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Gender Stereotypes and Attitudes toward Women Candidates
Unformatted Document Text:  In examining whether political gender stereotypes are related to attitudes about women candidates and women in office, I employ four dependent variables (See Appendix for all survey questions employed). The first measures whether respondents have a baseline gender preference when choosing among two equally qualified candidates, one a man and the other a woman. This variable is coded 0 for those who prefer a man and 1 for those who prefer a woman. The second and third ask respondents whether they would vote for a qualified Republican woman and a qualified Democratic woman for president (coded 0 for no, 1 for yes). The final dependent variable asks respondents for their opinion on the percentage of male and female officeholders in the “best government the U.S. could have.” This variable is coded so that people who wanted parity (50 percent women and 50 percent men) or majority-female government are coded 1 and those wanting majority male (51-100 percent) are coded 0. The primary independent variables of interest measure respondents’ stereotyped views of women and men in politics. There are four variables that measure issue competence and four that measure personal trait stereotypes. For the issue competence measures, respondents were asked whether they thought women or men in elected office were better at handling education, terrorism, health care, and the economy, or whether they saw no difference. For the trait measures, people were asked whether women or men candidates and officeholders tended to be more assertive, compassionate, consensus-building, and ambitious, or whether there was no difference between them. There are two issue and two trait stereotypes that are generally assumed to be “female” strengths (education, health care, compassionate, consensus-building) and two that are assumed to be “male” strengths (terrorism, economy, assertive, ambitious). Each stereotype variable is coded 1 if the respondent thinks men are better at the issue or more likely to have the trait, 2 if they see no difference between women and men, and 3 if they think women are better/more likely to possess the characteristic. The other independent variables include the usual control variables – respondent education, sex, party identification, race, age, and political knowledge. The final variable in the model accounts for whether the respondent lives in a state with a woman governor or woman member of the U.S. Senate or not. Based on previous research on descriptive representation and the impact of women officeholders, we might expect that people who have experienced women leaders could have different attitudes about women in office. This variable is coded 0 if a respondent lives in a state with only male governors and Senators and one if there was at least one woman leader in the state (governor or U.S. Senate). 1 Analysis The first step in the analysis is to examine the distribution of attitudes toward women candidates and in office in general and confirm the presence of gender stereotyped thinking with regard to women and men in politics. Table 1 presents the frequency distributions for the four dependent variables. There are few surprises here. A 1 An alternative measure, employing a continuous variable that accounts for the number of women leaders in a state, ranging from 0 to 3, made no difference in the analysis. 5

Authors: Dolan, Kathleen.
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In examining whether political gender stereotypes are related to attitudes about
women candidates and women in office, I employ four dependent variables (See
Appendix for all survey questions employed). The first measures whether respondents
have a baseline gender preference when choosing among two equally qualified
candidates, one a man and the other a woman. This variable is coded 0 for those who
prefer a man and 1 for those who prefer a woman. The second and third ask respondents
whether they would vote for a qualified Republican woman and a qualified Democratic
woman for president (coded 0 for no, 1 for yes). The final dependent variable asks
respondents for their opinion on the percentage of male and female officeholders in the
“best government the U.S. could have.” This variable is coded so that people who
wanted parity (50 percent women and 50 percent men) or majority-female government
are coded 1 and those wanting majority male (51-100 percent) are coded 0.
The primary independent variables of interest measure respondents’ stereotyped
views of women and men in politics. There are four variables that measure issue
competence and four that measure personal trait stereotypes. For the issue competence
measures, respondents were asked whether they thought women or men in elected office
were better at handling education, terrorism, health care, and the economy, or whether
they saw no difference. For the trait measures, people were asked whether women or
men candidates and officeholders tended to be more assertive, compassionate, consensus-
building, and ambitious, or whether there was no difference between them. There are
two issue and two trait stereotypes that are generally assumed to be “female” strengths
(education, health care, compassionate, consensus-building) and two that are assumed to
be “male” strengths (terrorism, economy, assertive, ambitious). Each stereotype variable
is coded 1 if the respondent thinks men are better at the issue or more likely to have the
trait, 2 if they see no difference between women and men, and 3 if they think women are
better/more likely to possess the characteristic.
The other independent variables include the usual control variables – respondent
education, sex, party identification, race, age, and political knowledge. The final variable
in the model accounts for whether the respondent lives in a state with a woman governor
or woman member of the U.S. Senate or not. Based on previous research on descriptive
representation and the impact of women officeholders, we might expect that people who
have experienced women leaders could have different attitudes about women in office.
This variable is coded 0 if a respondent lives in a state with only male governors and
Senators and one if there was at least one woman leader in the state (governor or U.S.
Senate).
Analysis
The first step in the analysis is to examine the distribution of attitudes toward
women candidates and in office in general and confirm the presence of gender
stereotyped thinking with regard to women and men in politics. Table 1 presents the
frequency distributions for the four dependent variables. There are few surprises here. A
1
An alternative measure, employing a continuous variable that accounts for the number of women leaders
in a state, ranging from 0 to 3, made no difference in the analysis.
5


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