Williams 1989). Reeves
(1987) found that racially conservative, less educated, male, and older white voters are less likely
to vote for black candidates. These perceptions heavily influence voters, affecting reality. In
doing so, people may prefer a minority candidate to be married to a white spouse than another
minority spouse.
To sum, my second hypothesis is, among interracially married couples, there will be
more support for minorities with white spouses than whites with minority spouses.
Male Authoritarian Personalities
In general, women are more likely to express left-leaning political preferences than men
(Stenner 2005). Meanwhile, more men have been identified as having authoritarian personalities,
sharing the characteristics of being more emotionally stable, introverted, disagreeable, and less
open-minded and conscientious (Adorno 1950). These personality traits further lead to men
being generally more conservative. Moreover, another study found that political ideology was
the most important factor influencing males’, but not females’, racial attitudes (Smith 2013).
This makes a strong link between the two studies as males’ personalities affect their ideology,
which then affect their racial attitudes. Moreover, men are more likely than women to display
racial resentment. As a result, men are expected to generally view blacks negatively.
Accordingly, men are more likely to be against interracial marriage because it goes against the
conservative grain and represents a more accepting and open-minded view of marriage in
society.
Consequently, my final hypothesis is that males will be more likely to vote for a
candidate with a spouse of the same race than a candidate with a spouse of a different race.
Among females, the race of the candidate’s spouse is not significant in their likelihood to vote
for the candidate.
Methodology
To test my hypotheses, I designed a survey experiment. I chose to test my claims using a
survey experiment because this method allows for the collection of a wide range of responses,
can be distributed easily, and is not time-intensive for the respondent. First, a survey experiment
allows for a wide range of responses, including respondents’ basic demographic information, as
well as critical post-test questions that operationalize the dependent variables. (Each of these is
explored further in the “Experiment” section of this paper). Second, the survey experiment
allows for easy distribution of the instrument, especially given the online platform from
Qualtrics, which can be disbursed through a variety of media. I used Facebook, Twitter,
LinkedIn, and emails to reach as much of my network as possible to garner as many responses as
I could. With this, I expected to reach an estimated 500 people. Third, the survey experiment
made the most sense because the design of the experiment did not require subjects to come into a
lab, but gave me the ability to “take the lab to them” in a way that the experiment could still be
run from the comfort of their own space. The survey is short enough that it can be completed in
less than 5 minutes and contributes to the expected number of responses. With these advantages,
the survey experiment method was decided to be the best method to test my hypotheses and
manipulate the respondent into giving honest answers regarding the subject of race and politics.
In the end, 240 people completed the survey.
Experiment
The experimental component of the research comes in the survey’s design. To reiterate,
the research question I am studying is: How does the likelihood to vote for a candidate vary
based on the race of the candidate’s spouse? To study this, the survey experiment gauges the
respondents’ reactions to a press release of a fictitious male candidate declaring his intentions to
run in the 2014 Congressional elections. Before the subject reads the press release, the subject
answers a series of pre-questions to gather his or her basic information: age, race, gender, level
of education, etc. (see Appendix A for specific questions).
In addition to the text of the press release, each respondent is randomly assigned
one of the five conditions, pictures of the candidate and his wife: a white male candidate
with a white spouse, a black male candidate with a black spouse, a black male candidate
with a white spouse, a white male candidate with a black spouse, or no picture at all. To
represent these conditions, photographs are included of the candidate and his wife (see
Appendix B for text of the press release and the pictures used). To be clear, Condition 1
will show a white candidate with a white spouse. Condition 2 will show a black candidate
with a black spouse. Condition 3 will show a black candidate with a white spouse.
Condition 4 will show a white candidate with a black spouse. Lastly, to have something
to compare our findings to, the control group (Condition 0) received the press release
without an accompanying picture of Michael Davis and his wife. Therefore, without any
depiction of Michael’s or his wife’s race, the results from this group should be based
solely on the candidate’s described qualifications in the press release. The text of the
press release remains unchanged for each of the conditions, so that the only factors being
manipulated are the candidate and his spouse’s race, while all else is controlled. Thereby,
the survey experiment remains internally valid as the condition groups are randomly
assigned and all else is held equal, but the external validity of the experiment may still be
limited by the small sample size and respondent demographics. However, according to a
study by McDermott (2002), the internal validity is more important to the experiment
since the results will be less biased, whereas external validity deals solely with whether
or not the results can be extrapolated outside of the experiment. This is an enormous
benefit to the study because it narrows its focus tightly around the subject’s response to
the press release with the photograph and, more generally, the issue of race and politics
The two by two factorial, between-subjects design of the experiment is apparent
now because two independent variables are being manipulated simultaneously: the
candidate’s race and the spouse’s race. Furthermore, it is a between-subjects design
because each subject receives only one treatment condition, whichever picture they are
randomly assigned with the press release. The hope here is that the experiment will reveal
two main effects (one for each variable) and a clear interaction of the two variables.
These will be derived from the subjects’ responses to the post-experiment questions (see
Appendix A). The first set of three post-experiment questions asks how likely the
respondent is to vote for Michael Davis, to donate to his campaign, and to volunteer for
his campaign. The point of this first set of questions is to examine the effect on political
support that an interracial couple may have. The second set of three post-experiment
questions asks how trustworthy, qualified, and competent Michael Davis seems to the
respondent. This set examines how confidence in the candidate is affected by the race of
his spouse. After these questions are answered, the subject is finished with the survey
experiment.
Analytical Process
Political support and confidence in the candidate are the two dependent variables.
Each of these dependent variables is operationalized by measuring subjects’ responses to
a battery of questions regarding respondents’ likelihood to engage in Michael Davis’s
campaign and respondents’ perceptions of Michael Davis as a candidate for political
office. Respondents reported how strongly they agreed or disagreed with the statements
on a five-point Likert scale. The Likert scale is a useful tool in this case because it offers
the respondent a certain degree of flexibility to weigh their answers and allows for the
quantifiable analysis I explore in the “Results” section of my research. I use factor
analysis to determine if all of the support and confidence questions are measuring each of
those concepts, respectively. I then generate an average “support” variable and an
average “confidence” variable based on responses to the question batteries.
My first hypothesis predicts that, overall, when Michael Davis is shown with a
spouse of a different race, respondents will be less likely to engage in his campaign and
perceive him favorably. In other words, I am testing the main effect of Michael Davis
being in a biracial versus same-race marriage, regardless of Michael Davis’s own race.
The second hypotheses posits that, between the two biracial couples (whether Michael
Davis is black or white, he has a spouse of the opposite race), a black Michael Davis with
a white spouse will be viewed more favorably than a white Michael Davis with a black
spouse. Here, I am testing the interaction of race of the candidate and race of spouse only
among the two biracial couples. Finally, I hypothesize third that the racial element of the
candidate and his spouse will be significantly less important in predicting engagement
and perceptions among female respondents than male respondents. Specifically, I am
testing the average conditional treatment effect between male and female respondents for
the full interaction of the two factors. I conduct univariate ANOVA tests for each of these
hypotheses because they reveal to me which factors are statistically significant in order to
arrive at the root causes of the effects.
Results
For the following analysis, all graphs and tables can be found in Appendix C. My
first hypothesis is that if the spouse of a candidate is racially different than the candidate,
then the voters will be less likely to vote for him proved to be partially true, but cannot be
accepted as an overarching truth. Therefore, I have to tentatively reject my null
hypothesis because I cannot accept nor fully reject it. I find evidence of this from the
univariate analysis of variance of the dependent variable vote.
[input Table 1.1]
The race of the candidate is statistically significant at a level of 0.053. Therefore, I can
analyze the graph of the estimated marginal means of the likelihood that the respondent
would vote for the candidate based on his race and the race of his spouse.
First, from the data, it is statistically and substantively significant that people are
more likely to vote for a black candidate. This is clearly seen in the subsequent graph.
[input Graph 1.1]
This goes somewhat against the idea of racism that I presented earlier in my research.
However, the effect of explicit racism in the form of hatred of blacks may have lessened
over time, so now black politicians are becoming more common, but the fact could still
remain that the interracially candidate is at an even greater loss to garner votes, which is
what my first hypothesis posits. In the following graph, “.00” indicates a Caucasian
candidate or spouse and “1.00” indicates an African American candidate or spouse.
[input Graph 1.2]
It reveals that people will be less likely to vote for a white candidate with a black spouse,
but not for a black candidate with a white spouse. In other words, black candidates can
expect to receive more votes when married to a white spouse. Comparatively, a black
candidate with a white spouse actually experiences a greater likelihood to receive votes
than a black candidate married to a black spouse. This is in direct contrast to a white
candidate who is expected to receive roughly the same number of votes regardless of his
spouse’s race. All of this supports my first hypothesis that when married interracially,
candidates are less likely to receive votes, but as the graph indicates, this is only true for
black candidates.
Fortunately, this falls right into proving my second hypothesis: respondents will
be less likely to vote for a white candidate with a black spouse than a white candidate
with a white spouse. Furthermore, a respondent will be more likely to vote for a black
candidate with a white spouse than a black candidate married to a black spouse. Graph
1.2 illustrates that the white candidate with a black spouse is the least likely condition to
receive votes. Moreover, the white candidate with a white spouse scenario has an
estimated marginal means advantage of over 0.2. Another revealing factor that plays a
role in this equation is that when the race of the spouse is black, overall, the respondents
were less likely to vote for them.
[input Graph 1.3]
The graph indicates another substantively significant trend, but in this case the margin of
difference is too small between the white spouse (.00) and the black spouse (1.00) to be
statistically significant. Yet, this still justifies the second half of my second hypothesis
that a black candidate married to a white spouse is more likely to receive votes than a
black candidate married to a white spouse because all black spouses lessen the likelihood
of a candidate receiving as many votes. Therefore, I can accept my second hypothesis as
true.
Lastly, for my third hypothesis that males will be more likely to vote for a
candidate with a spouse of the same race than a candidate with a spouse of different race
and, that among females, the race of spouse is not significant in their likelihood to vote
for the candidate, there is not much of an effect on voting for interracially married
candidates based off of the respondent’s gender. With the fixed factor of gender, the
univariate analysis of variance for gender is not statistically significant, as evidenced by
Table 1.2.
[input Table 1.2]
In the following graph of the estimated marginal means of men voting for the candidate,
once again “.00” indicates a Caucasian candidate and “1.00” indicates an African
American candidate.
[input Graph 1.4]
Opposing my hypothesis, the graph indicates males are more likely to vote for black
spouses than white spouses and show a willingness to vote more interracial couples, even
though the highest vote-getting scenario for male voters is the black couple. The graph
for females is below.
[input Graph 1.5]
This graph shows that females are substantively less likely to vote for interracial couples
than males but it is not statistically significant either from the analysis of Table 1.2
above. This may be explained by the fact that, according to the data, men are more likely
to vote for black spouses than women are, as shown in Graph 1.6.
[input Graph 1.6]
All in all, I cannot accept my third hypothesis because there is greater contrasting
evidence against it.
Discussion
I began this study looking to answer the question: how does the likelihood to vote
for a candidate vary based on the race of the candidate’s spouse? From the literature
review, experimental design, and the results, I can definitively say yes, the likelihood to
vote for a candidate can be based on the race of the candidate’s spouse because I found
measurable effects of being married to the same or opposite race as the candidate. Table
1.3, featuring the combined variables of support and confidence, display a wide array of
results that stem from the race of the couple.
[input Table 1.3 here]
To sum up my hypotheses, I successfully found that people are less likely to vote
for white candidates with black spouses, but was surprised to find that black candidates
married to white spouses are unaffected or, if anything, experience an increase in their
likelihood to be elected. This deemed my first hypothesis that interracially married
candidates are less likely to receive votes only true for Caucasian candidates. My second
hypothesis was substantively proven and showed how candidates, white and black, with
black spouses face a harder path to office because voters are less likely to vote for them.
Although my third hypothesis did not turn out to be true according to the data, it is still
interesting to see how the genders of the respondents did not greatly affect their
willingness to vote for an interracial couple.
Thus, some implications can be drawn from this. The first implication that comes
to the forefront is that politicians should be conscious of who they marry. In marriage,
through race, culture, and broadly speaking always being around your partner, people
adopt some of their partner’s characteristics, positive and negative. The public’s
perception of a candidate’s spouse affects the perception of the candidate, especially
given that they are high-profile citizens. Secondly, this research can add value to
campaign management. For example, if I am managing the campaign of a black
candidate and his white spouse, I may be more inclined to organize publicity events
where my candidate is doing something that is associated less with black culture, like a
golf tournament, so that racial lines become blurred and people see him for the person he
is, regardless of skin color. Third, and finally, this research strengthens the belief that
there are still adverse and real effects of racism. It does not take much to see that the
United States’s societal climate is still reeling from the deaths of Michael Brown and
Trayvon Martin. In the political landscape, blacks remain underrepresented and face an
upward battle to run for political office.
On the other hand, there were limitations to my research. The population size of
my survey experiment was a small and convenient sample. The respondents were few in
number and not as many as I was hoping for. In addition, the sample was convenient
because it was composed mostly of people who I had some sort of a connection to, such
as friends, family, classmate, et cetera. As a result, the demographics of the respondents
were not conducive to making my experiment externally valid, as the sample size is not
representative of the country as a whole. This is most exemplified in my survey’s
descriptive statistics. As a couple examples, 90% of those surveyed were in the 18-25
years old age group and 84.2% were Caucasian (see Appendix D for a full list of
descriptive statistics). Lastly, the photographs selected to show participants were not
consistent in the age, setting, and attractiveness of the subjects. I cannot say how much of
an impact the photographs used made, but more careful selection would be beneficial to
the experiment’s design.
For future research, there are a number of issues I would like to have examined or
examine further. First, it would have been useful to have something more than the control
group to compare my findings to. Since there has not been a plethora of research on the
subject of political candidates’ spouses, I had to justify my argument using research about
racism, stereotypes, and male personalities. If I had found previous research on the views
of candidates’ spouses based on their race, then I could have compared my findings to ten
or twenty years ago and see if things had changed for the better or worse since. Second,
as the United States becomes a more culturally and ethnically diverse nation every year,
it is worthy to explore how other minority spouses may affect a white candidate’s
likelihood to garner votes. Would it be more acceptable to marry an Asian woman than
an African American woman? My research opens the door for more research on other
identities, which brings me to my third area due future research: a candidate’s sexuality.
LGBT candidates could be seen in a more negative or positive light than interracially
married couples, but at this point, I cannot say without doing more research into the
matter, but it, too, could carry far-implications.
In conclusion, race and racism will continue to remain hot-button issues in an
increasingly polarized nation, but there is hope to be found in my findings that people are
overall just as likely to vote for black candidates and it is not without some doubt that
interracially married candidates are less likely to win elections. There are a wide range of
factors when running for office that are greater than race, but this research matters
because it takes a in-depth look at the issue of race in American politics today. In the
words of the late American poet Maya Angelou, “prejudice is a burden that confuses the
past, threatens the future, and renders the present inaccessible.” For this eloquent reason
alone, it is vital that we learn from our past, to know the present, and make positive
change for the future. Ultimately, the present issue of and research on race and politics is
important because it leads to the necessary self-awareness to aspire to the American
ideals of freedom we all hold dear.
References
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Prejudice and Interracial Interaction.” Journal of Personality and Social
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http://www.senate.gov/CRSReports/crspublish.cfm?pid=%260BL%2BR%5CC%3F%0A
(October 20, 2014.)
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Peffley, M., & Hurwitz, J. 1997. “Racial stereotypes and whites' political views of blacks
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Reeves, Keith. 1997. Voting Hopes or Fears? White Voters, Black Candidates, and
Racial Politics in America. New York: Oxford University Press.
Rudolph, T. J., and E. Popp. 2010. “Race, Environment, and Interracial Trust.” Journal
Of Politics 72(1), 74-89.
Schneider, M. C., & Bos, A. L. 2011. “An Exploration of the Content of Stereotypes of
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Appendix A
Pre-Questions:
What age group do you fall under?
a. 18-25
b. 26-35
c. 36-49
d. 50+
What is your racial or ethnic background?
a. African American
b. Asian
c. Hispanic/Latino
d. White/Caucasian e. Other
Are you a male or female?
a. Male
b. Female
What level of education have you received?
a. High school diploma b. Some college c. Undergraduate degree d. Graduate degree
How would you classify your party identification?
a. Strong Democrat b. Moderate Democrat c. Independent d. Moderate Republican
e. Strong Republican
When it comes to politics, do you think of yourself as:
a. Very liberal
conservative
b. Slightly liberal
c. Moderate
d. Conservative
e. Very
Post-Questions:
I would vote for Michael Davis
for the U.S. House of
Representatives.
I would donate to Michael
Davis’s campaign.
I would volunteer for Michael
Davis’s campaign.
Michael Davis seems like a
very trustworthy candidate for
political office.
Michael Davis does not appear
to be qualified to seek political
office.
I think Michael Davis would
be a competent elected official.
Strongly
Agree
Agree
Undecided Disagree
Strongly
Disagree
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
Appendix B
February 24, 2014
By: James Downey
PRESS RELEASE
Michael Davis announced his candidacy yesterday for the U.S. House of Representatives
for the 96th District. Davis is an attorney at the top law firm who has successfully argued
several cases before the State Supreme Court.
While practicing law, Davis served on City Council for ten years, followed by two terms
in the state House of Representatives where he chaired the Appropriations Committee
and sat on the Energy and Commerce Committee. Davis earned his law degree in 1991
and his Bachelor’s degree in economics in 1984, both suma cum laude.
Appendix C
Table 1.1: Vote – Univariate Analysis of Variance
Tests of Between-Subjects Effects
Dependent Variable: Vote
Type III Sum of
Source
Squares
df
Mean Square
F
Sig.
1.637a
3
.546
1.583
.195
2045.438
1
2045.438
5933.844
.000
.134
1
.134
.388
.534
1.306
1
1.306
3.788
.053
.224
1
.224
.650
.421
Error
63.771
185
.345
Total
2119.000
189
65.407
188
Corrected Model
Intercept
racespouse
racecandidate
racespouse * racecandidate
Corrected Total
a. R Squared = .025 (Adjusted R Squared = .009)
Table 1.2: Gender – Univariate Analysis of Variance
Tests of Between-Subjects Effects
Dependent Variable: Vote
Type III Sum of
Source
Squares
df
Mean Square
F
Sig.
2.599a
7
.371
1.070
.385
1872.132
1
1872.132
5395.058
.000
.030
1
.030
.087
.768
1.396
1
1.396
4.024
.046
Gender
.088
1
.088
.253
.615
racespouse * racecandidate
.261
1
.261
.754
.386
racespouse * Gender
.660
1
.660
1.902
.170
racecandidate * Gender
.099
1
.099
.285
.594
.029
1
.029
.085
.771
Error
62.809
181
.347
Total
2119.000
189
65.407
188
Corrected Model
Intercept
racespouse
racecandidate
racespouse * racecandidate
* Gender
Corrected Total
Table 1.3: Difference in Means for each Factors
Report
Condition
0
Mean
3.2727
44
44
Std. Deviation
.77922
.53446
Mean
2.8497
3.0458
51
51
Std. Deviation
.58238
.46197
Mean
3.0884
3.1769
49
49
Std. Deviation
.66240
.44671
Mean
3.0233
3.2326
43
43
Std. Deviation
.63992
.33755
Mean
2.8222
3.0355
45
47
Std. Deviation
.41194
.40667
Mean
2.9540
3.1481
232
234
.62864
.44954
N
2
N
3
N
4
N
Total
Confidence
2.9924
N
1
Support
N
Std. Deviation
Graph 1.1
Graph 1.2
Graph 1.3
Graph 1.4
Graph 1.5
Graph 1.6
Appendix D
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
Age
240
1
4
1.21
.715
Race
240
1
5
3.79
.641
Gender
240
1
2
1.60
.490
EducationLevel
238
1
4
2.15
.604
PartyID
240
1
5
3.47
1.042
Idealogy
240
1
5
3.31
.975
Condition
241
0
4
1.99
1.404
Vote
233
1
5
3.32
.604
Donate
233
1
5
2.78
.837
Volunteer
234
1
5
2.76
.879
Trust
234
1
5
3.60
.682
Qualified
234
1
5
2.14
.855
Competent
234
1
5
3.71
.683
Valid N (listwise)
230
Age
Cumulative
Frequency
Valid
Valid Percent
Percent
1
217
90.0
90.4
90.4
2
8
3.3
3.3
93.8
3
2
.8
.8
94.6
4
13
5.4
5.4
100.0
240
99.6
100.0
1
.4
241
100.0
Total
Missing
Percent
System
Total
Race
Cumulative
Frequency
Valid
Valid Percent
Percent
1
6
2.5
2.5
2.5
2
8
3.3
3.3
5.8
3
20
8.3
8.3
14.2
4
203
84.2
84.6
98.8
5
3
1.2
1.3
100.0
240
99.6
100.0
1
.4
241
100.0
Total
Missing
Percent
System
Total
Gender
Cumulative
Frequency
Valid
Missing
Total
Percent
Valid Percent
Percent
1
95
39.4
39.6
39.6
2
145
60.2
60.4
100.0
Total
240
99.6
100.0
1
.4
241
100.0
System
EducationLevel
Cumulative
Frequency
Valid
Valid Percent
Percent
1
20
8.3
8.4
8.4
2
170
70.5
71.4
79.8
3
40
16.6
16.8
96.6
4
8
3.3
3.4
100.0
238
98.8
100.0
3
1.2
241
100.0
Total
Missing
Percent
System
Total
PartyID
Cumulative
Frequency
Valid
Valid Percent
Percent
1
10
4.1
4.2
4.2
2
38
15.8
15.8
20.0
3
54
22.4
22.5
42.5
4
106
44.0
44.2
86.7
5
32
13.3
13.3
100.0
240
99.6
100.0
1
.4
241
100.0
Total
Missing
Percent
System
Total
Idealogy
Cumulative
Frequency
Valid
Total
Valid Percent
Percent
1
11
4.6
4.6
4.6
2
34
14.1
14.2
18.8
3
86
35.7
35.8
54.6
4
88
36.5
36.7
91.3
5
21
8.7
8.8
100.0
240
99.6
100.0
1
.4
241
100.0
Total
Missing
Percent
System
Condition
Cumulative
Frequency
Valid
Percent
Valid Percent
Percent
0
46
19.1
19.1
19.1
1
52
21.6
21.6
40.7
2
50
20.7
20.7
61.4
3
45
18.7
18.7
80.1
4
48
19.9
19.9
100.0
241
100.0
100.0
Total
Vote
Cumulative
Frequency
Valid
Valid Percent
Percent
1
2
.8
.9
.9
2
2
.8
.9
1.7
3
158
65.6
67.8
69.5
4
62
25.7
26.6
96.1
5
9
3.7
3.9
100.0
233
96.7
100.0
8
3.3
241
100.0
Total
Missing
Percent
System
Total
Donate
Cumulative
Frequency
Valid
Total
Valid Percent
Percent
1
17
7.1
7.3
7.3
2
57
23.7
24.5
31.8
3
125
51.9
53.6
85.4
4
29
12.0
12.4
97.9
5
5
2.1
2.1
100.0
233
96.7
100.0
8
3.3
241
100.0
Total
Missing
Percent
System
Volunteer
Cumulative
Frequency
Valid
Valid Percent
Percent
1
22
9.1
9.4
9.4
2
52
21.6
22.2
31.6
3
125
51.9
53.4
85.0
4
29
12.0
12.4
97.4
5
6
2.5
2.6
100.0
234
97.1
100.0
7
2.9
241
100.0
Total
Missing
Percent
System
Total
Trust
Cumulative
Frequency
Valid
Valid Percent
Percent
1
2
.8
.9
.9
2
1
.4
.4
1.3
3
105
43.6
44.9
46.2
4
107
44.4
45.7
91.9
5
19
7.9
8.1
100.0
234
97.1
100.0
7
2.9
241
100.0
Total
Missing
Percent
System
Total
Qualified
Cumulative
Frequency
Valid
Total
Valid Percent
Percent
1
50
20.7
21.4
21.4
2
119
49.4
50.9
72.2
3
50
20.7
21.4
93.6
4
12
5.0
5.1
98.7
5
3
1.2
1.3
100.0
234
97.1
100.0
7
2.9
241
100.0
Total
Missing
Percent
System
Competent
Cumulative
Frequency
Valid
Total
Valid Percent
Percent
1
3
1.2
1.3
1.3
2
2
.8
.9
2.1
3
75
31.1
32.1
34.2
4
135
56.0
57.7
91.9
5
19
7.9
8.1
100.0
234
97.1
100.0
7
2.9
241
100.0
Total
Missing
Percent
System