We test if candidates’ facial competence and dominance predict their ballot positions. That is, we test if across the 257 candidates from the main Danish parties facial competence positively predicts candidates’ chances of being positioned in the top of the ballot, and if facial dominance is a relatively more positive predictor of a top ballot position for conservative than for liberal candidates. Table 1 reports the full regression models for predictions of ballot position as measured by whether a candidate appears in the top 20 percent of the ballot or not. Model 1 estimates the main effect of facial competence and the interaction between facial dominance and candidates’ ideology. Model 2 further includes an interaction between facial competence and ideology. Across all candidates, facial competence constitutes a positive predictor of candidates’ nomination success (Model 1: b = 2.41, p = 0.001), and this effect is not moderated by candidates’ ideology (Model 2: b = -0.51, p = 0.732).9 The results also support that facial dominance is a relatively more positive asset for conservative candidates than for their liberal counterparts since the interaction between facial dominance and candidate ideology is negative and statistically significant (Model 1: b = 5.79, p = 0.001).10 Table 1 provides the full models from these analyses.
‘Table 1 about here’
To provide an in-depth interpretation of the results, we report predicted probabilities for being positioned in the top 20 percent of the ballot for candidates high and low in facial competence and facial dominance, respectively. Moreover, we report predicted probabilities for facial dominance for conservative and liberal candidates separately due to the interactive nature of the facial dominance prediction. We follow the observed values approach holding all other variables than the primary independent variable (facial competence or facial dominance) at their actual observed values (Hanmer & Kalkan, 2013). Finally, to represent a candidate high or low on either facial competence or facial dominance, we calculate predicted probabilities for the 10th (low) and 90th (high) percentiles of the distributions on either facial competence or facial dominance.
Starting with facial competence we find that a candidate positioned at the 10th percentile of the facial competence distribution has a predicted probability of 11 percent of being positioned among the top 20 percent on her/his party’s ballot. In contrast, a candidate high in facial competence (positioned at the 90th percentile) doubles the chance of being allocated a similar top ballot position with a predicted probability of 23 percent. That is, just as previous studies find that competent looking candidates receive more votes from the voters on Election Day, this result shows that also members of political parties—presumably high in political interest and knowledge—are affected by candidates’ facial appearance as they nominate competent looking candidates closer to the top of the ballots. Below, Figure 1 illustrates this result graphically.
‘Figure 1 abut here’
Turning to the role played by facial dominance in nomination success, we report predicted probabilities for liberal and conservative candidates high and low in facial dominance, respectively. From Table 1 we already saw that facial dominance plays a significantly different role depending on the ideology of the candidate. Interestingly, we find that among conservative candidates facial dominance does not seem to affect nomination success. A candidate low in facial dominance (at the 10th percentile) faces a chance of 19 percent for a position in the upper 20 percent of the ballot, while a candidate high in facial dominance (at the 90th percentile) has a chance of 22 percent. Whereas facial dominance seemingly does not matter for nomination success among conservative candidates, we find a clear relationship between facial dominance and nomination success on the liberal side of the ideological spectrum. Here a candidate low in facial dominance (at the 10th percentile) has a 22 percent chance of a top ballot position, while candidates high in facial dominance (at the 90th percentile) correspondingly only holds a 5 percent chance of the same top ballot position. That is, whereas we replicate the finding from studies on candidates’ electoral success that facial dominance interacts with candidate ideology (see Laustsen & Petersen, 2016), we find no positive effect of looking dominant on nomination success among conservative candidates. What drives the interaction between facial dominance and ideology on nomination success is instead the negative consequences of looking dominant for the liberal candidates (we return to this in the discussion section). Figure 2 reports the predicted probabilities for candidates high and low in facial dominance from liberal and conservative parties, respectively.
‘Figure 2 about here’
In sum these results support the “biosocial leadership categorization model”—as presented by Spisak et al. (2012b)—in which leader evaluation follows a two-step procedure first related to general leader competence, and second related to task specific leadership ability. Specifically, facial competence appears to influence evaluations of context-general leadership ability while facial dominance is factored into context-specific evaluations. Since perceptions of the social world is colored by ideological outlook (see also section “Modern Elections and Evolved Followership Psychology”), partisans on opposing ends of the ideological spectrum value facial dominance differently. Particularly, dominant looking liberal candidates stand a worse chance than their non-dominant looking colleagues in receiving a top ballot position. However, although the relationship is in the expected direction, we do not find that conservative partisans significantly assign more dominant looking candidates to a top ballot position.11
Finally, the reported results replicate across a series of alternative estimation procedures. We substituted the “top 20 percent measure” of nomination success with other measures such as “top 25 percent”, “top 30 percent”, “top 40 percent” and “top 50 percent”. We also employed a continuous relative measure of nomination success by dividing ballot position by the total number of candidates nominated within the party. Across these different operationalizations of nomination success facial competence constitutes a robust predictor of nomination success across all candidates. Likewise, facial dominance in all of the alternative models reduces liberal candidates’ chances of being nominated in the top of the ballot (see Online Supporting Information S.I.3-S.I.7 for full models and graphical illustrations of predicted probabilities for these alternative operationalizations of nomination success)12. That is, regardless of the employed operationalization of nomination success—spanning distinctions between the top 20 percent and the lower 80 percent to a split between the top and bottom halves of the ballot and a continuous measure—the results remain unchanged: Facial competence and facial dominance predict candidates’ success in party internal nomination contests following a pattern parallel to results obtained in prior studies investigating candidates’ electoral success in real-world electoral contests. Below we discuss the normative consequences of these findings in relation to democratic ideals about informed and deliberate decision-making processes among the public, and we stress the most pressing questions for future research on appearance-based voting.
In this article we have extended previous findings of associations between candidates’ facial appearances and their electoral success by investigating how appearance also relates to party internal nominations of candidates. In parallel to previous findings that ordinary voters use candidates’ facial appearances as cues to leader abilities, we find that naïve respondents’ ratings of candidates’ faces also relate significantly to decisions taken in intra party nomination processes. Our findings both replicate and extend previous research on face-based voting, add insights to evolutionary models of leadership and nuance our understanding of the relationship between candidates’ facial appearances and their success as candidates.
Specifically, we found that Danish local partisans regardless of their ideological leaning tend to assign competent looking candidates to the top of the ballot. Moreover, we also replicate the interaction between facial dominance and candidate ideology previously reported for the voter level and in survey experiments (Laustsen & Petersen, 2015, 2016). That is, not only were all partisans in these Danish municipalities putting a premium on a competent face; in line with evolutionary models of leadership and followership they also differed in preferences for a dominant face based on their ideological affiliation: Liberal partisans positioned dominant looking candidates significantly lower on the ballot than their conservative counterparts.
These findings are important for several reasons. First, our findings replicate findings that have previously only been obtained among lay-voters. Hence, our results show that not only lay-voters but also partisans—who we should expect to be more politically interested and knowledgeable than the average citizen—are attracted to candidates based on their facial appearances. In contrast to the argument that facial features influence electoral decisions “primarily among less knowledgeable individuals” (Lenz & Lawson, 2012: 574), partisans follow the same patterns in candidate face preferences as ordinary citizens. The similarity of our findings to prior results from experiments and observational studies is important because it underlines the universality of the psychology underlying leader preferences across followers high (partisans) and low (most ordinary voters) in political sophistication, knowledge and interest. The political importance of appearance-related cues might not be part of a story about an ill-informed and uninterested electorate after all. Instead, we suggest that the appearance effect of candidates’ faces reflects that modern citizens’ preferences for political candidates are (at least partly) regulated by a sophisticated, evolved followership psychology.
Second, evolutionary leadership scholars have suggested that an evolved followership psychology regulates leader preferences and that it is informed by two distinct evaluation processes: Evaluations of general leadership ability and evaluations of problem-specific leadership ability. According to this theory, a follower initially sorts out the potential leaders from non-leaders, and next from this pool of potential leaders the follower seeks out the individual who seems best capable of solving the problem experienced as most salient to the follower (Spisak et al., 2012a; Bøggild & Laustsen, 2016; see also Lord et al., 1984). Our results provide novel support for this two-step model of followership decisions and leader preferences. Consistent with the existence of an initial overall evaluation, we found that more competent-looking candidates – regardless of ideological affiliation – received better ballot positions. Consistent with the existence of a subsequent problem-specific evaluation, we found that ideological affiliation—most likely because conservatives tend to perceive the social world as more conflict-ridden and competitive than liberals (Jost et al., 2003; Hibbing et al. 2013; Duckitt & Sibley 2010)—shapes the effect of dominant looks such that dominant looking candidates received a relative better ballot position among conservatives than liberals (see also Laustsen & Petersen 2015; Laustsen 2016; Barker et al. 2006). To the best of our knowledge these findings constitute the first empirical test and support of the proposed psychological system of adaptive followership based on data from intra-party nomination processes.13
One potential counter argument against this interpretation is that the associations between facial appearance and candidates’ success—both in terms of electoral and nomination support—could reflect that the members of the party organizations themselves recognize the electoral benefits of promoting candidates with particular appearances because they have either an explicit or an implicit sense about which type of candidate (and appearance) their constituency prefers. Even if this alternative interpretation is valid, the present findings would still suggest that that modern-day party members factor in ancestrally relevant appearances and poses when promoting candidates for modern leader positions. That said, we think that two observations speak against this interpretation. First, the data analyzed here was collected from low-salience Danish municipal elections in 2009 in which campaigns—according to the best of our knowledge—are much more likely to focus on classic campaign objectives such as getting a candidate’s personal message out, meeting the voters and perhaps participate in debates against other candidates (although most likely only a handful of the most politically interested voters would show up in the audience). In addition, a report based on self-reported campaign strategies from 2,083 of the candidates who ran in the 2009 Danish local elections does not mention visual appearance or character traits a single time (Hansen & Hoff, 2010)14. Second, members of the party organizations could in theory be aware of central findings linking candidates’ facial competence to electoral success (cf. Todorov et al., 2005) but it seems less plausible that they should have known about the ideological difference in the role played by facial dominance since these relationships were not explored and published until years after the election (cf. Laustsen & Petersen 2015, 2016). Third, if party organizations’ strategic nominations were causing the observed pattern, it seems as a missed opportunity for conservative parties to not position the most dominant looking candidates at the top ballot positions. Based on this, we think it is most likely that the results reflect that both partisans’ and voters’ candidate preferences are shaped by an evolved psychology of followership.
One difference between the present findings obtained among party members and past findings obtained among lay individuals should be noted. Studies on lay individuals often report that conservatives have a positive preference for dominant leaders (e.g., Laustsen & Petersen, 2016). In contrast, the differences we found among liberal and conservative party members were driven by liberal members: they showed a negative preference for dominant leaders. A potential explanation for this difference in results could relate to the fact that within small local party organizations, members are much closer to the candidates than the average voter. They will, for example, participate in small meetings and group discussions together. Because dominant individuals are seen as exploitive and untrustworthy, previous research has found that people often shun them in closer relationships (see Laustsen & Petersen, 2015). Such considerations could off-set the often-found positive preference for dominant leaders among conservative party members. Given this, future studies could address whether preferences for dominant leaders are shaped by the proximity to the leader.
We also want to highlight a number of other pressing questions for future studies to investigate. Most importantly, it remains unclear what is actually perceived as a competent face and, consequently, causes the relationship between naïve respondents’ ratings of political candidates’ faces and the success experienced by these candidates on Election Day. While scholars have sought to disentangle the effect of looking competent from so-called “halo” (or spillover) effects related to attractiveness, results so far remain mixed. Some studies find that facial competence outperforms attractiveness (e.g. Todorov et al., 2005; Olivola & Todorov, 2010), some studies find attractiveness to be a stronger predictor than competence (e.g. Berggren et al., 2010; Verhulst et al., 2010) and still others find that facial competence and attractiveness exert distinct effects on electoral success (e.g. Laustsen, 2014). In addition, Olivola & Todorov (2010: pp. 97-100) have tried to link perceptions of competence to other face-based trait perceptions. Yet, still it remains unclear what more specific traits such inferences are potentially based on.
Relatedly, future research should also strive to obtain measurements of the exact—and strictly non-controllable—facial metrics of politicians that are reflected in trait perceptions of both facial competence and dominance. With respect to facial dominance, studies outside the realm of politics relate the facial width-to-height ratio (fWHR) to behavioral measures of aggression and untrustworthy behavior (see e.g. Carré, McCormick & Mondloch, 2009; Stirrat & Perrett, 2010) suggesting that this measure might also be relevant to integrate in future studies on face-based trait inferences in politics.
Finally, we believe that one of the major questions arising from both the present manuscript and the past literature is whether or not inferences from candidates’ faces tell “something real” about the candidates or if it only reflects invalid and shallow judgments. One way future research might address this question is to investigate how trait inferences from candidate faces relate to other outcome measures than candidates’ success in elections and, especially, post-election outcomes. For instance, future work could explore if face-based trait inferences relate to candidates’ policy positions, their behavior in debates, or in other types of work in parliament. In this way, future research would be able to provide additional traction on the question of whether the relationships between candidates’ physical appearance and their electoral success are antithetical to democracy or not. Previous research have proceed from different premises in relation to whether voters vote on "something real" when voting on the basis of facial traits (e.g., Lenz & Lawson, 2011; Laustsen & Petersen 2017). However, the here observed similarity between intra-party nominations (the results presented in this article) and voter preferences (the results presented in previous studies) suggests that voters’ preferences for physiological features in candidates could be reflections of an evolved followership psychology and, hence, increases the plausibility that differences in candidate appearance are associated with outcomes beyond electoral success. This suggests that when voters make decisions on this basis they might not necessarily act in an ill-informed and uninterested manner. Instead, they could be actively trying to identify the best leader to solve the problems facing society. At the same time, it is important to note that the evolutionary perspective opens for two arguments for why facial traits might not track actual ability in modern leaders. First, given differences between ancestral and modern environments, different traits might lead to leader competence then and now (cf. van Vugt & Ahuja, 2010). Second, while evolved followership might be functionally calibrated to track the personalities of potential leaders, facial traits are presumably not the most valid cues to personality (see Laustsen & Petersen, 2017: pp. 3-4) and it is even a possibility that reliance on facial traits in personality assessment reflects a non-adaptive by-product of mechanisms designed to read expressions of emotions in the face (e.g., Olivola & Todorov, 2010: p. 86). In this way, addressing the political implications of the relationship between candidate appearance and electoral success opens for a number of interesting questions both theoretically, empirically and normatively.
The present manuscript provides novel insights about the role played by candidate appearance in real-world elections. In short, we have shown how modern political behavior might be explained by evolutionary psychological theories integrating insights and principles from across the natural and social sciences (see also Fowler & Schreiber, 2008; Hatemi & McDermott, 2011; Oxley et al., 2008; Petersen et al., 2013). Specifically, the results provided here support the notion of an adaptive psychological system of followership that—according to our results—could be regulating preferences for political candidates among even highly interested political partisans.
Achen, C. H., & Bartels, L. M. (2004). Blind retrospection: Electoral responses to drought, flu, and shark attacks, unpublished manuscript. Princeton University.
Armstrong, J. S., Green, K. C., Jones Jr., R. J. J., & Wright, M. J. (2010). Predicting Elections from Politicians’ Faces. International Journal of Public Opinion Research, 22(4), 511-522.
Ballew, C.C., & Todorov, A.. (2007). Predicting political elections from rapid and unreflective face judgments. Proceedings of the National Academy of Sciences,104, 17948-17953.
Banducci, S., Karp, J. A., Thrasher, M., & Rallings, C. (2008). Ballot photographs as cues in low-information elections. Political Psychology, 29(6), 903‒917.
Barker, D. C., Lawrence, A. B., & Tavits, M. (2006). Partisanship and the dynamics of “candidate centered politics” in American presidential elections. Electoral Studies, 25(3), 599-610.
Berggren, N., Jordahl, H., & Poutvaara, P. (2010). The looks of a winner: beauty and electoral success. Journal of Public Economics,94(1–2), 8–15.
Berggren, N., Jordahl, H., & Poutvaara, P. (2017). The right look: Conservative politicians look better and voters reward it. Journal of Public Economics,146, 79-86.
Blom-Hansen, J., Elklit, J., Serritzlew, S., & Villadsen, L.R. (2016). Ballot position and election results: Evidence from a natural experiment. Electoral Studies, 44, 172-183.
Boehm, C. (2000). Conflict and the evolution of social control. Journal of Consciousness Studies,7(1–2), 79–101.
Brusattin, L. (2011). Candidate Visual Appearance as a Shortcut for Both Sophisticated and Unsophisticated Voters: Evidence from a Spanish Online Study. International Journal of Public Opinion Research,24(1), 1-20.
Bøggild, T., & Laustsen, L. (2016). An Intra-Group Perspective on Leader Preferences: Different Risks of Exploitation Shape Preferences for Leader Facial Dominance. The Leadership Quarterly, 27(6), 820-837.
Carré, J. M., McCormick, C. M., & Mondloch, C. J. (2009). Facial Structure Is a Reliable Cue of Aggressive Behavior. Psychological Science, 20, 1194-1198.
Cogsdill, E. J., Todorov, A., Spelke, E. S., & Banaji, M. (2014). Inferring Character From Faces: A Developmental Study. Psychological Science, 25(5), 1132-1139.
Cosmides, L., & Tooby, J. (1992). Cognitive adaptations for social exchange. In J. Barkow, L. Cosmides, & J. Tooby (Eds.), The adapted mind (pp. 163–228). Oxford: Oxford University Press.
Duckitt, J., & Sibley, C. G. (2010). Personality, ideology, prejudice, and politics: a dual‐process motivational model. Journal of Personality, 78(6), 1861-1894.
Elklit, J., (2013). Valgsystemerne. In: Christensen, J.G., Elklit, J. (Eds.), Det demokratiske System. Hans Reitzel, Copenhagen, pp. 29-62.
Fowler, J. H., & Schreiber, D. (2008). Biology, politics, and the emerging science of human nature. Science, 322(5903), 912-914.
Hall, C.C., Goren, A., Chaiken, S. & Todorov, A. (2009). Shallow cues with deep effects: Trait judgments from faces and voting decisions. In E. Borgida, J.L. Sullivan, & C.M. Federico (Eds.), The political psychology of democratic citizenship. pp. 73–99. New York: Oxford University Press.
Hanmer, M. J., & Kalkan, K. O. (2013). Behind the Curve: Clarifying the Best Approach to Calculating Predicted Probabilities and Marginal Effects from Limited Dependent Variable Models. American Journal of Political Science, 57(1), 263-277.
Hansen, K. M., & Hoff, J. (2010). Den kommunale valgkampagne anno 2009. En kommenteret tabelrapport [The 2009 municipality election campaign. Comments and table analyses]. (Working Paper). Copenhagen, Denmark: Department of Political Science, University of Copenhagen
Hatemi, P., & McDermott, R. (2011). Man is by nature a political animal. Chicago: University of Chicago Press.
Healy, A.J., Malhotra, N., & Mo, C. H. (2010). Irrelevant events affect voters’ evaluations of government performance. Proceedings of the National Academy of Sciences, 107(29), 12,804‒12,809.
Hibbing, J. R. & Alford, J. R. (2004). Accepting Authoritative Decisions: Humans as Wary Cooperators, American Journal of Political Science,48(1), 62-76.
Hibbing, J. R., Smith, K. B., & Alford, J. R. (2013). Predisposed. New York: Routledge.
Ho, D. E., & Imai, K. (2008). Estimating Causal Effects of Ballot Order from a Randomized Natural Experiment – The California Alphabet Lottery, 1978-2002. Public Opinion Quarterly, 72(2), 216-240.
Hoebel, A. E. (1954). The law of primitive man. Harvard, MA: Atheneum.
Jacobson, G. (1980). Money in congressional elections. New Haven, CT: Yale University Press.
Jost, J. T., Glaser, J., Kruglanski, A. W., & Sulloway, F. J. (2003). Political Conservatism as Motivated Social Cognition, Psychological Bulletin, 129(3), 339-375.
Kam, C. D. (2005). Who Toes the Party Line? Cues, Values, and Individual Differences. Political Behavior, 27(2), 163-182.
Klofstad, C. A. (2016). Candidate Voice Pitch Influences Election Outcomes. Political Psychology, 37(5), 725-738.
Krippendorff, K. (2004). Content analysis: An introduction to its methodology (2nd ed.). London: Sage.
Laustsen, L. (2014). Decomposing the Relationship Between Candidates’ Facial Appearance and Electoral Success. Political Behavior, 36, 777-791.
Laustsen, L. (2016). Choosing the right candidate: Observational and experimental evidence that conservatives and liberals prefer powerful and warm candidate personalities, respectively. Political Behavior (Forthcoming). doi:10.1007/s11109-016-9384-2
Laustsen, L. & Petersen, M. B. (2015). Does a competent leader make a good friend? Conflict, ideology and the psychologies of friendship and followership. Evolution and Human Behavior, 36, 286-293.
Laustsen, L. & Petersen, M. B. (2016). Winning Faces Vary by Ideology: Nonverbal Source Cues Influence Election and Communication Success in Politics. Political Communication, 33(2), 188-211.
Laustsen, L. & Petersen, M. B. (2017). Perceived conflict and leader dominance: Individual and contextual factors behind preferences for dominant leaders. Political Psychology (Forthcoming)
Laustsen, L., Petersen, M. B., & Klofstad, C. A. (2015). Vote Choice, Ideology, and Social Dominance Orientation Influence Preferences for Lower Pitched Voices in Political Candidates. Evolutionary Psychology, 13(3), 1-13.
Lenz, G. & Lawson, C. (2011). Looking the Part: Television Leads Less Informed Citizens to Vote Based on Candidates’ Appearance. American Journal of Political Science, 55(3), 574-589.
Little, A. C., Burriss, R. P., Jones, B. C., & Roberts, S. C. (2007). Facial appearance affects voting decisions. Evolution and Human Behavior,28, 18–27.
Little, A. C., Roberts, S. C., Jones, B. C., & DeBruine, L. M. (2012). The perception of attractiveness and trustworthiness in male faces affects hypothetical voting decisions differently in wartime and peacetime scenarios. The Quarterly Journal of Experimental Psychology, 65(10), 2018-2032.
Little, A. C., & Roberts, S. C. (2012). Evolution, Appearance and Occupational Success. Evolutionary Psychology, 10(5), 782-801.
Lord R. G., Foti, R. J., & De Vader, C. L. (1984). A test of leadership categorization theory: Internal structure, information processing, and leadership perceptions. Organizational Behavior and Human Performance, 34, 343–378.
Meredith, M., & Salant, Y. (2013). On The Causes and Consequences of Ballot Order Effects. Political Behavior, 35, 175-197.
Olivola, C. Y., & Todorov, A. (2010). Elected in 100 milliseconds: Appearance- based trait inferences and voting. Journal of Nonverbal Behavior, 34, 83‒110.
Oxley, D. R., Smith, K. B., Alford, J. R., Hibbing, M. V., Miller, J. L., Scalora, M., . . . Hibbing, J. R. (2008). Political attitudes vary with physiological traits. Science, 321(5896), 1667-1670.
Petersen, M. B., Sznycer, D., Sell, A., Cosmides, L., & Tooby, J. (2013). The ancestral logic of politics: Upper body strength regulates men’s assertion of self-interest over economic redistribution. Psychological Science, 24(7), 1098-1103.
Price, M. E., & Van Vugt, M. (2013). The Service-for-Prestige Theory of Leader-Follower Relations: A Review of the Evolutionary Psychology and Anthropology Literatures. In: R. Arvey & S. Colarelli (ed.). Biological Foundations of Organizational Behaviour. Chicago: Chicago University Press.
Rhodes, G. (2006). The Evolutionary Psychology of Facial Beauty. Annual Review of Psychology, 57, 199-226.
Rosar, U., Klein, M., & Beckers, T. (2008). The frog pond beauty contest: Physical attractiveness and electoral success of the constituency candidates at the North Rhine-Westphalia state election of 2005. European Journal of Political Research, 47, 64–79.
Rutchick, A. M. (2010). Deus ex machina: The influence of polling place on voting behavior. Political Psychology, 31(2), 209‒225.
Schyns, B., & Meindl, J. (2005). An overview of implicit leadership theories and their application in organization practice. In B. Schyns, & J. Meindl (Eds.), Implicit leadership theories: Essays and explorations (pp. 15–36). Greenwich: Information Age Publishing.
Sell, A., Cosmides, L., Tooby, J., Sznycer, D., von Rueden, C., & Gurven, M. (2009). Human adaptations for the visual assessment of strength and fighting ability from the body and face. Proceedings of the Royal Society, 276, 575-584.
Sell, A., Bryant, G. A., Cosmides, L., Tooby, J., Sznycer, D., von Rueden, C., Krauss, A., & Gurven, M. (2010). Adaptations in humans for assessing physical strength from the voice. Proceedings of the Royal Society, 277, 3509-3518.
Spisak, B. R., Dekker, P. H., Krüger, M., & van Vugt, M. (2012a). Warriors and peacekeepers: testing a biosocial implicit leadership hypothesis of intergroup relations using masculine and feminine faces. PlosOne,7(1), 1–8.
Spisak, B., Homan, A. C., Grabo, A., & van Vugt, M. (2012b). Facing the situation: testing a biosocial contingency model of leadership in intergroup relations using masculine and feminine faces. The Leadership Quarterly23, 273–80.
Stirrat, M., & Perrett, D. I. (2010). Valid facial cues to cooperation and trust: Male facial width and trustworthiness. Psychological Science, 21(3), 349–54.
Taber, C. & Lodge, M. (2006). Motivated Skepticism in the Evaluation of Political Beliefs. American Journal of Political Science, 50(3), 755-769.
Tooby, J., Cosmides, L., & Price, M. E. (2006). Cognitive adaptations for n-person exchange: The evolutionary roots of organizational behavior. Managerial and Decision Economics, 27, 103–129.
Tigue, C.C., Borak, D. J., O’Connor, J. M., Schandl, C., & Feinberg, D. R. (2012). Voice pitch influences voting behavior. Evolution and Human Behavior, 33, 210-216.
Todorov, A., Mandisodza, A. N., Goren, A., & Hall, C. C. (2005). Inferences of competence from faces predict election outcomes. Science, 308(5728), 1623–26.
Van Vugt, M. (2006). Evolutionary Origins of Leadership and Followership. Personality and Social Psychology Review,10(4), 354–71.
Van Vugt, M. & Ahuja, A. (2010). Selected – Why Some People Lead, Others Follow and Why It Matters. London: Profile Books
Van Vugt, M. & Grabo, A. E. (2015). The Many Faces of Leadership: An Evolutionary-Psychology Approach. Current Directions in Psychological Science, 24(6), 484-489.
Van Vugt, M., Hogan, R., & Kaiser, R. B. (2008). Leadership, Followership, and Evolution: Some Lessons from the Past. American Psychologist, 63, 182-196.
Verhulst, B., Lodge, M., & Lavine, H. (2010). The attractiveness halo: Why some candidates are perceived more favorably than others. Journal of Nonverbal Behavior, 34, 111‒117.
Von Rueden, C., Gurven, M., Kaplan, H., & Stieglitz, J. (2014). Leadership in an Egalitarian Society. Human Nature,25, 538-566.
Von Rueden, C., & Van Vugt, M. (2015). Leadership in small-scale societies: Some implications for theory, research and practice. The Leadership Quarterly, 26(6), 978-990.
Willis, J. & Todorov, A. (2006). First Impressions: Making Up Your Mind After a 100-Ms Exposure to a Face. Psychological Science,17, 592-598.
Table 1: Prediction of candidate ballot position from facial traits. Model 1 reports relationships for facial competence, facial dominance and the interaction between facial dominance and candidate ideology. Model 2 further includes the interaction between facial competence and candidate ideology. Models report unstandardized logit regression coefficients with standard errors in parentheses.
Figure 1: Predicted probabilities for position in top 20 percent of the ballot for candidates low (10th percentile) and high (90th percentile) in facial competence. Dashed lines are 95 percent confidence intervals.
Figure 2: Predicted probabilities for position in top 20 percent of the ballot for candidates low (10th percentile) and high (90th percentile) in facial dominance from liberal (left-hand panel) and conservative parties (right-hand panel), respectively. Dashed lines are 95 percent confidence intervals.
Online Supporting Information When the Party Decides: The Effects of Facial Competence and Dominance on Internal nominations of Political Candidates
S.I.1. Candidate sex and facial competence 37
S.I.2. Candidate sex and facial dominance 38
S.I.3. Robustness analyses measuring nomination success as position in top 25 percent 40
S.I.4. Robustness analyses measuring nomination success as position in top 30 percent 43
S.I.5. Robustness analyses measuring nomination success as position in top 40 percent 46
S.I.6. Robustness analyses measuring nomination success as position in top 50 percent 49
S.I.7. Robustness analyses based on continuous nomination success measure 52
S.I.8. Robustness analyses for facial competence using all 268 candidates 54
S.I.1. Candidate sex and facial competence 36
S.I.2. Candidate sex and facial dominance 37
S.I.3. Robustness analyses measuring nomination success as position in top 25 percent 39
S.I.4. Robustness analyses measuring nomination success as position in top 30 percent 42
S.I.5. Robustness analyses measuring nomination success as position in top 40 percent 45
S.I.6. Robustness analyses measuring nomination success as position in top 50 percent 48
S.I.7. Robustness analyses based on continuous nomination success measure 51
S.I.8. Robustness analyses for facial competence using all 268 candidates 53