Helping to Break the Glass Ceiling? Fathers, First Daughters, and Presidential Vote Choice in 2016

Abstract

Throughout her 2016 U.S. presidential campaign, Democratic Party nominee Hillary Clinton crafted messages intended to appeal to fathers of daughters and to highlight the implications of her historic nomination for American girls and women. Clinton reminded voters that her election could mean that “fathers will be able to say to their daughters, you, too, can grow up to be president” (Frizell, Time, http://time.com/3920332/transcript-full-text-hillary-clinton-campaign-launch/, 2015). But did these appeals succeed in mobilizing fathers of daughters to support Clinton? Using original cross sectional and experimental survey data from the 2016 CCES, we ask two questions. First, were men who fathered daughters (a life event which we operationalize, for important methodological and theoretical reasons detailed herein, as men who fathered a daughter as their first child) more likely to support, and vote for, Hillary Clinton in the 2016 presidential election than were those who fathered sons as their first child? Second, were Clinton’s direct appeals to fathers of daughters effective in increasing her electoral support? We find that fathers who have daughters as their first child are more likely to prefer and vote for Clinton, and are more likely to support a fictional female congressional candidate using a “Clintonesque” appeal that emphasizes expanding opportunities for “our daughters.” These results suggest that entry into fatherhood with a daughter (as opposed to with a son) is a formative experience for men that has consequences for their political choices in later life. Our conclusions inform the growing literature on the implications of fathering daughters on men’s political behavior.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

Notes

  1. 1.

    Throughout this paper, we use “first daughter” and “first daughterhood” to indicate when a male respondent has a first child who is a daughter.

  2. 2.

    As explained in greater detail below, our survey experiment featured a fictitious female congressional candidate in an attempt to insulate the experimental manipulations from the historic circumstances surrounding Clinton’s 2016 campaign and party nomination, and Clinton as a unique candidate.

  3. 3.

    In our observational analysis, we also uncover statistical evidence that the experience of fathering a daughter positively affects the probability that a father will support Clinton regardless of whether the daughter was first-born. However, for methodological and theoretical reasons described in this paper, we believe that (when using observational data) scholars would be prudent to use information about the first-born child if it is available.

  4. 4.

    Multiple, often intersecting individual-level factors played a role in shaping voters’ preferences in 2016 including age (Medenica 2018), anti-Muslim sentiment (Lajevardi and Oskooii 2018), racial resentment and economic anxieties (e.g., Cramer 2016; Luttig et al. 2017; Manza and Crowley 2017; Schaffner et al. 2018), authoritarian views (Macwilliams 2016), religiosity (Ekins 2017), and “collective narcissism” (Federico and De Zavala 2018). See Manne (2017) on Trump and misogyny.

  5. 5.

    One exception is an initial analysis that shows that men of color were more likely to vote for Clinton in 2016 (Ramakrishnan 2016; see also Towler and Parker 2018).

  6. 6.

    While Tesler (Tesler 2016a, b) found evidence that Clinton drew meaningful support from men who fathered daughters in the early months of the 2016 campaign, we know of no study that examines if fathers of daughters were more likely to support Clinton in the general election.

  7. 7.

    Sanbonmatsu (2002a) connects this baseline preference to gender stereotypes. Likewise, Dolan (2010, 2014) finds that male voters are more likely to see male candidates (as opposed to female candidates) as strong on an array of policy issues, results which also suggest a preference based on gender stereotypes. However, Dolan (2014) finds no evidence that gender stereotypes play into the ultimate electoral decision of these voters.

  8. 8.

    Because motherhood shapes women’s political attitudes in ways that are quite distinct from men’s attitudes (Elder and Greene 2012; Greenlee 2014), and because women, regardless of parental status, offer higher levels of support for female candidates than do men (Plutzer and Zipp 1996; Smith and Fox 2001), we do not expect that having a daughter will produce similar effects on women’s voting behavior and preferences. To strengthen our argument that first daughters have a clear and consistent impact on men’s voting preferences, we also offer full results of analyses for mothers.

  9. 9.

    We use the term “sex” here in concordance with the language used on our survey instrument to assess the identities of men’s offspring which allowed for the choice of either “male” or “female.” See Appendix A for longer discussion of this approach.

  10. 10.

    As we further discuss below, we advance an important methodological argument for focusing on men with first daughters in our analyses to properly operationalize our theory. For the purposes of assessing the effect of the sex of a child on the father’s presidential preferences net of other factors, the sex of the first-born child is our variable of choice, because it is essentially random with respect to parental characteristics. In contrast, the distribution of girl versus boy children in the family may be endogenous to parental preferences about the sex of children and total family size, and thus may be biased as a predictor of presidential preferences.

  11. 11.

    See http://cces.gov.harvard.edu/ for full survey description and Common Content data archive.

  12. 12.

    Since becoming a father entails a variety of selection processes, we did not compare fathers and non-fathers in order to avoid inappropriate comparisons.

  13. 13.

    All of our cross-sectional results are similar with Stein voters included in the 0 category.

  14. 14.

    One hundred percent of respondents identify as either male or female. Two percent of respondents also identify as “transgender” on a question specifically querying gender identity, and an additional 1.4 percent also responded as “prefer not to say” on this question.

  15. 15.

    Seventeen fathers who indicated that they had between 6 and 20 children were dropped from the final analysis out of concern that these individuals may have misrepresented the total number of their children. As a robustness check on our reported analyses, however, we re-estimated our models with all of these fathers included. The results of these additional analyses were substantively very similar to those reported in the paper.

  16. 16.

    The distribution of first daughters and first sons in our data reflects the distribution seen in the general population. We look to the 2013-2015 National Survey of Family Growth (NSFG) in order to benchmark the composition of our sample of fathers of first daughters against the national population of fathers. The NSFG is a survey of both men (N = 4506) and women (5699) aged 15–44 designed to produce national estimates of sexual activity, pregnancy, contraceptive use, medical care and use, father involvement with their children, and attitudes toward sex, childbearing, and marriage for use by the U.S. Department of Health and Human Services’ Centers for Disease Control and Prevention. It is primarily used by the federal government to plan funding for health services and health educational programs. According to the 2013-15 NSFG, of the 1719 men who have at least one biological child, 48% of these fathers had a first daughter and 51% had a first son. This closely mirrors the distribution of fathers of first daughters (45%) and first sons (55%) in our CCES sample, and thus we are confident that our sample mimics the distribution of fathers in the nation more broadly.

  17. 17.

    We include this final control in light of Healy and Malhotra’s (2013) finding that men with sisters may express more conservative gender attitudes. Though scholars have identified the contexts in which other familial relationships are consequential to men’s attitudes on gender equality, such as the employment status of one’s wife and mother or the educational attainment of one’s mother (Bolzendahl and Myers 2004; Davis and Greenstein 2009), we did not have these measures available in our data. We do, however, include a control for marital status, which we find does have a positive impact on electoral support for Clinton..

  18. 18.

    For question wording for the items that constitute this scale are found in Appendix B. Kinder and Sanders (1996) also used these measures.

  19. 19.

    We define “definite voters” as all individuals who indicate that they “definitely” planned to vote in the 2016 elections (or indicated they had already done so); and we define as voters all individuals who self-report that they “definitely voted in the General Election.” Note that each measure was taken at a different period in time (before and after the election, respectively).

  20. 20.

    We note that the hostile sexism scale does not reach a level of statistical significance in our model, despite other recent scholarship demonstrating its importance in predicting presidential preference in 2016 (Bracic et al. 2018; Cassese and Holman 2018; Valentino et al. 2018). However, we hesitate to derive any general conclusions from the results of our models about the influence of hostile sexism on support for Clinton, for several reasons. First, because the group examined in research highlighting the effect of hostile sexism on presidential support (white adults) is quite different from that examined in our study (fathers), it is possible that the general effect found in research on white adults simply fails to hold for fathers. However, and second, it may be that the null effects we find are attributable to the small sample of fathers used in our analysis. Our data do not allow us to assess these alternatives in detail. Given these uncertainties, and especially given that our research design was not developed with the primary purpose of evaluating the effect of hostile sexism on vote choice in mind, we prefer not to draw any firm conclusions about the effect of hostile sexism on support for Clinton among fathers at the present time. We acknowledge that whether and how hostile sexism influences the presidential preferences of different subgroups, including fathers and non-fathers, is a worthy subject for future research.

  21. 21.

    Our analysis of the effect of the experience of fathering a first daughter (or first son) on fathers’ presidential preferences takes place in the context of a very large literature on the correlates of presidential preferences, as well as smaller but fast-growing literature on the factors influencing support for Hillary Clinton/Donald Trump. Given that so much is known about what influences presidential preferences, we believe that the most appropriate way to assess the effect of first daughters is within multivariate statistical models that control for the full array of factors that has been demonstrated to affect individual support for (1) presidential candidates in general and/or (2) Hillary Clinton/Donald Trump in particular.

  22. 22.

    When using predicted values in order to determine statistically significant marginal effects, it is too conservative to use two separate 95% confidence intervals (Knezevic 2008). When the standard errors are roughly equivalent, a single 95% test translates into using two sets of 84% confidence intervals (Payton et al. 2003). Figure 1 displays two separate 84% confidence intervals..

  23. 23.

    We provide further discussion and analysis of mothers in the Supplemental Information.

  24. 24.

    To guard against the potential that a respondent may live in one of Minnesota’s actual nine congressional districts, we created the fictional 10th district of Minnesota. To avoid the possibility that a respondent living in Minnesota may recognize that the 10th district does not exist, we ran a model that controlled for whether the respondent lived in Minnesota. The results do not substantively differ when including this control.

  25. 25.

    We restricted the sample to respondents who correctly answered our attention check question which asked, “In what state will Molly Smith’s congressional election take place?”.

  26. 26.

    Smith’s ideology is assessed with the question, “Where would you place Smith on the ideological scale?”.

  27. 27.

    In this paper, we contemplate the impact of entering fatherhood with a child that the father categorizes in our survey as “female.” We acknowledge that for some small portion of fathers, the gender identity of their child may change over time, such that it does not neatly align with the dichotomous categories of sex that our survey question employs. Our survey instrument did not investigate whether fathers’ children either identify and/or are acknowledged by their father as transgender, non-binary, intersex, or gender non-conforming. We therefore also acknowledge that a father’s report that he has a daughter or a son may not map on to the gender identity of that child. Future research should further explore these dynamics.

References

  1. Alwin, D., Cohen, R., & Newcomb, T. (1991). Political attitudes over the life span: The Bennington women after fifty years. Madison, WI: University of Wisconsin Press.

    Google Scholar 

  2. Ansolabehere, S., & Schaffner, B. (2014). Does survey mode still matter? Findings from a 2010 multi-mode comparison. Political Analysis, 22(3), 285–303.

    Google Scholar 

  3. Arceneaux, K., & Nickerson, D. W. (2009). Modeling certainty with clustered data: A comparison of methods. Political Analysis, 17(2), 177–190.

    Google Scholar 

  4. Aronson, P. (2003). Feminists or ‘Postfeminists’? Young women’s attitudes toward feminism and gender relations. Gender & Society, 17(6), 903–922.

    Google Scholar 

  5. Barreto, M. A. (2007). ¡Sı Se Puede! Latino candidates and the mobilization of Latino voters. American Political Science Review, 101(3), 425–441.

    Google Scholar 

  6. Blake, A. (2016). “How America decided, at the last moment, to elect Donald Trump.” The Washington Post. Retrieved October 15, 2018 from https://www.washingtonpost.com/news/the-fix/wp/2016/11/17/how-america-decided-at-the-very-last-moment-to-elect-donald-trump/?noredirect=on.

  7. Bock, J., Byrd-Craven, J., & Burkley, M. (2017). The role of sexism in voting in the 2016 presidential election. Personality and Individual Differences, 119, 189–193.

    Google Scholar 

  8. Bolzendahl, C. I., & Myers, D. J. (2004). Feminist attitudes and support for gender equality: Opinion change in women and men, 1974–1998. Social Forces, 83(2), 759–790.

    Google Scholar 

  9. Box-Steffensmeier, J. M., De Boef, S., & Lin, T.-m. (2004). The dynamics of the partisan gender gap. American Political Science Review, 98(3), 515–528.

    Google Scholar 

  10. Bracic, A., Israel-Trummel, M., & Shortle, A. F. (2018). Is sexism for White people? Gender stereotypes, race, and the 2016 presidential election. Political Behavior. https://doi.org/10.1007/s11109-018-9446-8.

    Article  Google Scholar 

  11. Brooks, D. (2013). He runs, she runs: Why gender stereotypes do not harm women candidates. Princeton, NJ: Princeton University Press.

    Google Scholar 

  12. Burden, B., Ono, Y., & Yamada, M. (2017). Reassessing public support for a female president. The Journal of Politics, 79(3), 1073–1078.

    Google Scholar 

  13. Cassese, E., & Barnes, T. (2018). Reconciling sexism and women’s support for republican candidates: A look at gender, class, and whiteness in the 2012 and 2016 presidential races. Political Behavior. https://doi.org/10.1007/s11109-018-9468-2.

    Article  Google Scholar 

  14. Cassese, E., & Holman, M. R. (2018). Playing the woman CARD: Ambivalent Sexism in the 2016 U.S. presidential race. Political Psychology. https://doi.org/10.1111/pops.12492.

    Article  Google Scholar 

  15. Center for American Women in Politics (CAWP). (2018). “2018 Summary of Women Candidates.” CAWP Election Watch. Retrieved August 17, 2018 from http://www.cawp.rutgers.edu/2018-women-candidates-us-congress-and-statewide-elected-executive.

  16. Conley, D., & Rauscher, E. (2013). The effect of daughters on partisanship and social attitudes toward women. Sociological Forum, 28(4), 700–718.

    Google Scholar 

  17. Cramer, K. J. (2016). The politics of resentment: Rural consciousness in Wisconsin and the rise of Scott Walker. Chicago, IL: University of Chicago Press.

    Google Scholar 

  18. Cronqvist, H., & Frank, Yu. (2017). Shaped by their daughters: Executives, female socialization, and corporate social responsibility. Journal of Financial Economics, 126(3), 543–562.

    Google Scholar 

  19. Dahl, M., Dezső, C., & Ross, D. (2012). Fatherhood and managerial style: How a male CEO’s children affect the wages of his employees. Administrative Science Quarterly, 57(4), 669–693.

    Google Scholar 

  20. Dahl, G., & Moretti, E. (2008). The demand for sons. Review of Economic Studies, 75(4), 1085–1120.

    Google Scholar 

  21. Davis, S., & Greenstein, T. (2009). Gender ideology: Components, predictors, and consequences. Annual Review of Sociology, 35, 87–105.

    Google Scholar 

  22. Deave, T., & Johnson, D. (2008). The transition to parenthood: What does it mean for fathers? Journal of Advanced Nursing, 63(6), 626–633.

    Google Scholar 

  23. Dickerson, J. (2016). “Hillary Clinton’s fight for the dad vote.” CBS News. Retrieved July 10, 2017 from http://www.cbsnews.com/news/hillary-clintons-fight-for-the-dad-vote/.

  24. Dinas, E. (2013). Opening ‘openness to change’: Political events and the increased sensitivity of young adults. Political Research Quarterly, 66(4), 868–882.

    Google Scholar 

  25. Dittmar, K. (2017). Finding gender in election 2016: Lessons from presidential gender watch. New Brunswick, NJ: Center for American Women and Politics, Rutgers University.

    Google Scholar 

  26. Dolan, K. (2010). The impact of gender stereotyped evaluations on support for women candidates. Political Behavior, 32(1), 69–88.

    Google Scholar 

  27. Dolan, K. (2014). When does gender matter?: Women candidates and gender stereotypes in American elections. New York: Oxford University Press.

    Google Scholar 

  28. Dunning, T., & Harrison, L. (2010). Cross-cutting cleavages and ethnic voting: An experimental study of cousinage in Mali. The American Political Science Review, 104(1), 21–39.

    Google Scholar 

  29. Eifert, B., Miguel, E., & Posner, D. (2010). Political competition and ethnic identification in Africa citation terms of use. American Journal of Political Science, 54(2), 494–510.

    Google Scholar 

  30. Ekins, E. (2017). “The five types of Trump voters: Who they are and what they believe.” A Research Report from the Democracy Fund Voter Study Group. Retrieved July 2, 2018 from https://www.voterstudygroup.org/publications/2016-elections/the-five-types-trump-voters.

  31. Elder, L., & Greene, S. (2012). The politics of parenthood. Albany, NY: SUNY Press.

    Google Scholar 

  32. Elder, G., Johnson, M. K., & Crosnoe, R. (2003). The Emergence and development of life course theory. In J. T. Mortimer & M. J. Shanahan (Eds.), Handbook of the life course (pp. 3–19). New York: Kluwer Academic/Plenum Publishers.

    Google Scholar 

  33. Federico, C., & Zavala, A. G. D. (2018). Collective narcissism and the 2016 U.S. presidential vote. Public Opinion Quarterly, 82(1), 110–121.

    Google Scholar 

  34. Frizell, S. (2015). “Read the Full Text of Hillary Clinton’s Campaign Launch Speech.” Time. Retrieveed August 10, 2017 http://time.com/3920332/transcript-full-text-hillary-clinton-campaign-launch/.

  35. Gerber, A., Gimpel, J., Green, D., & Shaw, D. (2011). How large and long-lasting are the persuasive effects of televised Campaign ads? Results from a randomized field experiment. American Political Science Review, 105(1), 135–150.

    Google Scholar 

  36. Glick, P., & Fiske, S. T. (1996). The ambivalent sexism inventory: Differentiating hostile and benevolent sexism. Journal of Personality and Social Psychology, 70(3), 491–512.

    Google Scholar 

  37. Glick, P., & Fiske, S. T. (2001). An ambivalent alliance. Hostile and benevolent sexism as complementary jutifications for gender inequality. American Psychologist, 56(2), 109–118.

    Google Scholar 

  38. Glynn, A., & Sen, M. (2015). Identifying judicial empathy: Does Having daughters cause judges to rule for women’s issues? American Journal of Political Science, 59(1), 37–54.

    Google Scholar 

  39. Goldstein, K., & Ridout, T. (2004). Measuring the effects of televised political advertising in the United States. Annual Review of Political Science, 7, 205–226.

    Google Scholar 

  40. Green, D., Palmquist, B., & Schickler, E. (2002). Partisan hearts and minds: Political parties and the social identities of voters. New Haven, CT: Yale University Press.

    Google Scholar 

  41. Green, D., & Vavreck, L. (2008). Analysis of cluster-randomized experiments: A comparison of alternative estimation approaches. Political Analysis, 16(2), 138–152.

    Google Scholar 

  42. Greenlee, J. (2014). The political consequences of motherhood. Ann Arbor, MI: University of Michigan Press.

    Google Scholar 

  43. Gurin, P. (1985). Women’s gender consciousness. The Public Opinion Quarterly, 49(2), 143–163.

    Google Scholar 

  44. Healy, A., & Malhotra, N. (2013). Childhood socialization and political attitudes: Evidence from a natural experiment. The Journal of Politics, 75(4), 1023–1037.

    Google Scholar 

  45. Herrnson, P., Celeste Lay, J., & Stokes, A. K. (2003). Women running ‘as women’: Candidate gender, campaign issues, and voter-targeting strategies. Journal of Politics, 65(1), 244–255.

    Google Scholar 

  46. Junn, J. (2017). The trump majority: White womanhood and the making of female voters in the U.S. Politics, Groups, and Identities, 5(2), 343–352.

    Google Scholar 

  47. Kaufmann, K. (2002). Culture wars, secular realignment, and the gender gap in party identification. Political Behavior, 24(3), 283–307.

    Google Scholar 

  48. Kinder, D., & Sanders, L. (1996). Divided by color: Racial politics and democratic ideals. Chicago, IL: University of Chicago Press.

    Google Scholar 

  49. Klar, S., Madonia, H., & Schneider, M. C. (2014). The influence of threatening parental primes on mothers’ versus fathers’ policy preferences. Politics, Groups, and Identities, 2(4), 607–623.

    Google Scholar 

  50. Knezevic, A. (2008). “Overlapping confidence intervals and statistical significance.” StatNews: Cornell University Statistical Consulting Unit 73(1):.

  51. Knoester, C., & Eggebeen, D. J. (2006). The effects of the transition to parenthood and subsequent children on men’s well-being and social participation. Journal of Family Issues, 27(11), 1532–1560.

    Google Scholar 

  52. Krasno, J., & Green, D. (2008). Do televised presidential ads increase voter turnout? Evidence from a natural experiment. The Journal of Politics, 70(1), 245–261.

    Google Scholar 

  53. Ladd, J. M. (2010). Power of elite opinion leadership the neglected toward the news media: To produce antipathy evidence from a survey experiment. Political Behavior, 32(1), 29–50.

    Google Scholar 

  54. Lajevardi, N., & Oskooii, Kassra A. R. (2018). Old-fashioned racism, contemporary Islamophobia, and the isolation of Muslim Americans in the age of Trump. Journal of Race, Ethnicity, and Politics, 3(1), 112–152.

    Google Scholar 

  55. Lau, R., & Rovner, I. B. (2009). Negative campaigning. Annual Review of Political Science, 12, 285–306.

    Google Scholar 

  56. Luttig, M. D., Federico, C. M., & Lavine, H. (2017). Supporters and opponents of Donald Trump respond differently to racial cues: An experimental analysis. Research & Politics, 4(4), 1–8.

    Google Scholar 

  57. Macwilliams, M. C. (2016). Who decides when the party doesn’t? Authoritarian voters and the rise of Donald Trump. PS: Political Science and Politics, 49(4), 716–721.

    Google Scholar 

  58. Manne, K. (2017). Down girl: The logic of misogyny. New York: Oxford University Press.

    Google Scholar 

  59. Manza, J., & Crowley, N. (2017). Working class hero? Interrogating the social bases of the rise of Donald Trump. The Forum, 15(1), 3–28.

    Google Scholar 

  60. Markus, G. (1988). The impact of personal and national economic conditions on the presidential vote: A pooled cross-sectional analysis. American Journal of Political Science, 32(1), 137–154.

    Google Scholar 

  61. McCall, L., & Orloff, A. S. (2017). The multidimensional politics of inequality: Taking stock of identity politics in the U.S. presidential election of 2016. British Journal of Sociology, 68, S34–S56.

    Google Scholar 

  62. Medenica, V. E. (2018). Millennials and race in the 2016 election. Journal of Race, Ethnicity, and Politics, 3(1), 55–76.

    Google Scholar 

  63. New York Times. (2015). “Full Transcript: Democratic Presidential Debate.” New York Times. Retrieved July 6, 2017 from https://www.nytimes.com/2015/10/14/us/politics/democratic-debate-transcript.html.

  64. New York Times Editorial Board. (2016). “The Sleaziness of Donald Trump.” New York Times. Retrieved June 28, 2018 from https://www.nytimes.com/2016/10/08/opinion/the-sleaziness-of-donald-trump.html.

  65. Nteta, T., & Greenlee, J. (2013). A change is gonna come: Generational membership and white racial attitudes in the 21st century. Political Psychology, 34(6), 877–897.

    Google Scholar 

  66. Oswald, A., & Powdthavee, N. (2010). Daughters and left-wing voting. The Review of Economics and Statistics, 92(2), 213–227.

    Google Scholar 

  67. Payton, M., Greenstone, M., & Schenker, N. (2003). Overlapping confidence intervals or standard error intervals: What do they mean in terms of statistical significance? Journal of Insect Science, 3(1), 1–6.

    Google Scholar 

  68. Petrocik, J. R. (1996). Issue ownership in presidential elections, with a 1980 Case study. American Journal of Political Science, 40(3), 825–850.

    Google Scholar 

  69. Phillips, C. (2018). Wanting, and weighting: White women and descriptive representation in the 2016 presidential election. Journal of Race, Ethnicity, and Politics, 3(1), 29–51.

    Google Scholar 

  70. Plutzer, E. (2002). Becoming a habitual voter: Inertia, resources, and growth in young adulthood. American Political Science Review, 96(1), 41–56.

    Google Scholar 

  71. Plutzer, E., & Zipp, J. (1996). Identity politics, partisanship, and voting for women candidates. Public Opinion Quarterly, 60, 30–57.

    Google Scholar 

  72. Prokos, A., Baird, C., & Keene, J. (2010). Attitudes about affirmative action for women: The role of children in shaping parents’ interests. Sex Roles, 62(5–6), 347–360.

    Google Scholar 

  73. Ramakrishnan, K. (2016). “Trump got more votes from people of color than Romney did. Here’s the data.” Monkey Cage Blog, The Washington Post. Retrieved July 19, 2017 from https://www.washingtonpost.com/news/monkey-cage/wp/2016/11/11/trump-got-more-votes-from-people-of-color-than-romney-did-heres-the-data/?utm_term=.8b625e45812a.

  74. Sanbonmatsu, K. (2002a). Gender stereotypes and vote choice. American Journal of Political Science, 46(1), 20–34.

    Google Scholar 

  75. Sanbonmatsu, K. (2002b). Political parties and the recruitment of women to state legislatures. The Journal of Politics, 64(3), 791–809.

    Google Scholar 

  76. Sanbonmatsu, K., & Dolan, K. (2009). Do gender stereotypes transcend party? Political Research Quarterly, 62(3), 485–494.

    Google Scholar 

  77. Schaffner, B., MacWilliams, M., & Nteta, T. (2018). Understanding White polarization in the 2016 vote for president: The sobering role of racism and sexism. Political Science Quarterly, 133(1), 9–34.

    Google Scholar 

  78. Sears, D. (1981). Life stage effects upon attitude change, especially among the elderly. In S. B. Kiesler, J. N. Morgan, & V. K. Oppenheimer (Eds.), Aging: Social change (pp. 183–204). New York: Academic Press.

    Google Scholar 

  79. Sears, D., & Funk, C. (1999). Evidence of the long-term persistence of adults’ political predispositions. The Journal of Politics, 61(1), 1–28.

    Google Scholar 

  80. Sears, D., Lau, R., Tyler, T., & Allen, H. (1980). Self-interest vs. symbolic politics in policy attitudes and presidential voting. American Political Science Review, 74(3), 670–684.

    Google Scholar 

  81. Sears, D., & Levy, S. (2003). Childhood and adult political development. In D. Sears, L. Huddy, & R. Jervis (Eds.), Oxford handbook of political psychology (pp. 60–109). New York: Oxford University Press.

    Google Scholar 

  82. Sears, D., & Valentino, N. (1997). Politics matters: Political events as catalysts for preadult socialization. American Political Science Association, 91(1), 45–65.

    Google Scholar 

  83. Setzler, M., & Yanus, Y. (2018). Why did women vote for Donald Trump? PS: Political Science & Politics, 51(3), 523–527.

    Google Scholar 

  84. Shafer, E. F., & Malhotra, N. (2011). The effect of a child’s sex on support for traditional gender roles. Social Forces, 90(1), 209–222.

    Google Scholar 

  85. Sharrow, E., Rhodes, J., Nteta, T., & Greenlee, J. (2018). The first-daughter effect: The impact of fathering first daughters on men’s preferences on gender-equality issues. Public Opinion Quarterly, 82(3), 493–523.

    Google Scholar 

  86. Sides, J., Tesler, M., & Vavreck, L. (2018). Identity crisis: The 2016 presidential campaign and the battle for the meaning of America. Princeton, NJ: Princeton University Press.

    Google Scholar 

  87. Smith, E., & Fox, R. (2001). The electoral fortunes of women candidates for congress. Political Research Quarterly, 54(1), 205–221.

    Google Scholar 

  88. Strolovitch, D. Z., Wong, J. S., & Proctor, A. (2017). A possessive investment in white heteropatriarchy? The 2016 election and the politics of race, gender, and sexuality. Politics, Groups, and Identities, 5(2), 353–363.

    Google Scholar 

  89. Tesler, M. (2016a). “A key reason young people don’t support Hillary Clinton? They don’t have daughters.” Monkey Cage Blog, The Washington Post. Retrieved July 10, 2017 from https://www.washingtonpost.com/news/monkey-cage/wp/2016/02/11/a-key-reason-young-people-dont-support-hillary-clinton-they-dont-have-daughters/?utm_term=.69017896f20f.

  90. Tesler, M. (2016b). “Parents of Daughters Support Hillary Clinton More than Parents of Sons.” Monkey Cage Blog, The Washington Post. Retrieved July 6, 2017 from https://www.washingtonpost.com/news/monkey-cage/wp/2016/01/05/parents-of-daughters-support-hillary-clinton-more-than-parents-of-sons/?utm_term=.1060e2895c02.

  91. Tesler, M., & Sears, D. (2010). “The paradox of gender traditionalists’ support for Hillary Clinton.” In Obama’s Race: The 2008 election and the dream of a post-racial America (pp. 115–26). Chicago, IL: University of Chicago Press.

  92. Towler, C. C., & Parker, C. S. (2018). Between anger and engagement: Donald Trump and Black America. Journal of Race, Ethnicity, and Politics, 3(1), 219–253.

    Google Scholar 

  93. Traister, R. (2016). “Trump’s one public service was exposing the misogyny of the GOP.” New York Magazine. Retrieved June 30, 2018 from https://www.thecut.com/2016/10/trumps-one-service-was-exposing-the-misogyny-of-the-gop.html.

  94. Umberson, D., Pudrovska, T., & Reczek, C. (2010). Parenthood, Childlessness, and Well-Being: A Life Course Perspective. Journal of Marriage and Family, 72(3), 612–629.

    Google Scholar 

  95. Valentino, N., Wayne, C., & Oceno, M. (2018). “Mobilizing sexism: The interaction of emotion and gender attitudes in the 2016 US presidential election. Public Opinion Quarterly, 82, 213–235.

    Google Scholar 

  96. Warner, R. (1991). Does the sex of your children matter? Support for feminism among women and men in the United States and Canada. Journal of Marriage and Family, 53(4), 1051–1056.

    Google Scholar 

  97. Warner, R., & Steel, B. (1999). Child rearing as a mechanism for social change: The relationship of child gender to parents’ committment to gender equity. Gender & Society, 13(4), 503–517.

    Google Scholar 

  98. Washington, E. (2008). Female socialization: How daughters affect their legislator fathers’ voting on women’s issues. American Economic Review, 98(1), 311–332.

    Google Scholar 

  99. West, L. (2016). “Donald and Billy on the Bus.” New York Times. Retrieved June 30, 2018 from https://www.nytimes.com/2016/10/09/opinion/sunday/donald-and-billy-on-the-bus.html.

  100. Wolbrecht, C. (2000). The politics of women’s rights: Parties, positions, and change. Princeton, NJ: Princeton University Press.

    Google Scholar 

Download references

Acknowledgements

We thank all those who offered feedback on previous versions of this manuscript, especially Laura Stoker, Melissa Deckman, Sarah Kahn, the Working Group on American Politics at the University of Massachusetts Amherst, the University of Massachusetts Center for Research on Families, Hande Inanc, and the anonymous reviewers. This work was supported by a Faculty Research Grant from the University of Massachusetts–Amherst [to T.N.] and the Norman Fund at Brandeis University [to J.G.]. The 2016 Cooperative Congressional Election Study was supported by the National Science Foundation [Grant #1559125 to Stephen Ansolabehere], and the authors thank the co-PIs, Stephen Ansolabehere, Brian Schaffner, and Samantha Luks, for their support of this research.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Jill S. Greenlee.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 209 kb)

Appendices

Appendix A

The First Daughter Versus Other Operational Definitions of Daughters

We have argued that the first daughter is the best operational definition of exposure to daughters, for reasons relating to research design, modeling, and substantive theory. Here we provide more evidence for our claim that—especially given its research-design advantages—using the first daughter variable is the best decision from the perspective of modeling support for Clinton.

First, we observe that, among the fathers in our analysis, three different operational definitions of exposure to daughters that have been used in previous empirical research and which we collected in our survey—daughter as a first child (no = 0, yes = 1), the presence of a daughter in the family (no = 0, yes = 1), and the proportion of children in the family that are daughters (a continuous 0–1 variable)—are extremely closely related.Footnote 27 Among fathers in our study, the three items have a scale reliability coefficient of 0.88, suggesting that they likely tap the same underlying construct of exposure to a daughter. This finding suggests the utility of relying on the first daughter measure, especially given its superiority in terms of research design.

Second, and in part due to the very close relationship between these variables, the inclusion of these additional measures of exposure to daughters to our main statistical models adds very little in terms of explaining fathers’ support for Clinton. Indeed, as shown in Appendix A, Table 1, overall goodness-of-fit statistics for models of both pre-election preference for Clinton and post-election reported voting for Clinton are virtually identical for models that contain only the first daughter variable, and those that contain the additional measures of exposure to daughters, respectively. Thus, parsimony suggests relying on a model that uses only the first daughter variable.

See Tables 8, 9 and 10.

Table 8 Goodness-of-fit statistics for alternative models of preference for Clinton and reported vote for Clinton
Table 9 Preference for Clinton collinearity, 2016 CCES with weights
Table 10 Vote choice collinearity, 2016 CCES with weights

Appendix B: Survey Questions from 2016 CCES

Age In what year were you born? [TEXT ENTRY]

Sex Are you male or female? (1. Male; 2. Female)

Education What is the highest level of education you have completed? (1. No HS; 2. High school graduate; 3. Some college; 4. 2-year; 5. 4-year; 6. Post-grad)

Race What racial or ethnic group best describes you? (1. White; 2. Black; 3. Hispanic; 4. Asian; 5. Native American; 6. Mixed; 7. Other; 8. Middle Eastern)

Employment Status Which of the following best describes your current employment status? (1. Full-time; 2. Part-time; 3. Temporarily laid off; 4. Unemployed; 5. Retired; 6. Permanently disabled; 7. Homemaker; 8. Student; 9. Other)

Marital Status What is your marital status? (1. Married; 2. Separated; 3. Divorced; 4. Widowed; 5. Single; 6. Domestic Partnership)

Party Identification Generally speaking, do you think of yourself as a…? (1. Democrat; 2. Republican; 3. Independent; 4. Other; 5. Not sure)

Ideology Thinking about politics these days, how would you describe your own political viewpoint? (1. Very liberal; 2. Liberal; 3. Moderate; 4. Conservative; 5. Very conservative; 6. Not sure)

Importance of religion How important is religion in your life? (1. Very important; 2. Somewhat important; 3. Not too important; 4. Not at all important)

Income Thinking back over the past year, what was your family’s annual income? (1. Less than $10,000; 2. $10,000–$19,999; 3. $20,000–$29,999; 4. $30,000–$39,999; 5. $40,000–$49,999; 6. $50,000–$59,999; 7. $60,000–$69,999; 8. $70,000–$79,999; 9. $80,000–$99,999; 10. $100,000–$119,999; 11. $120,000–$149,999; 12. $150,000–$199,999; 13. $200,000–$249,999; 14. $250,000–$349,999; 15. $350,000–$499,999; 16. $500,000 or more; 97. Prefer not to say)

Sisters How many siblings do you have? Please count those no longer living, as well as those alive now. Also include any stepbrothers/sisters and children adopted by your parents. (TEXT ENTRY)

Father How many children do you have? Please count all that were alive at any time, including any you have from previous marriage or relationship, any adopted children, foster children (who have lived with you for at least a year), or stepchildren. Also, be sure to count any adult children as well as those under the age of 18. (TEXT ENTRY)

Age of Child In what year was (Insert 1st, 2nd, 3rd, 4th, or 5th Child) born? (TEXT ENTRY)

Sex of Child What is this (Insert 1st, 2nd, 3rd, 4th, or 5th Child) gender? (1. Male or 2. Female)

Racial Resentment Scale Items (1. Disagree Strongly; 2. Disagree; 3. Neither Agree nor Disagree; 4. Agree; 5. Strongly Agree): (1) Irish, Italians, Jews and many other minorities overcame prejudice and worked their way up. Blacks should do the same without any special favors. (2) Generations of slavery and discrimination have created conditions that make it difficult for blacks to work their way out of the lower class. (3) Over the past few years, blacks have gotten less than they deserve. (4) It’s really a matter of some people not trying hard enough; if blacks would only try harder they could be as well off as whites.

Hostile Sexism Scale Items (1. Disagree Strongly; 2. Disagree; 3. Neither Agree nor Disagree; 4. Agree; 5. Strongly Agree): (1) Many women are actually seeking special favors, such as hiring policies that favor them over men, under the guise of asking for “equality.” (2) Women are too easily offended. (3) Women seek to gain power by getting control over men. (4) When women lose to men in a fair competition, they typically complain about being discriminated against.

Economy is Worse Over the past year the nation’s economy has…? (1. Gotten much better; 2. Gotten better; 3. Stayed about the same; 4. Gotten worse; 5. Gotten much worse; 6. Not sure)

2016 Intent to vote (Pre-election) Do you intend to vote in the 2016 general election? (1. Yes, definitely; 2. Probably; 3. I already voted (early or absentee); 4. No; 5. Undecided)

2016 Presidential Preference (Pre-Election) Which candidate for President of the United States do you prefer? (1. Donald Trump; 2. Hillary Clinton; 3. Gary Johnson; 4. Jill Stein; 5. Other; 6. I Won’t Vote in this Election; 7. I’m Not Sure)

2012 Presidential Vote Choice (Pre-Election) In 2012, who did you vote for in the election for President? (1. Barack Obama; 2. Mitt Romney; 3. Someone Else; 4. Did Not Vote; 5. Don’t Recall)

Voted 2016 (Post-election) Which of the following statements best describes you? (1. I did not vote in the election this November; 2. I thought about voting this time but didn’t; 3. I usually vote, but didn’t this time; 4. I attempted to vote but did not or could not; 5. I definitely voted in the General Election)

2016 Presidential Vote Choice (Post-Election) For whom did you vote for President of the United States? (1. Donald Trump; 2. Hillary Clinton; 3. Gary Johnson; 4. Jill Stein; 5. Evan McMullin; 6. Other; 7. I’m Not Sure)

Molly Smith Experimental Treatments

Control Molly Smith is running to become the first woman to represent Minnesota’s 10th District.

STEM Treatment Molly Smith is running to become the first woman to represent Minnesota’s 10th District. She supports policies that would help increase the participation of women in careers in science, technology, engineering, and mathematics (STEM).

Clintonesque Treatment Molly Smith is running to become the first woman to represent Minnesota’s 10th District. She supports policies that would help increase the participation of women in careers in science, technology, engineering, and mathematics (STEM). She has said of her candidacy, “this campaign is about making sure there are no ceilings, no limits on any of us, and to ensure that our daughters will forever know that there is no barrier to who they are and what they can be in the United States of America.”

Smith Vote Choice Imagine you live in Smith’s district. Please indicate your likelihood that you would vote for her. (Scale: 1 = Very Unlikely to Vote for Her to 100 Very Likely to Vote for Her)

Smith Ideology Where would you place Smith on the ideological scale? (1. Very Liberal; 2. Liberal; 3. Somewhat Liberal; 4. Middle of the Road; 5. Somewhat Conservative; 6. Conservative; 7. Very Conservative)

Attention Check In what state will Molly Smith’s congressional election take place? (1. Indiana; 2. Connecticut; 3. Massachusetts; 4. Minnesota)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Greenlee, J.S., Nteta, T.M., Rhodes, J.H. et al. Helping to Break the Glass Ceiling? Fathers, First Daughters, and Presidential Vote Choice in 2016. Polit Behav 42, 655–695 (2020). https://doi.org/10.1007/s11109-018-9514-0

Download citation

Keywords

  • Fatherhood
  • Gender
  • Voting behavior
  • Hillary Clinton
  • 2016