Year: 2010
Type: article
Abstract: Americans ’ political beliefs present a long observed paradox. Whereas the mainstream political discourse is structured on a clearly defined polarity between conservative and liberal views, in practice, most people exhibit ideologically incoherent belief patterns. This paper challenges the notion that political beliefs are necessarily defined by a singular ideological continuum. It applies a new, network-based method for detecting heterogeneity in collective patterns of opinion, relational class analysis (RCA), to Americans’ political attitudes as captured by the American National Election Studies. By refraining from making a-priori assumptions about how beliefs are interconnected, RCA looks for opinion structures, belief networks, that are not necessarily congruent with received wisdom. It finds that in the twenty years between 1984 and 2004 Americans ’ political attitudes were consistently structured by two alternative belief systems: one that is strongly aligned with the liberal-conservative divide, another that rejects the association between moral (e.g. abortion) and economic (e.g. redistribution) attitudes. An interaction between class and religious participation explains this variance. High earners with weak religious commitments, and vice versa, tend to exhibit the latter approach; those with seemingly conflicting moral and economic worldviews are also more likely to self-identify as Republicans. These findings are particularly relevant for recent debates on the roles of moral and economic beliefs in shaping political behavior, suggesting that different sociodemographic groups understand the political debate differently, and consequently emphasize different issues in deciding their party identification. Please do not quote without permission. We thank Paul DiMaggio for useful comments. The usual
Authors: Delia Baldassarri, Amir Goldberg
Institutions: Princeton University, Columbia University, Stanford University
Language: English
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W1546342129