What Goes with Red and Blue? Assessing Partisan Cognition through Conjoint Classification Experiments

Political parties can provide valuable information to voters by cultivating distinct associations between their labels, issue priorities, policies and group traits. Yet, there is considerable debate over which associations voters incorporate, and whether these are accurate. In this study, we develop a novel conjoint classification experiment designed to map voters' partisan associative networks. We ask respondents to ‘guess' the party and ideology of hypothetical candidates given fully randomized issue priorities and biographical details. This inferential approach minimizes the biasing effects of partisan boosting in measuring the relative associations voters make between attributes and parties, and the impact these mappings have on candidate evaluations. We find voters consistently link many issues with party and ideological labels, but agree far less on associations with candidate attributes. Our study highlights important heterogeneity in the information value of party reputations, with implications for theories of democratic competence and empirical findings emerging from candidate-vignette designs