Implicit candidate traits in the 2016 U.S. Presidential Election: Replicating a dual-process model of candidate evaluations

A major challenge to understanding the causes and consequences of how citizens assess political candidates is the extent to which relevant attitudinal evaluations are accessible at the conscious and unconscious level. The current research examines a dual-process model of candidate trait perceptions in the context of the 2016 U.S. Presidential elections. We expected that implicit evaluations of the warmth and competence of Donald Trump and Hillary Clinton would predict explicit evaluations of the presidential candidates and related political groups, as well as voting behavior. We find that these implicit constructs, especially competence, demonstrated predictive validity for outcomes of interest in the context of the 2016 election, above and beyond explicit analogs, demographics variables, and partisan identification. The larger role of implicit competence, compared to implicit warmth, may be due, in part, to increased assimilation of implicit associations into explicit evaluations on the warmth but not the competence dimension. These findings are suggestive of the possibility that warmth assessments were also consequential in this electoral context, consistent with other research examining the impact of gender stereotypes on evaluations of females in positions of leadership. Implications and future directions for the study of political cognition, gender bias, candidate evaluations, and electoral decision-making are discussed.