TY - JOUR
AU - Archer, Allison M N
AB - Abstract Since the 2016 US presidential campaign and the rise of the #MeToo movement, issues of sexual assault and harassment have risen to prominence. At the same time, these issues have also been understood and evaluated through the lens of partisanship. The US Supreme Court confirmation hearings of Brett Kavanaugh exemplified these dynamics by providing clear partisan and emotion-laden cues to citizens. Given these events’ temporal proximity to the midterms, we argue that the confirmation hearings not only amplified an ongoing conversation, but also heightened the effect of sexist predispositions on turnout. Using a unique online survey with validated voter turnout in the 2018 midterms, we find that higher levels of modern sexism increased turnout among Republicans while lower levels of modern sexism increased turnout among Democrats. In 2018, sexist predispositions triggered turnout in opposing ways across the aisle. The 2016 presidential election and the #MeToo movement shifted the national conversation toward issues of sexual assault, sexual harassment, and gendered power imbalances in the United States. These issues even reached the highest court in the land. On September 16, 2018, the Washington Post reported on Christine Blasey Ford’s allegations of sexual assault by Supreme Court nominee Brett Kavanaugh. Amidst rancorous partisan debate and concomitant media coverage, Kavanaugh and Blasey Ford testified before the Senate Judiciary Committee, and on October 6, 2018, Kavanaugh was narrowly confirmed by the Senate. The Kavanaugh hearings raised the salience of the already simmering topic of sexual misconduct. A Gallup Poll from late October 2018 asked how important Kavanaugh’s recent confirmation would be for electoral decision-making: 62 percent of respondents reported that the confirmation would be “Extremely important” or “Very important” to their vote (Gallup Organization 2018). The Kavanaugh hearings—and presumably issues related to sexual misconduct—were on the minds of voters as they considered going to the polls that fall. We investigate the role of these unfolding events in mobilizing turnout in the 2018 midterm elections. The national dialogue surrounding sexism, given the 2016 campaign, the rise of the #MeToo movement, and the temporal proximity of the Kavanaugh hearings, made conditions ripe for sexist predispositions to influence voter turnout. Using a uniquely timed survey appended with validated vote, we provide two contributions. First, we advance the literature by theorizing that the link between sexism and voter turnout will depend critically, and in opposing ways, on partisanship. Second, in testing this theory, we connect sexist predispositions to political participation: specifically, validated turnout in the 2018 midterms. The Kavanaugh nomination was marked by rancorous partisan debate surrounding Blasey Ford’s allegations of sexual misconduct. The sharp partisan divide among elites provided clear messaging about how rank-and-file partisans should interpret and emotionally react to the allegations. We argue that this debate evoked anger among partisans and thus provided a unique case to leverage sexism into turnout. Rank-and-file Republicans witnessed Republican elites decrying the hearings as a witch hunt, in which an “innocent” man’s reputation was being tarnished by a “complaining” woman. Republicans also witnessed angry and emotional testimony from Kavanaugh and “a parade of alpha-male outrage” (Glasser 2018), including Republican Senators Lindsey Graham and John Cornyn. Cornyn even told Kavanaugh, “You’re right to be angry” (Ferris and Bresnahan 2018). Kavanaugh’s nomination reflected the preferences of the Republican president and the Republican Party; thus, the allegations, hearings, and related media coverage were likely viewed with anger by Republicans scoring high in sexism. Rank-and-file Democrats were predisposed to oppose any Republican nominee, but the sexual misconduct allegations spotlighted sharper and more emotional fault lines. Democratic elites expressed anger over the treatment of Blasey Ford and Kavanaugh’s confirmation. Additionally, after experiencing a full year of #MeToo revelations and two years of Trump’s presidency, the Kavanaugh hearings provided yet another example of Republican men mistreating women. Similar to how Trump’s 2016 accusation that Hillary Clinton played “the woman’s card” activated anger among those low in sexism (Cassese and Holman 2019), the Kavanaugh hearings and confirmation were likely viewed with anger by Democrats low in sexism. If the national conversation about sexual misconduct since 2016 instigated anger among Republicans scoring high in sexism and Democrats low in sexism, the 2018 midterms provided an opportunity to act on that emotion. According to appraisal theories of emotions, anger arises from a perception of an unfair state of the world accompanied by a clear attribution of blame (Smith and Ellsworth 1985). This anger appraisal is associated with an action tendency to retaliate or punish whoever is to blame for the unfair condition (Huddy, Feldman, and Cassese 2007), even when punishment is personally costly (Seip, Van Dijk, and Rotteveel 2014). Furthermore, anger drives political participation (e.g., Valentino et al. 2011). Thus, we hypothesize that in 2018, more sexist Republicans were more likely to turn out relative to less sexist Republicans, and less sexist Democrats were more likely to turn out relative to more sexist Democrats. That is, sexism’s effect on turnout depends upon partisanship: it increases turnout among Republicans and decreases turnout among Democrats. Modern Sexism, Party, and Turnout Our original dataset provides temporal leverage to test these expectations. In April 2018, YouGov collected online survey data from 2,102 respondents. The sample is a pooled sample consisting of 1,302 panelists from weeks 9 and 10 of the 2016 Cooperative Campaign Project and a fresh sample of 800 respondents fielded at the same time.1 Importantly, this timing preceded the October 2018 Kavanaugh hearings and the November 2018 midterms. Though some politicians faced sexual misconduct allegations between April and November 2018 (North et al. 2019), none received the volume of media or elite attention as Kavanaugh. The weighted sample is intended to be representative of the US general adult population. Respondents answered questions concerning the #MeToo movement and sexist predispositions, and YouGov appended their validated vote data from the 2012–2018 elections. Three items from the modern sexism scale (Swim et al. 1995) are used to assess levels of sexism. This scale taps a sense of resentment toward women who challenge gender inequality in American society (Swim et al. 1995).2 The #MeToo movement shone a spotlight on instances of abuses of power and on power dynamics between men and women writ large. The modern sexism scale conceptually resonates with the ongoing political events and #MeToo movement. In addition, the temporal stability of modern sexism (Archer and Kam 2021) makes it particularly advantageous for testing the effect of modern sexism across different elections. An additive index is based upon respondents’ strength of agreement/disagreement with the following: When women demand equality these days, they are actually seeking special favors. Women often miss out on good jobs because of discrimination. [reverse coded] Women who complain about harassment cause more problems than they solve. For all analyses, modern sexism is rescaled from 0 (low sexism) to 1(high sexism), with M = 0.36, s.d. = 0.27, and α = 0.76. Modern sexism correlates with a range of attitudes such as candidate evaluation and vote choice (e.g., McThomas and Tesler 2016; Simas and Bumgardner 2017; Godbole, Malvar, and Valian 2019). We extend existing work by using validated turnout as our main dependent variable. Studies of sexism’s effect on political participation are less prevalent than those studying attitudes, and the few cases we have found (Valentino, Wayne, and Oceno 2018; Cassese and Holman 2019) rely on experiments using participatory intentions rather than actual, validated participation. We focus on validated turnout, a particularly difficult case given its habitual and costly nature (e.g., Gerber, Green, and Shachar 2003). We first examine the mean levels of modern sexism among those who turned out and those who stayed home in the 2018 midterms. As table 1 shows, voters’ and nonvoters’ average levels of modern sexism are statistically indistinguishable. However, within each party, levels of sexism across those who did and did not vote in 2018 are statistically different. Democratic voters scored significantly lower on modern sexism compared with Democratic nonvoters (p < 0.001), and Republican voters scored significantly higher on modern sexism compared with Republican nonvoters (p < 0.012). These patterns provide initial proof of concept for the hypothesis. Table 1. Mean levels of modern sexism by turnout in 2018 . Abstained 2018 . Turned out 2018 . Differences by turnout, p-value . All Respondents (N = 2,102) 0.373 (0.011) 0.362 (0.010) ∼0.45 Democrats only (N = 965) 0.266 (0.017) 0.175 (0.009) <0.001 Pure Independents (N = 373) 0.400 (0.024) 0.400 (0.026) ∼0.99 Republicans only (N = 764) 0.498 (0.019) 0.553 (0.011) <0.012 . Abstained 2018 . Turned out 2018 . Differences by turnout, p-value . All Respondents (N = 2,102) 0.373 (0.011) 0.362 (0.010) ∼0.45 Democrats only (N = 965) 0.266 (0.017) 0.175 (0.009) <0.001 Pure Independents (N = 373) 0.400 (0.024) 0.400 (0.026) ∼0.99 Republicans only (N = 764) 0.498 (0.019) 0.553 (0.011) <0.012 Note.—Table entry is the mean with standard error in parentheses. Survey weights applied. Leaners are classified as partisans. Open in new tab Table 1. Mean levels of modern sexism by turnout in 2018 . Abstained 2018 . Turned out 2018 . Differences by turnout, p-value . All Respondents (N = 2,102) 0.373 (0.011) 0.362 (0.010) ∼0.45 Democrats only (N = 965) 0.266 (0.017) 0.175 (0.009) <0.001 Pure Independents (N = 373) 0.400 (0.024) 0.400 (0.026) ∼0.99 Republicans only (N = 764) 0.498 (0.019) 0.553 (0.011) <0.012 . Abstained 2018 . Turned out 2018 . Differences by turnout, p-value . All Respondents (N = 2,102) 0.373 (0.011) 0.362 (0.010) ∼0.45 Democrats only (N = 965) 0.266 (0.017) 0.175 (0.009) <0.001 Pure Independents (N = 373) 0.400 (0.024) 0.400 (0.026) ∼0.99 Republicans only (N = 764) 0.498 (0.019) 0.553 (0.011) <0.012 Note.—Table entry is the mean with standard error in parentheses. Survey weights applied. Leaners are classified as partisans. Open in new tab We next estimate a conditional change model with validated 2018 turnout as the dependent variable. The key covariates are modern sexism, party identification, and their interaction; validated turnout in 2014 (the immediately preceding midterms), demographics (gender, race, ethnicity, education, income, and age), and ideological identification are included as controls.3 Importantly, all survey items were measured in April 2018, seven months preceding the midterms, which protects our estimates against concerns about reverse causality. The results in column 1 of table 2 strongly support our expectations: the coefficient on the interaction term between modern sexism and partisanship is highly significant and sizable, as is the coefficient on modern sexism. For ease of interpretation, figure 1 depicts the predicted probability of turning out among Republicans and Democrats across levels of modern sexism. Histograms depict the in-sample distributions of modern sexism across parties. Democrats with lower levels of modern sexism were more likely to turn out than Democrats with higher levels of modern sexism, and the former outnumber the latter. Republicans with higher levels of modern sexism were more likely to turn out than Republicans with lower levels of modern sexism, and the former outnumber the latter. In short, the mobilizing tendencies of modern sexism align with the underlying distributions across parties. Figure 1. Open in new tabDownload slide Modern sexism, party identification, and turnout. Predicted probabilities with 83.5% confidence intervals. Weighted histograms by party below. Figure 1. Open in new tabDownload slide Modern sexism, party identification, and turnout. Predicted probabilities with 83.5% confidence intervals. Weighted histograms by party below. Table 2. Validated turnout as a function of modern sexism and party identification . Turnout 2018 [1] . Turnout 2016 [2] . Turnout 2018 [3] . Turnout 2018 [4] . Turnout 2014 [5] . Modern sexism x 1.57* 1.26* 1.16* 1.03† 0.24  Party ID (0.49) (0.62) (0.50) (0.53) (0.53) Modern sexism −0.79* −0.19 −0.69* −0.58† 0.16 (0.29) (0.39) (0.33) (0.33) (0.36) Party ID −0.54* −0.51† −0.34 −0.29 0.05 (0.22) (0.30) (0.23) (0.24) (0.29) Turnout 2014 1.86* 1.05* (0.09) (0.12) Turnout 2012 2.50* 2.45* (0.13) (0.12) Turnout 2016 2.06* 1.47* (0.10) (0.12) N 1,946 1,921 1,963 1,946 1,921 . Turnout 2018 [1] . Turnout 2016 [2] . Turnout 2018 [3] . Turnout 2018 [4] . Turnout 2014 [5] . Modern sexism x 1.57* 1.26* 1.16* 1.03† 0.24  Party ID (0.49) (0.62) (0.50) (0.53) (0.53) Modern sexism −0.79* −0.19 −0.69* −0.58† 0.16 (0.29) (0.39) (0.33) (0.33) (0.36) Party ID −0.54* −0.51† −0.34 −0.29 0.05 (0.22) (0.30) (0.23) (0.24) (0.29) Turnout 2014 1.86* 1.05* (0.09) (0.12) Turnout 2012 2.50* 2.45* (0.13) (0.12) Turnout 2016 2.06* 1.47* (0.10) (0.12) N 1,946 1,921 1,963 1,946 1,921 Note.—Table entry is the probit regression coefficient with standard errors in parentheses. Survey weights applied. All models also control for ideology, gender, race, ethnicity, education, income, and age. Full results appear in the Supplementary Material. †p < 0.10; *p < 0.05 Open in new tab Table 2. Validated turnout as a function of modern sexism and party identification . Turnout 2018 [1] . Turnout 2016 [2] . Turnout 2018 [3] . Turnout 2018 [4] . Turnout 2014 [5] . Modern sexism x 1.57* 1.26* 1.16* 1.03† 0.24  Party ID (0.49) (0.62) (0.50) (0.53) (0.53) Modern sexism −0.79* −0.19 −0.69* −0.58† 0.16 (0.29) (0.39) (0.33) (0.33) (0.36) Party ID −0.54* −0.51† −0.34 −0.29 0.05 (0.22) (0.30) (0.23) (0.24) (0.29) Turnout 2014 1.86* 1.05* (0.09) (0.12) Turnout 2012 2.50* 2.45* (0.13) (0.12) Turnout 2016 2.06* 1.47* (0.10) (0.12) N 1,946 1,921 1,963 1,946 1,921 . Turnout 2018 [1] . Turnout 2016 [2] . Turnout 2018 [3] . Turnout 2018 [4] . Turnout 2014 [5] . Modern sexism x 1.57* 1.26* 1.16* 1.03† 0.24  Party ID (0.49) (0.62) (0.50) (0.53) (0.53) Modern sexism −0.79* −0.19 −0.69* −0.58† 0.16 (0.29) (0.39) (0.33) (0.33) (0.36) Party ID −0.54* −0.51† −0.34 −0.29 0.05 (0.22) (0.30) (0.23) (0.24) (0.29) Turnout 2014 1.86* 1.05* (0.09) (0.12) Turnout 2012 2.50* 2.45* (0.13) (0.12) Turnout 2016 2.06* 1.47* (0.10) (0.12) N 1,946 1,921 1,963 1,946 1,921 Note.—Table entry is the probit regression coefficient with standard errors in parentheses. Survey weights applied. All models also control for ideology, gender, race, ethnicity, education, income, and age. Full results appear in the Supplementary Material. †p < 0.10; *p < 0.05 Open in new tab Though our instrumentation is limited, we can test for whether modern sexism is merely proxying other considerations by adding an interaction between ideology and partisanship. When we do so, the results for modern sexism and its interaction with party identification are substantively and statistically unchanged, assuaging concerns that modern sexism is proxying for a generalized conservative outlook (full results with predicted probability graphs appear in the Supplementary Material). The 2018 Midterms in Context We have focused our attention on the 2018 midterms, as that election clearly provided distinct paths for mapping sexism to turnout across partisans. What about the 2016 general election? Existing work suggests that Trump’s sexist rhetoric, allegations of his past sexual misconduct, and Clinton’s gender activated sexism in 2016 vote choice unlike before (e.g., Schaffner, MacWilliams, and Nteta 2018; Cassese and Barnes 2019). We apply the same model to validated vote in 2016, controlling for 2012 turnout (the immediately preceding presidential election) and the same covariates used in predicting 2018 turnout.4 In column 2 of table 2, we again see a significant interaction between modern sexism and partisanship, corresponding with the expectation that modern sexism has differential implications for turnout across partisans. However, these results produce a slightly different pattern: while modern sexism significantly mobilizes Republicans in 2016, it has a negative but insignificant effect among (strong) Democrats in 2016.5 The second panel of figure 1 illustrates these patterns. The activation of modern sexism in the 2016 campaign disproportionately advantaged Trump in mobilizing voter turnout, consistent with existing literature (e.g., Valentino, Wayne, and Oceno 2018; Cassese and Barnes 2019). Having established that modern sexism was partly “baked into” turnout in 2016, we reconsider the robustness of the results for 2018. These results appear in models [3] and [4] in table 2, where we substitute 2016 turnout for 2014 turnout [3] and where we include turnout in both elections [4]. Both models reinforce the previous findings: modern sexism and party identification interact significantly, and modern sexism is significant on its own. Taken together, these analyses consistently find that increases in modern sexism mobilize turnout among Republicans and decreases in modern sexism mobilize turnout among Democrats. The 2014 election provides a placebo test to assess whether this pattern is epiphenomenal. This election was dominated by the economy, health care, and foreign policy—not issues related to gender or sexual misconduct. When we model validated turnout in 2014, we find no evidence that modern sexism had any role in affecting turnout across parties. The predicted probabilities for 2014 in figure 1 showcase these flat lines. Conclusions Midterm elections have historically been less salient affairs, but 2018 represented an anomaly with the highest midterm turnout rate in over 50 years (Domonoske 2018). Exit polls pointed to longstanding concerns such as health care, immigration, and the economy as key ingredients of people’s votes. However, our evidence suggests that the #MeToo movement and the Kavanaugh hearings, which occurred in close temporal proximity to the midterms, not only amplified an ongoing conversation, but also mobilized political engagement among voters of both parties. Our theory and analyses highlight the critical importance of considering the conditional nature of sexism’s effect on turnout. Even if sexism does not, in the aggregate, change average levels of turnout, sexism can mobilize and demobilize potential voters in countervailing ways.6 Although modern sexism is a stable (Archer and Kam 2021), system-justifying belief (Jost and Kay 2005), its connections to politics will depend upon the degree to which elites frame and potential voters understand elections through this lens (Cassese and Holman 2019). Modern sexism is now baked into the fault lines of the major two-party system. Our theory will likely apply when political debates around sexual misconduct align with the parties’ fault lines and anger is the predominant emotion. These would be cases in which a Republican is accused of sexual misconduct and anger arises on both sides. Our theory might not apply when these conditions—which are often connected—are not met. For instance, the Democratic rank and file might have felt angry about the behavior of Democratic elites accused of sexual misconduct such as John Conyers and Al Franken. However, Democratic Party leaders acted quickly to pressure these men out of office, likely defusing any anger. In contrast, during the 2020 presidential campaign, then-Democratic candidate Joe Biden faced sexual assault allegations from former staffer Tara Reade. Though Democratic elites stated that Reade should be heard, many also stood by Biden in questioning her claims. Thus, instead of anger, Democratic voters low in sexism may have felt uncertainty, ambivalence, and perhaps disgust—reactions likely to de-mobilize rather than mobilize. While Republican elites could have used the Reade accusations to attack Democrats, they would also have needed to confront the allegations against Trump, who himself stated that Biden should “just go out and fight it” (Navarro, Tin, and Watson. 2020). Thus, Republicans scoring high in sexism were unlikely to feel angered by the allegations against Biden; instead, they might have experienced schadenfreude, disgust at Democrats’ perceived hypocrisy, or ambivalence given the allegations against Trump—emotions that would not necessarily have mobilized turnout. The long-term effects of the #MeToo movement and Kavanaugh hearings are difficult to anticipate. The conditions that amplify the conditional effect of sexism on turnout might quickly recede without long-lasting change: many noted the parallels between the Thomas-Hill hearings of 1992 and the Kavanaugh-Blasey Ford hearings three decades later. The sound and fury of the #MeToo movement and Kavanaugh hearings may be eclipsed by the novel coronavirus pandemic, historic economic disrepair, and massive protests against racial inequality and police brutality. On the other hand, the #MeToo movement and Kavanaugh hearings have been credited with bringing sexual misconduct to the forefront of national conversations, ushering in policy change, and altering the gender composition of the House (e.g., Zanona 2018). Thus, these new voices in power may continue to elevate discourse around issues of sexual misconduct and gender inequities, in conjunction with other movements and issues, underscoring the legacy of the electoral implications of these events as well as their political and policy consequences. Data Availability Statement REPLICATION DATA AND DOCUMENTATION are available at https://doi.org/10.7910/DVN/ASVMVB. Supplementary Material SUPPLEMENTARY MATERIAL may be found in the online version of this article: https://doi.org/10.1093/poq/nfab005. Cindy D. Kam holds the William R. Kenan, Jr. Chair in the Department of Political Science at Vanderbilt University, Nashville, TN, USA. Allison M. N. Archer is an assistant professor in the Department of Political Science and Valenti School of Communication at the University of Houston, Houston, TX, USA. The authors thank Allison Anoll, Bruce Oppenheimer, and John Sides for invaluable advice. Data collection was supported by Vanderbilt University. Footnotes 1 For the panelists, the AAPOR Cooperation Rate (COOP3) was 78.45 percent, and it was 55.67 percent for the fresh cross-section. No material differences emerge across the two groups. 2 Existing work has also employed hostile and benevolent sexism. Modern sexism is conceptually similar to hostile sexism, as both reflect resentment toward women challenging societal male dominance; the two positively correlate (Glick and Fiske 1996). Benevolent sexism reflects positive, though paternalistic and traditionalist, views of women. In the context of #MeToo and the Kavanaugh hearings, hostile sexists would resent women who allege harassment (and challenge male dominance) but benevolent sexists would react negatively to men seen as preying on women’s vulnerability (following Barnes, Beaulieu, and Saxton 2020). While intriguing, examination of benevolent sexism’s effects in the #MeToo era is complicated by Trump himself using benevolent sexism as cover against allegations he has faced (e.g., Viebeck 2015). 3 Partisan identification is measured using a seven-point scale ranging from “Strong Democrat” (0) to “Strong Republican” (1). Previous turnout is a dummy indicating validated vote in the respective election. Ideology is measured on a five-point scale from “Very liberal” (0) to “Very conservative” (1). Female, Black, and Latino are dummy indicator variables. Education is measured on a five-point scale from “less than high school” (0) to “post-BA” (1). Income is split into four quartiles; the highest category is the suppressed baseline. Income refused is a dummy for those who refused to report income. Age is captured by dummy variables, with those 18–30 as the baseline. 4 Although modern sexism is measured in 2018, test-retest Wiley-corrected correlations are extremely high from 2016 to 2018 (>0.9), and aggregate, average levels of modern sexism are extraordinarily stable across the last two decades (Archer and Kam 2021). The 2016 analyses omit the 25 respondents too young to vote in 2012; estimates for 2018 are unchanged when we rerun the model without this group. 5 The effect of modern sexism among Strong Democrats is larger in 2018 than 2016 at p∼0.105 (one-tailed). 6 Further research on how race and ethnicity might interplay in this relationship is certainly warranted given the important complexities at the interface of power, sexism, and race/ethnicity in American society. The women’s movement and feminism have historically represented the concerns of “white, middle-class women” (Simien and Clawson 2004, p. 795). The perspectives of people of color, especially those who are Democrats, demand extended theorizing and analyses that are outside the bounds of the current research note. References Archer Allison M. N. , Kam Cindy D.. 2021 . “Modern Sexism in Modern Times: Public Opinion in the #MeToo Era .” Public Opinion Quarterly 84 . doi.org/10.1093/poq/nfaa058. Google Scholar OpenURL Placeholder Text WorldCat Barnes Tiffany D. , Beaulieu Emily, Saxton Gregory W.. 2020 . “Sex and Corruption: How Sexism Shapes Voters’ Responses to Scandal .” Politics, Groups, and Identities 8 : 103 – 21 . Google Scholar OpenURL Placeholder Text WorldCat Cassese Erin C. , Barnes Tiffany D.. 2019 . “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 41 : 677 – 700 . Google Scholar OpenURL Placeholder Text WorldCat Cassese Erin C. , Holman Mirya R.. 2019 . “Playing the Woman Card: Ambivalent Sexism in the 2016 U.S. Presidential Race .” Political Psychology 40 : 55 – 74 . Google Scholar OpenURL Placeholder Text WorldCat Domonoske Camila. 2018 . “A Boatload of Ballots: Midterm Voter Turnout Hit 50-Year High.” NPR, November 8. Available at https://www.npr.org/2018/11/08/665197690/a-boatload-of-ballots-midterm-voter-turnout-hit-50-year-high. Ferris Sarah , Bresnahan John. 2018 . “Graham Erupts in Anger at Kavanaugh Hearing.” Politico, September 27. Available at https://www.politico.com/story/2018/09/27/lindsey-graham-kavanaugh-hearing-849479. Gallup Organization . 2018 . Gallup Poll, Oct 2018. Gallup Organization [producer] . Cornell University, Ithaca, NY : Roper Center for Public Opinion Research, iPoll [distributor]. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Gerber Alan S. , Green Donald P., Shachar Ron. 2003 . “Voting May be Habit-Forming: Evidence from a Randomized Field Experiment .” American Journal of Political Science 47 : 540 – 50 . Google Scholar OpenURL Placeholder Text WorldCat Glasser Susan B. 2018 . “‘If They Can, They Will’: The Ford-Kavanaugh Hearing and the Angry Politics of Now.” The New Yorker, September 27. Available at https://www.newyorker.com/news/letter-from-trumps-washington/if-they-can-they-will-the-ford-kavanaugh-hearing-and-the-angry-politics-of-now. Glick Peter , Fiske Susan T.. 1996 . “The Ambivalent Sexism Inventory: Differentiating Hostile and Benevolent Sexism .” Journal of Personality and Social Psychology 70 : 491 – 512 . Google Scholar OpenURL Placeholder Text WorldCat Godbole Maya A. , Malvar Noelle A., Valian Virginia V.. 2019 . “Gender, Modern Sexism, and the 2016 Election .” Politics, Groups and Identities 7 : 700 –7 12 . Google Scholar OpenURL Placeholder Text WorldCat Huddy Leonie , Stanley Feldman, Erin Cassese. 2007 . “On the Distinct Political Effects of Anxiety and Anger.” In The Affect Effect: Dynamics of Emotion in Political Thinking and Behavior , ed. Russell Neuman W., George E. Marcus, Michael MacKuen, Ann Crigler. Chicago : University of Chicago Press , 202 – 30 . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Jost John T. , Kay Aaron C.. 2005 . “Exposure to Benevolent Sexism and Complementary Gender Stereotypes: Consequences for Specific and Diffuse Forms of System Justification .” Journal of Personality and Social Psychology 88 : 498 – 509 . Google Scholar OpenURL Placeholder Text WorldCat McThomas Mary , Tesler Michael. 2016 . “The Growing Influence of Gender Attitudes on Public Support for Hillary Clinton, 2008–2012 .” Politics & Gender 12 : 28 – 49 . Google Scholar OpenURL Placeholder Text WorldCat Navarro Aaron , Alexander Tin, Eleanor Watson. 2020 . “GOP Groups Seize on Tara Reade Allegations to Attack Democrats.” Available at https://www.cbsnews.com/news/republican-groups-tara-reade-allegations-attack-democrats/. North Anna , Grady Constance, McGann Laura, Romano Aja. 2019 . “A List of People Accused of Sexual Harassment, Misconduct, or Assault.” Vox. https://www.vox.com/a/sexual-harassment-assault-allegations-list/mel-watt. Schaffner Brian F. , MacWilliams Matthew, Nteta Tatishe. 2018 . “Understanding White Polarization in the 2016 Vote for President: The Sobering Role of Racism and Sexism .” Political Science Quarterly 133 : 9 – 34 . Google Scholar OpenURL Placeholder Text WorldCat Seip Elise C. , Van Dijk Wilco W., Rotteveel Mark. 2014 . “Anger Motivates Costly Punishment of Unfair Behavior .” Motivation and Emotion 38 : 578 – 88 . Google Scholar OpenURL Placeholder Text WorldCat Simas Elizabeth N. , Bumgardner Marcia. 2017 . "Modern Sexism and the 2012 US Presidential Election: Reassessing the Casualties of the ‘War on Women .’ " Politics & Gender 13 : 359 – 378 . Google Scholar OpenURL Placeholder Text WorldCat Simien Evelyn M. , Clawson Rosalee A.. 2004 . “The Intersection of Race and Gender: An Examination of Black Feminist Consciousness, Race Consciousness, and Policy Attitudes .” Social Science Quarterly 85 : 793 – 810 . Google Scholar OpenURL Placeholder Text WorldCat Smith Craig A. , Ellsworth Phoebe C.. 1985 . “Patterns of Cognitive Appraisal in Emotion .” Journal of Personality and Social Psychology 48 : 813 – 38 . Google Scholar OpenURL Placeholder Text WorldCat Swim Janet K. , Aikin Kathryn J., Hall Wayne S., Hunter Barbara A.. 1995 . “Sexism and Racism: Old-Fashioned and Modern Prejudices .” Journal of Personality and Social Psychology 68 : 199 – 214 . Google Scholar OpenURL Placeholder Text WorldCat Valentino Nicholas A. , Brader Ted, Groenendyk Eric W., Gregorowicz Krysha, Hutchings Vincent L.. 2011 . “Election Night’s Alright for Fighting .” Journal of Politics 73 : 156 – 70 . Google Scholar OpenURL Placeholder Text WorldCat Valentino Nicholas A. , Wayne Carly, Oceno Marzia. 2018 . “Mobilizing Sexism: The Interaction of Emotion and Gender Attitudes in the 2016 US Presidential Election .” Public Opinion Quarterly 82 : 213 – 35 . Google Scholar OpenURL Placeholder Text WorldCat Viebeck Elise. 2015 . “Trump Defends Record on Women’s Issues: ‘I Cherish Women. I Want to Help Women.’” Washington Post, August 9. Available at https://www.washingtonpost.com/news/post-politics/wp/2015/08/09/donald-trump-i-cherish-women/. Zanona Melanie. 2018 . “Women Wield Sizable Power in ‘MeToo’ Midterms.” The Hill, September 12. Available at: https://thehill.com/homenews/house/406183-women-wield-sizable-power-in-me-too-midterms. © The Author(s) 2021. Published by Oxford University Press on behalf of American Association for Public Opinion Research. All rights reserved. For permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
TI - MOBILIZING AND DEMOBILIZINGMODERN SEXISM AND TURNOUT IN THE #METOO ERA
JF - Public Opinion Quarterly
DO - 10.1093/poq/nfab005
DA - 2021-07-01
UR - https://www.deepdyve.com/lp/oxford-university-press/mobilizing-and-demobilizingmodern-sexism-and-turnout-in-the-metoo-era-tR6RPHTdNl
SP - 1
EP - 1
VL - Advance Article
IS - 
DP - DeepDyve
ER -