When Suffrage Becomes Suffering: How the
Electoral College Affects Emotions

American Psychology-Law Society 2025 Annual Meeting

Emma Marshall, JD, MA

University of Nebraska-Lincoln

Katherine P Hazen JD, PhD

Northeastern University

Eve M. Brank, JD, PhD

University of Nebraska-Lincoln

The Electoral College

Direct Electoral Process

Bush v. Gore, 2000

INDirect Electoral Process

Chiafalo v. Washington, 2020; Duquette & Schultz, 2013

Experience of voting in Electoral College

Farber & Sherry, 2013; Issacharoff, 2003; Jones, 2024

Discrete emotions & (In)Justice

Avery & Quinones, 2002; Barclay & Kiefer, 2014

When individuals attempt to determine whether or not an injustice has occurred, they tend to pay attention to at least two pieces of information: the outcome and the process.

Research on the psychology of fairness in other contexts, however, suggests that people care deeply about the fairness of decision-making processes (Tyler, 2017) and value having a voice in that process (Folger, 1977). For example, when people are given the opportunity to vote in majority-rule elections, they tend to view the process as more fair, and the results as more legitimate, even when their preferred candidate loses (Bo et al., 2010).

However, the benefits of voice are neither automatic nor universal (de Vries et al., 2002; Darmofal, 2010). When people feel like their voice is ignored or disregarded, they may instead perceive the process as more unfair than those who had no voice at all (Avery & Quinones, 2002).

This experience of repeated voice disregard can also result in heightened negative emotions like anger and a desire to avoid similar experiences in the future (Avery & Quinones, 2002; Barclay & Kiefer, 2014).

Emotions produced by outcome (primary) and process (secondary) appraisals

Other studies have found a similar relationship between experiences of injustice and negative emotions like anger.

For example, Krehbiel and Cropanzano (2000) found that people tend to experience more negative emotions like anger and sadness when an unfavorable outcome results from an unfair procedure.

Whereas more positive emotions like happiness are primarily the result of a favorable outcome and are less sensitive to process-based concerns.

When we talk about outcome favorability here - we are referring to whether or not an outcome is personally beneficial. So an outcome could be favorable, even if it is the result of an unfair process.

According to cognitive appraisal theories, emotion typically results from this kind of judgement. A general emotional response begins by an initial primary appraisal of an event as either beneficial (favorable) or harmful (unfavorable) in relation to a persons goal. So

Methods

Participants

Pilot Study 1

POTUS 2016

N = 257
100% Winner-takes-all
M-turk

Pilot Study 2

POTUS 2016

N = 175
- n = 95 (54%) Winner-take-all
- n = 80 (46%) District-based
M-turk

Study 1

POTUS 2020

N = 783
- n = 395 (50%) Winner-takes-all
- n = 295 (38%) District-based
Prolific

Materials & Procedure

Results

Pilot Study 1: Favorable outcomes produce HAPPY voters

The model explains 58.5% of the variance in happiness (R² = 0.5847). ANCOVA significant (F(6, 168) = 39.42, p < 0.001).

Covariate Effects

None of the demographic covariates significantly predict happiness on their own p<.05

Main Effects

As expected, happiness was primarily the result of people’s likely satisfaction with the results of the election. Consistent, with the idea that happiness is primarily an emotional response that is based on people’s view of how favorable or unfavorable the outcome is, the perception that the process was fair was not signficant (p = 0.052), after controlling for other demo variables.

But those who voted for the candidate that won the overall election and became president report happiness scores that are 3.28 points higher than those with unfavorable outcomes, after controlling for demographics and fairness perceptions.

The interaction between fairness and outcome is also not statistically significant (p = 0.29), suggesting that the effect of fairness on happiness doesn’t significantly differ between people who experienced favorable vs. unfavorable outcomes.

Estimated Marginal Means After controlling for demographics, the predicted happiness levels for each combination are:

Unfair & Unfavorable: -1.29 (most unhappy group) Fair & Unfavorable: -0.76 (still unhappy, but less so)

Unfair & Favorable: 1.99 (happy despite unfairness) Fair & Favorable: 2.01 (happiest group, but only slightly above unfair/favorable)

Pilot Study 1: Both Favorable outcomes and unfair procedures influence ANGER

Similarly, as expected, participants’ higher levels of anger towards the EC system seemed to occur when an unfavorable outcome was paired with some type of unfair procedure.

Although the interaction effect was not significant (p = 0.73), there was a main effect of both outcome favorability and process fairness perceptions on people’s level of anger p < 0.001).

So while the effect of fairness on anger doesn’t significantly differ between people who experienced favorable vs. unfavorable outcomes, there was a pattern that emerged that supports the idea that anger resulted from both outcome and process related concerns.

Voters who perceived the EC as unfair and experienced unfavorable outcomes reported the highest levels of anger.

Unfair & Unfavorable (0): 1.28 (highest anger)

Fair & Unfavorable (0): 0.17 (reduced anger)

Unfair & Favorable (1): -1.11 (low anger despite unfairness)

Fair & Favorable (1): -1.99 (lowest anger)

Notably, these factors only explain 37.7% of the variance in anger (R² = 0.3771), so there is likely more going on here.

Pilot Study 2: Similar pattern emerges
for other negative emotions

In study 2, we were able to replicate these results for happy and anger emotions and also identify similar patterns for other negative emotions including sadness, anxiety, and fear (all ps < .001).

While none of the interaction effects were significant, we did find that both outcome favorability and seeing the process as fair had a significant main effect on anger, sadness, anxiety and fear (all ps < .001).

Anger

Key Finding: Both winning an election and seeing the process as fair significantly reduced anger. Details: People whose preferred candidate won showed much lower anger (β = -3.24). Perceiving the process as fair also reduced anger (β = -1.04), especially among those who lost. Demographic Impact: No significant effects of gender, education, or age.

Anxiety

Key Finding: Election outcomes, fairness perceptions, and gender all influenced anxiety levels. Details: Favorable outcomes substantially reduced anxiety (β = -2.96). Fairness perceptions also decreased anxiety (β = -1.07). Men reported somewhat higher anxiety levels (β = 0.66). Impact for Losers: For electoral losers, perceiving the process as fair reduced anxiety by 87%.

Fear

Key Finding: Winning and fairness both significantly reduced fear, with a potential interaction. Details: Favorable outcomes strongly decreased fear (β = -2.73). Fairness perceptions also reduced fear (β = -1.10). The marginally significant interaction (p = 0.08) suggests fairness matters more for reducing fear among losers than winners. Dramatic Effect: Among electoral losers, perceiving the process as fair reduced fear by 93%.

Sadness

Outcome and fairness both influenced sadness, but with smaller effects than for other emotions. Fairness had the smallest impact on sadness compared to other emotions, but still reduced it by 79% among people who voted for a losing candidate.

Overall, these findings reveal that while winning or losing an election is the strongest determinant of a person’s emotional response, especially for positive emotions like happiness.

But perceiving the electoral process as fair also seems to play an important role in reducing negative emotional responses to the electoral college, especially for those whose voted for the candidate that ultimately lost the election.

Study 1: Do these emotions predict future voting intentions?

We found similar patterns in Study 1 with the 2020 election data. But we also wanted to see if people’s emotions towards the EC significantly predicted their intentions to vote in future elections (all ps < .001).

In order to determine the role that outcome favorability, pj, and emotions play in producing people’s intentions to vote in the future we ran a series of beta regressions. Here you can see the basic structure of our three nested models.

We first ran a model with only outcome favorability and demographic factors.

Next, we ran a more complex model that added in pj variables to see if people’s perceptions of process fairness better predicted people’s intentions to vote.

Finally, we added in the emotions variables, so that our full model included outcome favorability, pj, and emotions.

You can see that the models are color coded – so red indicates the coefficients for the outcome only model. Blue for the model with PJ variables, and green for the full model.

Study 1: Favorable outcomes, unfair procedures, and emotions
predict future voting intentions

intent using beta regression with three different models of increasing complexity:

Basic Model (Outcome Only): This only considered case outcomes from 2020 as a predictor and explained very little of the variation in intent (only about 1%).

Justice Model: This added procedural justice variables (fairness, voice, trust, neutrality, and respect) to the outcome variable. This model performed significantly better than the basic model, explaining about 4.3% of the variation in intent.

Key findings include:

Fairness had a positive effect on intent Voice (being heard) had a positive effect

Respect, surprisingly, had a negative relationship with intent

Trust and neutrality weren’t statistically significant

Full Model: This added emotional variables (anger, happiness, anxiety, sadness, and fear) to the justice model. This model performed significantly better than the justice model, explaining about 7% of the variation. Key emotional findings include:

Happiness had a positive effect on intent Anxiety had a positive effect Fear had a negative effect Anger and sadness weren’t significant

The likelihood ratio tests confirmed that each more complex model was significantly better than the simpler one. While AIC (which balances model fit and simplicity) favors the full model, BIC (which more heavily penalizes complexity) favors the simpler models, suggesting some caution because we might have an issue with overfitting.

interpret chart:

Key Findings:

Outcome Favorability: Significant in the Outcome Only and Justice models (red and blue), but not significant in the Full Model (not shown in green) Fairness: Positive and significant in both Justice and Full models Voice: Positive and significant in both models Respect: Negative and significant in both models (confidence interval entirely to the left of zero) Happiness and Anxiety: Positive and significant in the Full Model Fear: Negative and significant in the Full Model Trust, Neutrality, Anger, and Sadness: Not significant (gray dots with confidence intervals crossing zero)

Comparison Across Models: You can see how adding variables changed some coefficients. For example, the effect of Outcome Favorability disappeared when emotions were added, suggesting emotions might mediate this relationship.

Discussion

Emotional responses to the Electoral College shaped by both Outcome Favorability and Process-Fairness
Evidence that vote disregard in EC produces unique emotional experience
Future research needed to test Frustration effect and impact of repeated voice disregard on voting behaviors

Overall our findings suggest that both election outcomes and perceptions of fairness in the EC process affect how people feel about the experience of voting, and that having one’s vote disregarded by the EC might just be a uniquely infuriating experience, that has consequences for people’s future voting behavior.

However, these findings should all be considered preliminary. For one thing, the 2020 election was unusual in that there was a coordinated effort to convince a significant portion of the population that the results were illegitimate– ie., stop the steal. So, it is not entirely clear how much of our results are due to some unique facet of our current political moment.

Future research with higher-powered samples and longitudinal data tracking voting behavior across multiple electoral cycles are needed to better understand the nature of these relationships. Especially given that previous scholarship on the “frustration effect” suggests that repeated experiences of having one’s voice disregarded are often needed to produce changes in voice behavior.

But we hope to keep exploring these questions, in bigger, longitudinal datasets like the American National Election Survey (https://electionstudies.org/data-center/2024-time-series-study/) that can show us how these patterns and relationships might play out over time and across largers groups of votes.

We also hope to further explore whether people tend to discriminate between the EC and other electoral systems that count votes more normally. Does the experience of having one’s vote disregarded in the EC system may result in increased negative emotions towards the EC which in turn discourages participation in future presidential elections while simultaneously encouraging participation in other federal elections where the EC does not play a role in determining the outcome? If so, it may help to explain some of the voter turnout issues we see in the US.

When Suffrage Becomes Suffering: How the Electoral College Affects Emotions