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Political Behavior

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01-12-2010 | ORIGINAL PAPER

How Sophistication Affected The 2000 Presidential Vote: Traditional Sophistication Measures Versus Conceptualization

Authors: Herbert F. Weisberg, Steven P. Nawara

Published in: Political Behavior | Issue 4/2010

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Abstract

The 2000 Presidential vote is modeled using voter sophistication as a source of heterogeneity. Three measures of sophistication are employed: education, knowledge, and the levels of conceptualization. Interacting them with vote predictors shows little meaningful variation. However, removing the assumption of ordinality from the levels of conceptualization uncovers considerable heterogeneity in the importance of the vote predictors in explaining the vote. Thus, different sophistication measures should not be treated as equivalent, nor combined as if they are equivalent. Few of the issue and candidate components are relevant to those with a less sophisticated understanding of politics. The opposite partisan attachments of the two most sophisticated groups suggest that sophistication’s impact on the vote can be confounded by partisanship.

previous article Explicit Evidence on the Import of Implicit Attitudes: The IAT and Immigration Policy Judgments

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For this analysis, we divided educational experience into three categories: those with high school degrees or less, those with some college, and those with at least a bachelor’s degree.

This ten-point additive scale includes the identification of Trent Lott, Tony Blair, William Rehnquist, and Janet Reno, the identification of the major presidential and vice presidential candidates’ home states (with multiple choice options), and knowledge of which party controlled both the House and Senate before the election (mean = 3.8, std. dev = 2.6).

This is in contrast to Knight’s (1985) finding that Levels B and C are qualitatively different from Level A on the one hand and Level D on the other in the extent to which ideological concerns are important to their vote.

As Rahn, Krosnick, and Breuning (1994) show, responses to the open-ended likes and dislikes questions may be rationalizations of prior evaluations of the candidates, which suggests that differences found between voters of degrees of sophistication may indicate differences in how they are able to rationalize those evaluations.

While the levels and the vote components are coded off the same open-ended comments, there is not necessarily a relationship between group benefits voters and the social group component. Group benefits voters can also mention domestic policies and the candidates in their open-ended comments, and those components could be found more important in the statistical analysis than the social group component. Conversely, people who comment about the social groups can also make ideological comments, so that the social group component could be found to be more important for ideological voters than for level B.

In analyzing the 2000 ANES data, we use the post-election weights, since the dependent variable is a post-election measure. These weights are the product of the household non-response adjustment factor, the within-household selection weight (number of eligible persons), and a post-stratification adjustment factor by age and education: v000002a. We use weights in the regression since we do not include demographic characteristics as control variables.

Adding controls on such demographics as gender, age, education, and race has minimal effect on the equations in Table 2, with there being no consistent pattern to the occasional significance of one demographic variable for one conceptualization level.

Just one of the 157 respondents in Level D made a (single) comment about foreign policy, so that component lacks sufficient variance to be included in the regression equation.

Comments regarding the parties as managers of government are generally highly partisan in nature, so their potential effect is likely absorbed by the control on party identification.

We appreciate the advice of Luke Keele, who suggested this approach for estimating the impact of the individual components on the vote within the logit framework. It is analogous to Stokes’ b*Xbar approach for regression in that it shows zero impact when the coefficient is zero and when the component mean is at the neutral zero point. The predicted probabilities were calculated using CLARIFY: Software for Interpreting and Presenting Statistical Results, Version 2.0 (Tomz et al. 2001; King et al. 2000).

Because pure Independents are least constrained by partisanship, these estimates of impact should be regarded as higher than would be obtained for other partisan categories. While we choose to analyze these predicted probability changes for Independents, some may prefer to drop party identification from the analysis to consider the components without having to specify partisanship when calculating the predicted probabilities. The appendix provides these estimates from a logistic regression analysis in which partisanship was not controlled.

The differences between domestic and foreign policy components also reflect the number of policy comments made by respondents. Domestic policy was the subject of the most comments, with the average person giving 3.8 responses, while the average number of foreign policy responses was just 0.26.

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Title: How Sophistication Affected The 2000 Presidential Vote: Traditional Sophistication Measures Versus Conceptualization
Authors: Herbert F. Weisberg
Steven P. Nawara
Publication date: 01-12-2010
Publisher: Springer US
Published in: Political Behavior / Issue 4/2010
Print ISSN: 0190-9320
Electronic ISSN: 1573-6687
DOI: https://doi.org/10.1007/s11109-010-9117-x

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