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The Role of Genes and Environments in Linking the Need to Evaluate with Political Ideology and Political Extremity

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Abstract

Understanding the origins of political ideology and political extremity at the individual level is becoming increasingly pressing in the face of polarization in the political domain. Building upon the motivated social cognition model of political ideology, we propose a motivated cognition approach to the study of political extremity with the need to evaluate as a key epistemic motive that contributes to political extremity. Moreover, we hypothesize that the link between the need to evaluate and political extremity may rest largely on shared genetic effects. This hypothesis builds upon existing biology and politics research, which has convincingly demonstrated that genes influence the direction of ideology, but has been largely silent on the role of genes in political extremity. To test our hypothesis, we consider several types of ideological, affective, and partisan extremity alongside conventional measures of political ideology and the need to evaluate in a behavioral genetic framework. Using a twin study methodology, we show for the first that the need to evaluate is heritable, that its phenotypic relationships with ideological extremity and strength are rooted in shared genetic influences, and, unexpectedly, that the relationship between the need to evaluate and some forms of political extremity is largely environmental. In examining the genetic and environmental components of the covariation of the need to evaluate with political ideology and right wing authoritarianism, we find limited support for shared genetic influences. Taken together, these results illustrate the value of adopting a biologically informed motivated cognition approach to the study of political ideology and political extremity.

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Notes

  1. We conceive of these five aspects of political extremity as theoretically distinct, though they are positively intercorrelated. See also footnote 6.

  2. It is also possible to conduct a trivariate analysis to determine whether the need to evaluate accounts for genetic variance in political ideology or political extremity when controlling for other measures, such as the Big Five personality traits (cf. Ksiazkiewicz, Ludeke, & Krueger, 2016). The need to evaluate has modest phenotypic correlations with the Big Five personality traits. In our sample, the correlations are: openness (0.19), conscientiousness (0.02), extraversion (0.23), agreeableness (-0.09), emotional stability (0.01). Focusing on openness and extraversion, these two personality factors are largely unrelated to our measures of political extremity (all phenotypic correlations below 0.1 in absolute value). Openness does have significant phenotypic correlations with political ideology in these data (see Ksiazkiewicz, Ludeke, & Krueger, 2016), but controlling for openness does not substantively change the results discussed below. As such, we do not present analyses formally testing whether the need to evaluate accounts for unique variance in political ideology or political extremity when controlling for Big Five traits.

  3. Due to a labeling error, the middle response options on the need to evaluate scale were presented out of order. They were presented as “1 = Completely disagree, 2 = Moderately agree, 3 = Slightly agree, 4 = Slightly disagree, 5 = Moderately disagree, 6 = Completely agree.” This adds measurement error to our measure of the need to evaluate, which means that we likely have a more conservative estimate of the heritability of the need to evaluate than we might otherwise. Nonetheless, the scale demonstrates good reliability when coded as written (Cronbach’s alpha = 0.75, as compared to 0.87 in Jarvis & Petty, 1996). The reliability is considerably lower if we assume that participants fixed the poles (i.e., assumed that 1 and 6 were correct and that the intermediate categories were mislabeled; alpha = 0.56) or flipped the poles (assumed that 1 and 6 needed to be flipped; alpha = 0.56). For those participants that explicitly indicated that they were changing the labeling of the scale (e.g., by writing so on their response sheet), the participant response scale is used. Otherwise, we treat the responses as following the provided scale. This procedure produces a good Cronbach’s alpha (0.75).

  4. There is also a fourth component that is sometimes estimated to represented dominance genetic effects (D), but the simultaneous estimation of A, C, D, and E requires data beyond that provided by MZ and DZ twins.

  5. We focus here on the Wilson-Patterson measure of ideology, which contains less measurement error than the single-item measure (cf. Ksiazkiewicz, Ludeke, & Krueger, 2016).

  6. As discussed above, we think of each of the extremity measures as capturing one of five theoretically distinct forms of extremity: ideological extremity, ideological strength, ideological breadth, attitude bipolarity, and strength of partisanship. For this reason, we analyze the ten measures of extremity in these five groupings in the results. Nonetheless, these different aspects of extremity are related conceptually to each other (and empirically to the need to evaluate). When the ten measures are combined in an exploratory factor analysis, two significant factors emerge. After rotation, the first factor captures extremity in terms of the Wilson–Patterson measures. The second factor captures extremity of partisanship (extremity of party identification, extremity of feeling thermometers toward parties and candidates). The extremity of single-item ideology and the feeling thermometers toward political groups load somewhat on each factor. Both factors have a significant phenotypic correlation with the need to evaluate (0.26, 0.18) and significant unique environmental correlations with the need to evaluate (0.16, 0.21). Only Factor 1 has a significant genetic correlation (0.52; for Factor 2, rA = 0.06). We present these results here for the interested reader, but focus on the five types of extremity described previously in the main text.

  7. We kept these three types of feeling thermometers separate analytically because each represents a different type of political attitude theoretically (toward parties, candidates, and political movements). Nonetheless, the extremity of these attitudes is positively correlated. If we average together the three extremity measures, we do find a significant genetic correlation with the need to evaluate (0.30), in support of H3b, though we lose the unique environmental correlation (perhaps because the unique environmental factors that lead to attitude extremity toward parties, candidates, and political movements are not the same). We note this here simply to say that future research should utilize more nuanced measures for different types of attitudinal extremity to examine their relationships with the need to evaluate separately and jointly.

  8. A similar pattern holds for the direction of political ideology, especially economic ideology (which shares a sizeable genetic component with the need to evaluate), and right wing authoritarianism (for which the covariance with the need to evaluate is primarily through the unique environment). Here, too, research on how these traits co-develop could be theoretically insightful and practically useful for developing effective interventions for pursuing fairness and social justice, insofar as these attitudes are relevant to perpetuating existing hierarchies in society.

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Acknowledgements

This study was funded, in part, by the Rice Social Science Research Institute. The remainder of the study was crowd-funded through the SciFund Challenge.

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  1. Department of Political Science, University of Illinois at Urbana-Champaign, 420 David Kinley Hall MC-713, 1407 W Gregory Drive, Urbana, IL, 61801, USA

    Aleksander Ksiazkiewicz

  2. Department of Psychology, University of Minnesota, Minneapolis, MN, USA

    Robert F. Krueger

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Ksiazkiewicz, A., Krueger, R.F. The Role of Genes and Environments in Linking the Need to Evaluate with Political Ideology and Political Extremity. Soc Just Res 30, 381–407 (2017). https://doi.org/10.1007/s11211-017-0292-3

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