UBC Theses and Dissertations
Heterogeneity in political decision-making : the nature, sources, extent, dynamics, and consequences of interpersonal differences in coefficient strength Fournier, Patrick
There is mounting evidence that the public's political decisional processes are heterogeneous (Rivers, 1988; Sniderman, Brody & Tetlock, 1991; and Johnston, Blais, Gidengil & Nevitte, 1996). All citizens do not reason the same way about politics: they rely on different considerations, or they give different weights to similar considerations. However, our understanding of this phenomenon remains sketchy, in many regards. I address the conceptual and empirical ambiguity by exploring the nature, the sources, the extent, the consequences, and the campaign dynamics of interpersonal heterogeneity in political decision-making. The analysis relies on Canadian and American public opinion survey data. The evidence reveals that heterogeneity is a very important phenomenon. Relationships between dependent and explanatory variables are rarely stable and consistent across the entire population. Most political decisions (especially the more common ones) and most independent variables exhibit interpersonal diversity in coefficient strength. Hypothesis-testing and explanationbuilding can be led astray if researchers limit their analyses to the whole citizenry. Normatively, heterogeneity is responsible for individual and aggregate deviations from enlightened preferences. Heterogeneity, however, is a very complex phenomenon. One can not deal with it in any simple way. A researcher can not simply capture it, take it into account, and move on to other concerns. Heterogeneity permeates through our models of political behaviour in significant, pervasive and perplexing ways. This research raises concerns about the complexity of political behaviour and our ability to understand citizens, campaigns, elections, and democracy. The world is not a simple, straightforward and easily comprehensible subject. It is much more intricate and difficult to grasp than we currently believe. In order to understand reality, our approaches, theories, and models need to be as complex and multidimensional as reality. Striving for oversimplification can only lead to misconceptions and fallacies.
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