Browse
Submit Data
Databases
API
Help

Dataset Information

21 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Status threat, not economic hardship, explains the 2016 presidential vote.

ABSTRACT: This study evaluates evidence pertaining to popular narratives explaining the American public's support for Donald J. Trump in the 2016 presidential election. First, using unique representative probability samples of the American public, tracking the same individuals from 2012 to 2016, I examine the "left behind" thesis (that is, the theory that those who lost jobs or experienced stagnant wages due to the loss of manufacturing jobs punished the incumbent party for their economic misfortunes). Second, I consider the possibility that status threat felt by the dwindling proportion of traditionally high-status Americans (i.e., whites, Christians, and men) as well as by those who perceive America's global dominance as threatened combined to increase support for the candidate who emphasized reestablishing status hierarchies of the past. Results do not support an interpretation of the election based on pocketbook economic concerns. Instead, the shorter relative distance of people's own views from the Republican candidate on trade and China corresponded to greater mass support for Trump in 2016 relative to Mitt Romney in 2012. Candidate preferences in 2016 reflected increasing anxiety among high-status groups rather than complaints about past treatment among low-status groups. Both growing domestic racial diversity and globalization contributed to a sense that white Americans are under siege by these engines of change.

SUBMITTER: Mutz DC

PROVIDER: S-EPMC5948965 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Gains in health insurance coverage explain variation in Democratic vote share in the 2008-2016 presidential elections.

Project description:In the last decade, health care reform has dominated U.S. public policy and political discourse. Double-digit rate increases in premiums in the Health Insurance Marketplaces established by the Affordable Care Act (ACA) in 2018 make this an ongoing issue that could affect future elections. A seminal event that changed the course of policy and politics around health care reform is the 2016 presidential election. The results of the 2016 presidential election departed considerably from polling forecasts. Given the prominence of the Affordable Care Act in the election, we test whether changes in health insurance coverage at the county-level correlate with changes in party vote share in the presidential elections from 2008 through 2016. We find that a one-percentage-point increase in county health insurance coverage was associated with a 0.25-percentage-point increase in the vote share for the Democratic presidential candidate. We further find that these gains on the part of the Democratic candidate came almost fully at the expense of the Republican (as opposed to third-party) presidential candidates. We also estimate models separately for states that did and did not expand Medicaid and find no differential effect of insurance gains on Democratic vote share for states that expanded Medicaid compared to those that did not. Our results are consistent with the hypothesis that outcomes in health insurance markets played a role in the outcome of the 2016 presidential election. The decisions made by the current administration, and how those decisions affect health insurance coverage and costs, may be important factors in future elections as well.

| S-EPMC6449023 | biostudies-literature

Inversions in US Presidential Elections: 1836-2016.

Project description:Inversions-in which the popular vote winner loses the election-have occurred in four US presidential races. We show that rather than being statistical flukes, inversions have been ex ante likely since the early 1800s. In elections yielding a popular vote margin within 1 point (one-eighth of presidential elections), about 40 percent will be inversions in expectation. We show this conditional probability is remarkably stable across historical periods-despite differences in which groups voted, which states existed, and which parties participated. Our findings imply that the United States has experienced so few inversions merely because there have been so few elections (and fewer close elections).

| S-EPMC10782436 | biostudies-literature

Under threat by popular vote: German-speaking immigrants' affect and cognitions following the Swiss vote against mass immigration.

Project description:A popular initiative in support of regulating future immigration to Switzerland was accepted by the electorate in 2014. Assuming that the initiative acted as an exclusionary threat for current immigrants of Switzerland, we conducted an online survey among a sample of highly-skilled German-speaking immigrants ("expats"). Participants reported having experienced negative affect following the vote. Moreover, having a more left-wing orientation, living in a political constituency that had voted pro-regulation and having proportionally few Swiss friends positively predicted negative affect following the vote. Negative affect was associated with a reported negative change in one's attitudes towards Switzerland, increased considerations to leave the country, and impaired satisfaction with life. In sum, the results suggest that a powerful exclusionary threat such as a national vote may be experienced as distressful by highly-skilled immigrants currently living in the country.

| S-EPMC5391132 | biostudies-literature

Changes in Mental Health Following the 2016 Presidential Election.

Project description:BackgroundThe 2016 presidential election and the controversial policy agenda of its victor have raised concerns about how the election may have impacted mental health.ObjectiveAssess how mental health changed from before to after the November 2016 election and how trends differed in states that voted for Donald Trump versus Hillary Clinton.DesignPre- versus post-election study using monthly cross-sectional survey data.ParticipantsA total of 499,201 adults surveyed in the Behavioral Risk Factor Surveillance System from May 2016 to May 2017.ExposureResidence in a state that voted for Trump versus state that voted for Clinton and the candidate's margin of victory in the state.Main measuresSelf-reported days of poor mental health in the last 30 days and depression rate.Key resultsCompared to October 2016, the mean days of poor mental health in the last 30 days per adult rose from 3.35 to 3.85 in December 2016 in Clinton states (0.50 days difference, p = 0.005) but remained statistically unchanged in Trump states, moving from 3.94 to 3.78 days (- 0.17 difference, p = 0.308). The rises in poor mental health days in Clinton states were driven by older adults, women, and white individuals. The depression rate in Clinton states began rising in January 2017. A 10-percentage point higher margin of victory for Clinton in a state predicted 0.41 more days of poor mental health per adult in December 2016 on average (p = 0.001).ConclusionsIn states that voted for Clinton, there were 54.6 million more days of poor mental health among adults in December 2016, the month following the election, compared to October 2016. Clinicians should consider that elections could cause at least transitory increases in poor mental health and tailor patient care accordingly, especially with the 2020 election upon us.

| S-EPMC7602772 | biostudies-literature

Correction: Under threat by popular vote: German-speaking immigrants' affect and cognitions following the Swiss vote against mass immigration.

Project description:[This corrects the article DOI: 10.1371/journal.pone.0175896.].

| S-EPMC5540401 | biostudies-other

Economic hardship, ontological insecurity, and household food waste.

Project description:The experience of a downward change in one's financial situation is so common that most consumers will experience it during their lifetime, and this prevalence has been compounded by the recent COVID-19 pandemic. Limited research, however, has examined the impact of economic hardship on consumers' food-related behavior. Using a sample of Canadians and Americans (n = 519; Mage = 38.4; SDage = 13.6; 46.2% female; 85% lived alone), we identify that economic hardship significantly and negatively predicts consumer food waste behavior, such that economic hardship leads consumers to waste less food. Conversely, we also identify a positive indirect effect wherein economic hardship positively predicts ontological insecurity (i.e., the aversive feeling of being overwhelmed and out of control), which in turn positively predicts overconsumption (e.g., overstocking one's fridge or pantry) and in turn predicts higher food waste. This preliminary work opens the door to future work exploring a potentially rich avenue of research on the implications of adverse economic events on consumer food choice, consumption, and disposal. Implications for research and practice are discussed.

| S-EPMC9759702 | biostudies-literature

Local demographic changes and US presidential voting, 2012 to 2016.

Project description:Immigration and demographic change have become highly salient in American politics, partly because of the 2016 campaign of Donald Trump. Previous research indicates that local influxes of immigrants or unfamiliar ethnic groups can generate threatened responses, but has either focused on nonelectoral outcomes or analyzed elections in large geographic units, such as counties. Here, we examine whether demographic changes at low levels of aggregation were associated with vote shifts toward an anti-immigration presidential candidate between 2012 and 2016. To do so, we compile a precinct-level dataset of election results and demographic measures for almost 32,000 precincts in the states of Florida, Georgia, Michigan, Nevada, Ohio, Pennsylvania, and Washington. We employ regression analyses varying model specifications and measures of demographic change. Our estimates uncover little evidence that influxes of Hispanics or noncitizen immigrants benefited Trump relative to past Republicans, instead consistently showing that such changes were associated with shifts to Trump's opponent.

| S-EPMC6911220 | biostudies-literature

Using Facebook data to predict the 2016 U.S. presidential election.

Project description:We use 19 billion likes on the posts of top 2000 U.S. fan pages on Facebook from 2015 to 2016 to measure the dynamic ideological positions for politicians, news outlets, and users at the national and state levels. We then use these measures to derive support rates for 2016 presidential candidates in all 50 states, to predict the election, and to compare them with state-level polls and actual vote shares. We find that: (1) Assuming that users vote for candidates closer to their own ideological positions, support rates calculated using Facebook predict that Trump will win the electoral college vote while Clinton will win the popular vote. (2) State-level Facebook support rates track state-level polling averages and pass the cointegration test, showing two time series share similar trends. (3) Compared with actual vote shares, polls generally have smaller margin of errors, but polls also often overestimate Clinton's support in right-leaning states. Overall, we provide a method to forecast elections at low cost, in real time, and based on passively revealed preference and little researcher discretion.

| S-EPMC8635376 | biostudies-literature

The 2016 presidential election and periviable births among Latina women.

Project description:ObjectiveResearch suggests that sociopolitical stressors connected with the 2016 presidential election were associated with increases in preterm birth among Latina women. This study determined whether periviable births (<26 weeks gestation), which exhibit extremely high rates of infant morbidity and mortality, among US Latina women increased above expected levels after the 2016 US presidential election.MethodsWe assigned singleton live births among Latina and non-Latina white women in the US to 96 monthly conception cohorts conceived from January 2009 through December 2016. We constructed risk ratios by dividing the rate of periviable birth among Latina women by the rate among non-Latina white women. We used time-series methods to determine if the risk ratio of periviable births in cohorts conceived by Latina women and exposed to the election of 2016 exceeded those expected from autocorrelation and calendar effects.ResultsWe found an outlying sequence of risk ratios among Latina women starting with the cohort conceived in April and ending with that conceived in November 2016. Increases in the ratios ranged from 0.07 above an expected of 1.61 for the cohort conceived in June, to 0.39 above an expected of 1.27 for the cohort conceived in April.ConclusionWe find that pregnancies in gestation at the time of the 2016 election among Latina women yielded more than expected periviable births. These findings support the argument that the prospect of anti-immigrant policies promised by the Trump campaign sufficiently stressed Latina women to affect the timing of birth.

| S-EPMC8128056 | biostudies-literature

Economic hardship and mental health complaints during COVID-19.

Project description:The COVID-19 economic crash is idiosyncratic because of its virtual standstill of economic activity. We therefore ask how individual labor market experiences are related to the development of mental health complaints in the spring of 2020. As clinical data collection was compromised during the lockdowns, standardized surveys of the European labor force provide an opportunity to observe mental health complaints as the crisis unfolded. Data are representative of active members of the labor force of six European nations that contained varying levels of COVID-19 burdens in terms of mortality and lockdown measures. We document a steep occupational prestige level gradient on the probability of facing economic hardship during the lockdowns-looming job loss, income loss, and workload decline-which evidently exacerbate socioeconomic inequalities. Analyses indicate a striking positive relationship between instantaneous economic hardships during the COVID-19 lockdown and expressing feelings of depression and health anxiety. Importantly, the magnitude of the association between such hardships and indicators of mental health deterioration is highly dependent on workers' occupational standing, revealing a second layer of exacerbating inequality.

| S-EPMC7959574 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data