US Presidential Election Research Articles

Kpop: a kernel balancing approach for reducing specification assumptions in survey weighting

Abstract With the precipitous decline in response rates, researchers and pollsters have been left with highly nonrepresentative samples, relying on constructed weights to make these samples representative of the desired target population. Though practitioners employ valuable expert knowledge to choose what variables X must be adjusted for, they rarely defend particular functional forms relating these variables to the response process or the outcome. Unfortunately, commonly used calibration weights—which make the weighted mean of X in the sample equal that of the population—only ensure correct adjustment when the portion of the outcome and the response process left unexplained by linear functions of X are independent. To alleviate this functional form dependency, we describe kernel balancing for population weighting (kpop). This approach replaces the design matrix X with a kernel matrix, K encoding high-order information about X. Weights are then found to make the weighted average row of K among sampled units approximately equal to that of the target population. This produces good calibration on a wide range of smooth functions of X, without relying on the user to decide which X or what functions of them to include. We describe the method and illustrate it by application to polling data from the 2016 US presidential election.

Political Variables Predicted the Fading Affect Bias More Strongly for Political Than Nonpolitical Events in the 2020 Presidential Election

ABSTRACTWinning and losing voters tend to experience positive and negative emotions toward elections, respectively. The emotions of autobiographical event memories fade over time with unpleasant emotions fading faster than pleasant emotions; this phenomenon is referred to as the fading affect bias (FAB). Although the FAB differs across several event types (e.g., social media and nonsocial media), the FAB and its relations to political, healthy (e.g., grit), and unhealthy variables (e.g., depression) did not differ significantly across political and nonpolitical events in the context of the 2016 US presidential election. To further explore these relations across political and nonpolitical events, the current study used two online samples (college students and MTurk) in the 2020 US presidential election context. The FAB was expected and found to be robust, it was positively predicted by rehearsal ratings, and its relations to political variables were stronger for political events than nonpolitical events.

Last Word: Will Abortion Sway the 2024 US Presidential Election?

Last Word: Will Abortion Sway the 2024 US Presidential Election?

COVID-19 anti-vaccine misinformation discourse on Twitter: Influential roles of polarization and the 2020 US presidential election

This study investigated the politicization of COVID-19 vaccination on Twitter in the context of the 2020 U.S. Presidential Election. I analyzed 2,100 English tweets related to COVID-19 antivaccine misinformation from October 28th, 2020, to November 3rd, 2020 (one week before Election Day). Those tweets clustered into 12 topics.The result indicated that conspiracy theories about population control have raised concerns and become prevalent in perpetuating anti-vaccine beliefs. It also reflects the rise of a new trend in anti-vaccine topics. The study highlights the influence of partisan reasoning on vaccination decision-making in the context of a public health crisis caused by COVID-19, and the difficulty in correcting partisan-driven conspiracy theories and misinformation.

Faith, geography and the ballot box: Analyzing voting trends in the 2020 US presidential election through spatial and confessional correlations

Faith, geography and the ballot box: Analyzing voting trends in the 2020 US presidential election through spatial and confessional correlations

Neuropsychology and Politics Collide in the 2024 US Presdiential Election: Pitfalls of attacks on age, language, and memory.

Public perception of dementia has emerged as a key factor in the 2024 United States presidential election. The first televised presidential debate (27 June 2024) evoked a groundswell of concern about the neuropsychological health and political viability of President Joseph R. Biden, Jr. A rapid erosion of public support ensued, culminating in the collapse of the reelection campaign the following month. Political attacks on the cognitive fitness of world leaders create dissonance for clinical neuroscientists. We are ethically prohibited from remotely diagnosing public figures. Yet, we are also citizens with the right to feel and express personal concerns. In this commentary, I will address an often-uneasy relationship between politics and neuropsychology with a focus on the history and rationale for ethical guidelines such as the Goldwater Rule. I will also discuss lessons learned from recent events in the 2024 US election cycle about neurological health literacy (e.g. How is dementia diagnosed?) and broader impacts of age-based political attacks on global public health initiatives that target stigma reduction and improved early detection of dementia.

Civic identity: media, belonging, and Latiné youth in the 2020 US presidential election

ABSTRACT We explore how Latiné immigrant-origin youth used and made sense of media to enact their civic identities during the 2020 US presidential election cycle. In a polarized national context, this project highlights the voices and experiences of the participants (n = 39). We conducted and analysed semi-structured interviews to identify three comprehensive themes. Findings suggest that how participants used social media to dispel misinformation allowed them to redefine community and belonging, becoming informed citizens to protect and strengthen these communities, acting on their distrust of media, democracy’s fourth pillar, and reframing what it means to belong to and engage in a democracy.

The relationship between the lifestyle health index and voter turnout during the 2020 United States presidential election in the context of regional cultures

ObjectivesThere are numerous population health challenges confronting the United States (U.S.), including the unhealthy lifestyle – chronic disease pandemics. However, the impact of unhealthy lifestyle behaviors and the increased prevalence of chronic diseases that result from them affect many facets of life outside of the health domain, and their scope remains under-appreciated. The current analysis contributes to addressing this knowledge gap by comparing the newly developed Lifestyle Health Index (LHI) to U.S. county-level voter turnout rates in the 2020 presidential election. Study designDescriptive, cross-sectional, retrospective analysis. MethodsCounty-level data on the LHI, percent voter turnout, and the American Nations regional cultures model schematic was used in the current analysis. ResultsPearson correlations between county-level LHI scores and sub scores and Democratic, Republican, and overall voter turnout were all statistically significant and of similar strength (r > 0.63, p < 0.001). All counties in the worst performing LHI quartile had a voter turnout <60 %. Higher LHIs were consistently assocaited with lower voter turnout across the regional cultures, although heterogeneity was evident across the American Nations. ConclusionsA large percentage of the U.S. population is afflicted with poor health, and unhealthy lifestyle behaviors are a primary driver. Poor health does not occur in a vacuum and impacts many other facets of an individual's life. The current study further demonstrates the potential detrimental impact of poor health on civic engagement, specifically participation in the electoral process (i.e, citizens' health may influence voter turnout). Health care professionals and institutions in the U.S. should uniformly embrace the recent policy brief by the American College of Physicians on participation in the electoral process for patients receiving care. This paradigm shift has the potential to substantially improve voter turnout during U.S. elections.

Bias and excess variance in election polling: a not-so-hidden Markov model

Abstract With historic misses in the 2016 and 2020 US Presidential elections, interest in measuring polling errors has increased. The most common method for measuring directional errors and non-sampling excess variability during a postmortem for an election is by assessing the difference between the poll result and election result for polls conducted within a few days of the day of the election. Analysing such polling error data is notoriously difficult with typical models being extremely sensitive to the time between the poll and the election. We leverage hidden Markov models traditionally used for election forecasting to flexibly capture time-varying preferences and treat the election result as a peek at the typically hidden Markovian process. Our results are much less sensitive to the choice of time window, avoid conflating shifting preferences with polling error, and are more interpretable despite a highly flexible model. We demonstrate these results with data on polls from the 2004 through 2020 US Presidential elections and 1992 through 2020 US Senate elections, concluding that previously reported estimates of bias in Presidential elections were too extreme by 10%, estimated bias in Senatorial elections was too extreme by 25%, and excess variability estimates were also too large.

Theology of migration: From division to reconciliation

As the next US presidential election approaches, immigration once again emerges as one of the most heated issues in US political debates. While ideological differences over immigration are not new, the existence of such differing positions between and within parties highlights the deep-seated divisions within US society. Even more problematic is the current predominant narrative of immigration, which tends to foster further division while ignoring the diversity of immigration patterns and immigrants’ experiences that require holistic approaches. The dominance of a monolithic interpretation of immigration, focusing on a specific pattern and accompanied by the reproduction of provocative images and rhetoric in the media, exacerbates societal divisions and reinforces a single narrative of immigration characterized by hate and fear. In the face of societal division over immigration, this article argues that immigration can be a source of reconciliation rather than division when its inherent diversity is recognized, and its humanness is reclaimed through the concept of imago Dei, the primary definition of all human identity.

Looking Ahead to the 2024 US Presidential Election: Are 65+ Voters Really Shifting to the Left?

Looking Ahead to the 2024 US Presidential Election: Are 65+ Voters Really Shifting to the Left?

Distrusting the Process: Electoral Trust, Operational Ideology, and Nonvoting Political Participation in the 2020 American Electorate.

This article explores the relationships between electoral trust, operational ideology, and nonvoting political participation (NVP) during the 2020 US presidential election cycle. We hypothesize that: (1) more liberal operational ideology is associated with more NVP, (2) less electoral trust is associated with more NVP, and (3) operational ideology moderates the negative relationship between electoral trust and NVP. Using data from the 2020 American National Election Study (N = 8,280), our contribution is threefold: We first add to previous research that indicated liberals engage in more NVP than conservatives. We then provide some of the first evidence to suggest that electoral trust-in this case, trust prior to the 2020 election-is negatively associated with NVP. Results further indicate that the negative relationship between electoral trust and NVP is strongest among those with conservative operational ideology, such that the more trust those with conservative operational ideology have in the election, the less they engage in NVP. Given that electoral trust is crucial for a well-functioning democracy, the implication is that elites with a strategic incentive to express contempt for the election process can have direct and downstream consequences on political participation.

Protectionism, bilateral integration, and the cross section of exchange rate returns in US presidential debates

We study the impact of US presidential election TV debates on the cross section of intraday exchange rate returns of 96 currencies from 1996 to 2016. The performance of the candidates in the debate is an exogenous shock to the election probability. We find that currencies of countries with high levels of bilateral foreign trade with the US depreciate if the election probability of the protectionist candidate increases during the debate, while no significant impact is detected for countries with bilateral US exports to GDP below 2 percent. Expectations about protectionist measures are the main transmission channel of debate outcomes, while the candidates' stance towards military and immigration play a minor role.

How Did Medicare for All Influence Trump’s Electoral Prospects Across Different Levels of COVID-19 Perceived Political Engagement?

Background The 2020 US presidential election was a pivotal moment in American politics, with the healthcare system taking center stage as a critical issue. The COVID-19 pandemic significantly raised public awareness about the deficiencies of the US healthcare system, leading to increased support for comprehensive healthcare reforms, such as Medicare for All. Methods This study examines the relationship between the pandemic, support for Medicare for All, and voting choices in the 2020 presidential election. Logistic regression analyses were conducted using data from the Collaborative Multi-Racial Post-Election Survey (CMPS) 2020 to explore the impact of support for Medicare for All on voting behavior. The analysis controlled for variables such as partisanship, race, gender, age, education, economic anxiety, and COVID-19 exposure. Results The findings indicate a negative relationship between support for Medicare for All and voting for Donald Trump. This relationship holds true across different levels of perceived COVID-19 political engagement. The analysis demonstrates that increased support for Medicare for All is associated with a decreased likelihood of voting for Trump. This effect is more pronounced among individuals who reported minimal impact of the pandemic on their political engagement. Conclusions The COVID-19 pandemic brought healthcare issues to the forefront of public discourse, reinforcing existing health policy preferences rather than altering them. The study provides insights into how major crises like the COVID-19 pandemic can influence public attitudes and political outcomes. These findings have significant implications for future healthcare policies and electoral strategies, emphasizing the need to consider both enduring health policy preferences and the situational effects of crises.

Polarizing Uses of Older Age

The Forum in Issue 8 of Age, Culture, Humanities is dedicated to the timely topic of the 2024 US American presidential elections, where the role of older age has loomed over the campaign. We invited distinguished colleagues from the USA, Canada, and Denmark to contribute short comments and reflections from an age studies perspective. Eight of them accepted, despite the short deadline, and their essays were published in instalments from mid-April to mid-July 2024. In this introduction, I expand on one topic that popped up again and again, namely the polarizing tendencies many observed in the current discourse. I ask: What is the role of age in the context of polarization?

Spatially constrained statistical approach for determining the optimal number of regions in regionalization

Determining the optimal number of regions is a challenging issue in regionalization. Although cluster validity indices developed for non-spatial clustering have been used to determine the optimal number of regions, spatial contiguity constraints for regionalization are often neglected. Consequently, different regionalization results can share the same validity index value, which reduces the reliability of identifying the optimal number of regions in regionalization. To overcome this limitation, this study proposes a spatially constrained statistical approach for determining the optimal number of regions using two metrics: (i) a permutation-based variance for measuring the homogeneity within regions and (ii) a proportion index based on spatially constrained k-nearest neighbors to quantify the separation between regions. Furthermore, a distance-based method is employed to balance these two metrics to automatically determine the optimal number of regions. Experimental results on five synthetic datasets, the US presidential election and climate datasets show that the statistical approach developed in this study outperforms three widely used cluster validity indices in determining the optimal number of regions. The proposed statistical approach is straightforward to implement and can effectively reduce subjectivity in regionalization.

Overseas institutional uncertainty and corporate innovation – evidence from an emerging economy

Using the 2016 US presidential election as a source of plausibly exogenous variation in uncertainty, we examine the R&amp;D effect of institutional uncertainty in Chinese listed firms. Our results show that innovation activities are adversely affected in firms exposed to external election shocks and that the effect is more pronounced in SOEs, older firms, and financially constrained firms. Our study contributes to the literature on uncertainty and R&amp;D management by broadening the conceptual boundaries of institutional uncertainty and enriching the understanding of how overseas institutional uncertainty affects domestic firms' R&amp;D activities. The findings have important implications for innovation strategy at firms and policymaking at governments.

The search suggestion effect (SSE): A quantification of how autocomplete search suggestions could be used to impact opinions and votes

News reports in 2016 suggested that a leading search engine was suppressing negative search suggestions for one US Presidential candidate but not for her opponent. We conducted a progressive series of five experiments to determine what effect differential suppression of this type might have on voters. We found that negative suggestions attract far more clicks than neutral or positive ones, consistent with extensive research on negativity bias, and that the differential suppression of negative search suggestions can turn a 50/50 split among undecided voters into more than a 90/10 split favoring the candidate for whom negative search suggestions were suppressed. We conclude that differentially suppressing negative search suggestions can have a dramatic impact on the opinions and voting preferences of undecided voters, potentially shifting a large number of votes without people knowing and without leaving a paper trail for authorities to trace.

Social Media in the Aftermath of the 2016 US Presidential Election: Disruption at the Cost of Connection

This data captures people’s experiences as unknowing targets of disinformation. Participants were US citizens naive to the actions of the different entities using social media to target Americans with disinformation in the months leading up to the 2016 US presidential election. Results indicated participants reported notable changes in their interactions on social media in the form of disruptions to existing relationships. Specifically, participants reported that they argued with their connections more, observed others disagree more, and reported an increase in the loss of friends and family connections through the unfriending or unfollowing features of social media. While, some participants found these changes amusing, most reported increased psychological distress. Not one participant mentioned Russian election interference or disinformation as the cause of these interpersonal difficulties. Analysis of text responses did not include any mention of disinformation, Cambridge Analytica, or Russia as causes of these disruptions. These results suggest that social media use has implications for individuals’ social relationships and these disruptions may impact their psychological functioning. Implications of these results for the psychological impacts of social media use will be discussed.

Geriatric Politics and the American Presidential Election

Geriatric Politics and the American Presidential Election