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Religious Differences among Congressional Districts and the Success of Women Candidates

Published online by Cambridge University Press:  31 May 2016

Mark Setzler*
Affiliation:
High Point University
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Abstract

Scholars exploring the female representation gap in the U.S. Congress have pointed to district-level differences to explain why some districts regularly field women candidates and elect congresswomen while others almost never do. Specifically, demographic, economic, and political characteristics strongly influence a district's female candidacy, nomination, and election rates. This article asks whether also knowing about a district's religious environment helps us better predict the presence and success of women candidates. My central finding is that religiosity, in general, and the strength of some denominations within a district are strong predictors of where women will run and how well they will compete.

Information

Type
Research Article
Copyright
Copyright © The Women and Politics Research Section of the American Political Science Association 2016 
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Figure 1. Share of congressional districts that had, nominated, and elected woman candidates, by rates of religious adherence, 2006–2012. The low-religiosity districts are in the bottom quintile with respect to the share of their residents who are affiliated with any religious congregation. The high-religiosity districts are in the top quintile.

Figure 1

Table 1. Logistic regression estimates predicting the likelihood that a district had, nominated, and elected a woman House candidate

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Figure 2. Religious differences among districts and their probabilities of having, nominating, and electing a woman. Bars plot the predicted probabilities that districts with disproportionately high and low shares of religious residents elected a woman, nominated a woman, or had at least one woman candidate, with all other variables (see Table 1) held constant at their average marginal effects. The lines mark 95% confidence intervals. The low-religiosity estimates are calculated for a district whose religious population share is equal to the mean share for all of the districts in bottom quintile of adherence rates for the noted religious group. The high-religiosity estimates are for a typical district in the top quintile.

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Figure 3. Religious differences among districts and the probability that their major party primaries had at least one woman candidate. Bars compare the predicted probabilities of a woman entering the Democratic/Republican primary in a low- and a high-religion district, with all other variables (see Table 2) held constant at their average marginal effects. The lines mark 95% confidence intervals. The low-religiosity estimates are for a district whose religious population share is equal to the mean share for all of the districts in bottom quintile of adherence rates for the noted religious group. The high-religiosity estimates are for a district in the top quintile.

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Figure 4. Religious differences among districts and the probability that their major party primaries nominated a woman. Bars plot the predicted probabilities of nominating a Democratic/Republican woman in low- and high-religion districts, with all other variables (see Table 2) held constant at their average marginal effects. The lines mark 95% confidence intervals. The low-religiosity estimates are calculated for a typical district whose religious population share is equal to the mean share for all of the districts in bottom quintile of adherence rates for the noted religious group. The high-religiosity estimates are for a district in the top quintile.

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Figure 5. Religious differences among districts and their probability of electing a woman, by electoral stage. Bars plot the predicted probabilities of a electing a congresswoman in a low- and a high-religion district at different stages of the electoral cycle, with all other variables (see Tables 1 and 3) held constant at their average marginal effects. The lines mark 95% confidence intervals. The low-religiosity estimates are for a district whose religious population share is equal to the mean share for all of the districts in bottom quintile of adherence rates for the noted religious group. The high-religiosity estimates are for a typical district in the top quintile.

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Table 2. Logistic regression estimates of the likelihood that a district's Democratic and Republican primaries had and nominated a female candidate

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Table 3. Logistic regression estimates of the likelihood that a district elected a woman, by electoral stage

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