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A Non-Gendered Lens? Media, Voters, and Female Candidates in Contemporary Congressional Elections

Published online by Cambridge University Press:  06 March 2015

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Abstract

Much research in the study of U.S. politics has argued that female candidates for elected office are treated differently—and often worse—than male candidates in the press and by the public. Although these patterns do not doom women to electoral failure, they raise a formidable series of obstacles that often complicate women’s path to elective office, slowing the move toward gender parity in representation. Broad changes to the American political landscape, as well as methodological limitations of previous work, however, suggest the need for an updated assessment. We rely on a detailed content analysis of local newspaper coverage from nearly 350 U.S. House districts and nationally representative survey data from the 2010 midterms to provide a comprehensive evaluation of whether women experience a more hostile campaign environment than do men. We find that candidate sex does not affect journalists’ coverage of, or voters’ attitudes toward, the women and men running for office in their districts. Rather, reporters’ portrayals and citizens’ assessments of candidates stem primarily from partisanship, ideology, and incumbency, not the sex of the candidate. Although our results differ from much of the existing literature, we regard them as a valuable point of departure for answering pressing questions about gender and representation in contemporary politics, both in an American and comparative context.

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Copyright © American Political Science Association 2015 
Figure 0

Table 1 Candidate sex and news coverage in the 2010 U.S. House elections

Figure 1

Figure 1 Trait mentions in news coverage, by sex of the candidate—2010 U.S. House electionsNote: Dots indicate the proportion of candidates (with 95 percent confidence intervals) who received at least one mention of each trait in the overall amount of news coverage analyzed. For women, N = 108; for men, N = 555.

Figure 2

Figure 2 The impact of candidate sex on trait and issue mentions in news coverage—2010 U.S. House electionsNote: Dots represent unstandardized OLS regression coefficients with 95 percent confidence intervals. Refer to tables A5 and A6 for the full regression equations.

Figure 3

Figure 3 Leadership, empathy, and trustworthiness, by candidate party and sex—evaluations of 2010 U.S. House candidatesNote: Dots indicate the mean rating on a 1 – 4 scale (with 95 percent confidence intervals). For female Democratic candidates, N = 202; for male Democratic candidates, N = 674; for female Republican candidates, N = 91; and for male Republican candidates, N = 805. N varies slightly across traits, as some respondents did not answer all three questions. Refer to table A7.

Figure 4

Figure 4 Competence and integrity, by candidate party and sex—evaluations of 2010 U.S. House candidatesNote: Dots indicate the mean rating on a 1 – 7 scale (with 95 percent confidence intervals). For female Democratic candidates, N = 154; for male Democratic candidates, N = 496; for female Republican candidates, N = 64; and for male Republican candidates, N = 589. N varies slightly across traits, as some respondents did not answer both questions. Refer to table A7.

Figure 5

Figure 5 The impact of candidate sex on evaluations of 2010 U.S. House candidatesNote: Dots for “Strong Leader,” “Empathetic,” and “Trustworthy” are ordered logistic regression coefficients with 95 percent confidence intervals. Dots for “Competent” and “Has Integrity” are OLS regression coefficients with 95 percent confidence intervals. Refer to tables A8 and A9 for the full regression equations.

Figure 6

Figure 6 The impact of trait coverage on evaluations of 2010 U.S. House candidatesNote: Dots for “Strong Leader,” “Empathetic,” and “Trustworthy” are ordered logistic regression coefficients with 95 percent confidence intervals. Dots for “Competent” and “Has Integrity” are OLS regression coefficients with 95 percent confidence intervals. Refer to tables A8 and A9 for the full regression equations.

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