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Partisanship as a Social Identity: Implications for Polarization

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The claim that partisanship has developed into a social identity is one of the dominant explanations for the current rising levels of affective polarization among the U.S. electorate. We provide evidence that partisanship functions as a social identity, but that the salience of partisan identity—in and of itself—does not account for increased affective polarization. Using a two-wave panel survey capturing natural variation in the salience of politics, we find that partisanship contributes more to individuals’ self-concept in times of heightened political salience. We also show that partisans can be detached from their Democratic or Republican identity by having them focus on individuating characteristics (by way of a self-affirmation treatment). However, we find only limited evidence that when partisan social identity is made less salient, either by way of natural variation in political context or through a self-affirmation treatment, partisans are any less inclined to express in-party favoritism and out-party hostility. Taken together, our evidence shows that partisanship does operate as an important social identity, but that affective polarization is likely attributable to more than the classic in-group versus out-group distinction.

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  1. See Huddy et al. (2015) and Egan (2019) for important exceptions.

  2. To the best of our knowledge, we are the first to make these connections, which provide an alternative mechanism explaining self-affirmation’s effect on displays of in-group favoritism.

  3. Nielsen ratings data show that viewership significantly drops off over the winter holiday season. For example, there is a 21% reduction in the viewership for MSNBC, and a 13% reduction for CNN from early December to the week of Christmas.

  4. We requested a sample that was evenly distributed between Democrats and Republicans; while there were some Independents/non-partisans in our resulting sample, we exclude them from analysis given our focus on partisan identity.

  5. We drop the 6 subjects who switched their party identification from Wave 1 to Wave 2. We take this as an indicator of either weak identification or, more likely, lack of attention, and thus, given our focus on partisanship, we exclude these observations.

  6. Appendix Table 7 demonstrates that our self-affirmation treatment is in fact transient; that is, there are no significant differences in means on our primary outcomes in Wave 2 according to having been assigned to self-affirmation treatment in Wave 1.

  7. We choose these alternative treatment and control conditions because they offer more experimental control than the canonical treatments, which involve an open-response writing exercise. The writing exercise also was not as conducive to the online format of our study.

  8. A similar technique using celebrities instead of strangers in a photograph has been employed previously by Napper et al. (2009).

  9. The manipulation check index is derived from seven questions asked in Wave 2 only, such as “How much did the previous exercise make you: ‘think about good things about myself’.

  10. Results are substantively similar if the “values (no ranking)” (pure control) condition subjects are dropped from the analysis. See Appendix 6.3.

  11. Both Wave 1 and Wave 2 implemented identical surveys. The general order of questions in both surveys was as follows: demographic / basic political questions (including partisanship and political interest); treatment screen; manipulation checks; affective polarization measures; partisan self questions (e.g. “Being a Democrat/Republican is an important part of my self-image.”).

  12. See Appendix Table 7 for self-affirmation treatment assignment across waves without combining the pure control and treatment.

  13. The replication data for this study can be found here

  14. While there is by random chance a significant difference between Democratic subjects’ ideology in treatment vs. control groups, this difference does not explain the significant treatment effect on the Partisan Self Index. Appendix Table 12 shows that treatment effects are substantively similar when controlling for ideology in a regression.

  15. When we instrument Partisan Self with both wave and self-affirmation treatment assignment, we again find inconsistent evidence that a reduction in Partisan Self corresponds with a reduction in our measures of affective polarization. The results from these 2SLS analyses are in Appendix 6.9, and are similar to the results presented here; namely, while there is a wave effect on the feeling thermometer measure, the wave effects on the traits measure in our partisan subsamples is insignificant, and the self-affirmation treatment has null effects on both measures of affective polarization.

  16. This effect is substantively similar in Appendix Fig. 11, which uses only true panel subjects. Recall that we focused on powering our self-affirmation treatment in Wave 1 given our hypotheses, and only powered our wave effects in Wave 2 by recontacting half of our initial respondents from Wave 1. Nonetheless, the self-affirmation treatment is still significant using the true panel, though the significance is reduced given these sample limitations.

  17. Given the possibility of “testing effects” across waves, we replicate these findings in Appendix 6.8 dropping subjects who were treated in Wave 1 from the means calculated in Wave 2. Our results are substantively unchanged.

  18. Results for these measures are replicated using only true panel subjects in Appendix Figs. 12 and 13.


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Treatment Screens

See Figs. 4, 5, 6 and 7.

Fig. 4
figure 4

Self-affirmation “Ranking Self Treatment” condition screen

Fig. 5
figure 5

“Ranking Others Control” condition screen

Fig. 6
figure 6

Self-affirmation “Pure Control” condition screen

Fig. 7
figure 7

Fake end screen separating treatment screens for outcome questions

Descriptive Statistics

See Tables 6 and 7.

Table 6 Descriptive statistics

In terms of its representativeness, our sample is about 73% white, which is on par with 2016 voter demographics—the CCS estimated white voters to have been roughly 74% of the 2016 electorate. The average age in our sample is about 49, which is roughly on par with 2016 voter age (where those 60 and older have by far the highest turnout rates—about 70%—followed closely by those age 45–59). The age and race demographics of our sample by party are also roughly on par with what we might expect given the growing numbers of non-white and younger voters within the Democratic party. Thus, while the extent to which our conclusions can be generalized to the U.S. voting population are reliant on the representativeness of our online convenience sample, the sample is not too far from this population on some key demographics.

Table 7 Subject self-aff. treatment assignment across waves: original treatment conditions (not combining pure control with treatment)

See Fig. 8, 9 and 10.

Fig. 8
figure 8

Density of partisan self index outcome, by wave

Fig. 9
figure 9

Density of in-out party therms outcome, by wave

Fig. 10
figure 10

Density of in-out party traits outcome, by wave

Replication of All Main Results Dropping Pure Control Subjects

See Tables 8 and 9.

Table 8 Wave effects (true panel subjects only)
Table 9 Self-affirmation effects (using all subjects in both waves)

Wave Effects: Individual Traits (Not an Index)

See Table 10.

Table 10 Wave effects (true panel subjects only)

Wave Effects: Out-Party Traits Only

See Table 11.

Table 11 Wave effects (true panel subjects only)

Self-affirmation Results: Control for Ideology

See Table 12.

Table 12 Self-affirmation effects (controlling for ideology)

Interaction Effect Figures (True Panel Only)

See Figs. 11, 12 and 13.

Fig. 11
figure 11

Self affirmation treatment effects on partisan self, by party and wave

Fig. 12
figure 12

Self affirmation treatment effects on party feeling thermometers, by party and wave

Fig. 13
figure 13

Self affirmation treatment effects on in-out party supporter traits, by party and wave

Interaction Effect Figures: Drop W1 Subjects Who Received Treatment for Wave 2 (Make Sure Lack of SA Treatment Effect in W2 is Not Driven by “Testing Effects” from W1)

See Figs. 14, 15 and 16.

Fig. 14
figure 14

Self affirmation treatment effects on partisan self, by party and wave

Fig. 15
figure 15

Self affirmation treatment effects on party feeling thermometers, by party and wave

Fig. 16
figure 16

Self affirmation treatment effects on in-out party supporter traits, by party and wave


See Tables 13 and 14.

Table 13 2SLS effects (col. self. instrumented by wave) (true panel subjects only)
Table 14 2SLS effects (partisan self instrumented by self-affirmation treatment)

SA Treatment Among True Panel Subjects is Transient

See Table 15.

Table 15 SA treat. in true panel is transient (treat. in Wave 1 does not affect outcomes in Wave 2)

Table 7 reports the means of each measure among samples in Wave 2 according to whether they were assigned to self-affirmation treatment or control in Wave 1.

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West, E.A., Iyengar, S. Partisanship as a Social Identity: Implications for Polarization. Polit Behav 44, 807–838 (2022).

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