Objective. This article addresses the differences in belief systems that drive how moderates and ideologues form their policy preferences. The model put forth posits that while ideologues rely on ideological and partisan cues to form their preferences and respond to survey questions, moderates default to a more primitive source of their worldviews. Methods. This project uses an anthropological operationalization of cultural worldview to test the model by analyzing the relationships between culture, ideology, and policy preferences for moderates and ideologues separately. Results. Results indicate that the model is supported: moderates rely more heavily on their cultural views while forming and reporting their policy preferences, whereas ideologues rely primarily on their ideological views to form and report policy preferences. Conclusion. There is evidence that partisans and moderates think about their views in fundamentally different ways, which is not fully accounted for in typical models of political behavior.Public opinion literature relies on ideology and partisanship as the central components of individuals' "belief systems." Individuals use these heuristics to determine their policy preferences, but only if they identify with a political party or ideology (e.g., Campbell et al., 1960;Converse, 1964;Jacoby, 1988;Zaller, 1992;Lewis-Beck et al., 2008). The literature offers little knowledge about how individuals whose political preferences do not fall clearly to one side or the other form their preferences, except that these individuals often dictate the aggregate direction of the national mood: they swing one way or the other to determine the general direction of opinion on policy preferences-making it especially important to understand how they form preferences (Erikson, MacKuen, and Stimson, 2002;Page and Shapiro, 1992;Stimson, 2004). In the absence of ideological or partisan heuristics to guide their choices, how do moderates and those who are apolitical form preferences on political issues? This article demonstrates that a theory of culture derived from anthropology and applied to political science, Cultural Theory, explains preferences espoused by these nonideologues better than ideology and partisanship alone.The "Cultural Theory of risk" (Douglas and Wildavsky, 1982) has its origins as an anthropological theory that describes how individuals want to live in the world and with the people around them. Culture in this sense serves as a filter through which individuals comprehend their surroundings and provides a very broad social constraint on individuals' belief systems by setting the parameters of what ways of life are acceptable (Douglas, 1978;Thompson, Ellis, and Wildavsky, 1990;Wildavsky, 1987). Cultural Theory has been operationalized as a typology, and using a series of carefully developed survey * Direct correspondence to Natalie M. Jackson, Huffington Post/Pollster.com, 770 Broadway, 5th Fl., New York, NY 10003 natalie.jackson@huffingtonpost.com .
The Health Belief Model (HBM), a value‐expectancy model, is a leading framework in health behavior and communication research. The model is intended to inform targeted communication strategies that promote positive health behaviors. Individual beliefs associated with health risks such as perceived susceptibility and perceived severity are often incorporated into HBM as predictors of health behavior. However, recent studies point to limitations of the current model. At the same time, researchers have successfully used Cultural Theory (CT) to conceptualize, measure, and predict the cultural influences on health risk management. This study applies OLS regression and graphical analysis to examine the relationship between more intrinsic cultural value‐based beliefs and HBM beliefs so as to understand behavioral intentions associated with COVID‐19 among the general public in the United States while statistically controlling for the effects of partisanship and demographic factors.
This chapter discusses (1) the development of election poll aggregation and its use in popular election forecasts, (2) the technical and statistical demands of using polls this way, and (3) the controversies surrounding aggregation and forecasting. The first section covers how increases in publicly released polls resulted in poll averaging and aggregation websites becoming popular in the early 2000s, then how election forecasting using polls as the biggest predictors became popular in the media. The second section discusses how polls are aggregated and how aggregations vary. The focus then turns to how polls are used in election forecasts. Finally, common questions that arise from poll aggregation and forecasting are addressed: Are averages always better than single polls? Are there too many forecasts; do we need to aggregate the forecasts? Are we expecting too much from polls, which are meant to be snapshots, not predictions, by using them in forecasts?
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