Abstract
Despite the centrality of party identification to our understanding of political behavior, there remains remarkable disagreement regarding its nature and measurement. Most scholars agree that party identities are quite stable relative to attitudes. But do partisans defend their identities, or does this stability result from Bayesian learning? I hypothesize that partisans defend their identities by generating “lesser of two evils” justifications. In other words, partisan identity justification occurs in multidimensional attitude space. This also helps to explain the weak relationship between attitudes toward the two parties observed by proponents of multidimensional partisanship. I test this hypothesis in an experiment designed to evoke inconsistency between one’s party identity and political attitudes. To establish generalizability, I then replicate these results through aggregate level analysis of data from the ANES.
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Notes
This finding is particularly interesting when one notes the variation in these correlations over time. This pattern will be discussed at greater length in the pages to follow.
More specifically, I mean that party identification may not help citizens maximize the probability of voting “correctly” with respect to information costs. This is the definition of heuristic efficiency most often implied in the political science literature. Much of the controversy over heuristics stems from the fact that psychologist tend to define heuristics as “efficient” only in a much broader evolutionary sense (i.e. maximizing the probability of survival) (see Kuklinski and Quirk 2000).
See Fiorina’s (2002) “40-year retrospective” on parties and partisanship for a discussion of the ups and downs of the link between party identification and voter behavior and why such fluctuations have occurred.
Recent work by Kroh and Selb (2009) attempts to reconcile the classic model with the revisionist model by distinguishing between the “trait” aspect of partisanship inherited from one’s parents versus the “state” aspect of partisanship determined by one’s ongoing political evaluations.
In factor analysis, the difference between orthogonal “Republican” and “Democrat” dimensions versus orthogonal “partisan direction” and “partisan intensity” dimensions are purely a matter of rotation. Weisberg (1980) finds evidence of Democratic, Republican, and Independence dimensions.
Throughout this paper, feeling thermometers will be used extensively to measure attitudes. Though “feelings” are often defined as consciously experienced emotions (Damasio 1994), these feeling thermometers contain no mention of any emotion: anger, fear, enthusiasm, etc. Respondents merely rate how “warm” or “cold” they feel toward people and groups. Such simplistic measures cannot adequately capture emotions (Marcus 2000; Marcus et al. 2006), but they do capture attitudes—which have a bipolar affect component (Eagly and Chaiken 1993).
From this point forward, the terms “attitude” and “evaluation” will be used interchangeably.
In a multiparty system, it seems reasonable that one’s attitudes toward her own party would need to remain more positive (less negative) than her attitudes toward any other viable parties.
While the focus of this article will be on lesser of two evils justification, the theory also accounts for the possibility of greater of two goods justification. In other words, individuals may feel pressure to change their identities when they find themselves liking the opposition party. By rehearsing positive thoughts about their own party, individuals could ensure that their attitudes toward their own party remain more positive than their attitudes toward the opposition party—thereby avoiding the indifference threshold. From an empirical standpoint, these individuals would appear in the upper right hand quadrant of Fig. 1, lining up on the same orthogonal dimension as lesser of two evils identifiers. However, the data as well as casual observation suggest that greater of two goods justification is uncommon—perhaps not surprising given the adversarial nature of politics. Therefore, attention is focused on lesser of two evils justification.
Relatively few students at the university identify as or lean Republican (20.9% of the sample).
Comparisons between the Republicans support and Democrats oppose groups—both of which conflict with Democratic identity—show that effects of both stimuli run in the same direction, though Democrats oppose tends to produce larger effects as one might expect.
More specifically, I restrict my analyses to those who labeled themselves as a strong Democrat, weak Democrat, Independent leaning Democrat, or Independent not leaning toward either political party. Pure independents are included in the analysis in order to avoid losing data on any subjects who may have been leaning toward the Democratic Party prior to the treatment. While no differences in party identification emerge between cells, it is possible that changes too small for statistics to detect may have occurred. Moreover, the pure independent category appears to include closet Democrats as one might expect in a college student sample. Looking at the characteristics of this group shows that, on average, they look a great deal like Democrats. On a feeling thermometer running from 50 to −50, pure independents give the Republican Party an average rating of −11.11 and they give the Democratic Party an average rating of 2.04. In any event, inclusion of independents makes for a more conservative test.
The control group correlation is significantly different from zero (p < .01). The difference in correlations between the party cues condition and the control condition approaches statistical significance (p < .10), and the correlation in the disagreement condition is statistically different from that of the control condition (p < .01).
After rotating the matrix to maximize the variance of loadings for each factor, the two dimensions extracted in the high threat conditions come to reflect attitudes toward the Democratic Party and attitudes toward the Republican Party respectively. Strength of party identification is associated with both of these dimensions (negatively with the opposition party dimension), though it is associated more strongly with the favored party dimension.
Unemployment plus inflation is often referred to as the misery index. Therefore, this is essentially a measure of change in economic misery, but it is reversed so that negative values correspond to greater misery. Unemployment and inflation were chosen over other measures of economic performance (such as GDP), because of their direct influence on voters. GDP is felt largely through its influence on the availability of jobs.
The standard deviation variable is mean deviated so that the constant will take on a more intuitive value. If this step were not taken, the constant would represent the predicted correlation between the party feeling thermometers when the standard deviation of party identification (as well as all the other variables in the model) equaled zero. Since a standard deviation of zero is clearly a nonsensical notion, this variable is rescaled so that the constant will take on the value it would have when the standard deviation of party identification (partisan polarization) is at its average level. The variable is also rescaled to run from −1 to 1.
Similar models were run to check for robustness. Fixed and random effects models yielded nearly identical results.
Negative inconsistency (poor performance by one’s own party) appears to be exerting a larger influence than positive inconsistency (positive performance by the opposition party). In other words, the difference between own party incumbency and own party non-incumbency are much larger when the economy is bad than when it is good. Recall the similar pattern in the experiment, where agreeing with the opposition party exerted less influence than disagreeing with one’s own party (see footnote 10).
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Groenendyk, E. Justifying Party Identification: A Case of Identifying with the “Lesser of Two Evils”. Polit Behav 34, 453–475 (2012). https://doi.org/10.1007/s11109-011-9170-0
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DOI: https://doi.org/10.1007/s11109-011-9170-0