COVID-19 Public Health Measures During National Assembly Elections of the Republic of Korea.
ABSTRACT: The general elections for the 21st National Assembly in the Republic of Korea were scheduled for April 15th, 2020, which was during the novel coronavirus disease (COVID-19) outbreak. To ensure a safe election, the Korean Centers for Disease Control and Prevention (KCDC) recommended several public health measures. The KCDC developed key interventions after reviewing the general election strategy that targeted COVID-19 patients and individuals isolating at home. Four voters who participated in the election tested positive, but did not contract COVID-19 during voting. The results demonstrated that the KCDC minimized the spread of infection in the community during the election. The measures implemented by KCDC during the election held under a COVID-19 outbreak cannot be generalized to elections as a whole because cultural and national consciousness vary between countries. Nevertheless, it demonstrates that the systemic strategies and applications against the pandemic can minimize the possibility of viral spread.
Project description:The decisions voters make-and whether those decisions are rational-have profound implications on the functionality of a democratic society. In this study, we delineated two criteria in evaluating voter rationality and weigh evidence of voter rationality versus irrationality. Furthermore, we compared models in two different elections in Taiwan to explore the reasons behind the irrational choices voters can make. Survey questions and an implicit association test (IAT) were administered prior to both elections among 197 voters in Taipei. These voters then reported their actual votes post-election. Model testing suggests that voters often are rational, but are more likely to make irrational choices in more important elections. Our findings indicate that voters generally aim to be diligent and to optimize their choices, even if they make less rational choices in the end. Further implications regarding elections and human rationality are discussed.
Project description:With a majority of 'Yes' votes in the Constitutional Referendum of 2017, Turkey continued its drift towards an autocracy. By the will of the Turkish people, this referendum transferred practically all executive power to president Erdo?an. However, the referendum was confronted with a substantial number of allegations of electoral misconducts and irregularities, ranging from state coercion of 'No' supporters to the controversial validity of unstamped ballots. Here we report the results of an election forensic analysis of recent Turkish elections to clarify to what extent it is plausible that these voting irregularities were present and able to influence the outcome of the referendum. We apply statistical forensics tests to identify the specific nature of the alleged electoral malpractices. In particular, we test whether the data contains fingerprints for ballot stuffing (submission of multiple ballots per person during the vote) and voter rigging (coercion and intimidation of voters). Additionally, we perform tests to identify numerical anomalies in the election results. For the 2017 Constitutional Referendum we find systematic and highly significant statistical support for the presence of both ballot stuffing and voter rigging. In 11% of stations we find signs for ballot stuffing with a standard deviation (uncertainty of ballot stuffing probability) of 2.7% (4 sigma event). Removing such ballot-stuffing-characteristic anomalies from the data would tip the overall balance from 'No' to a majority of 'Yes' votes. The 2017 election was followed by early elections in 2018 to directly vote for a new president who would now be head of state and government. We find statistical irregularities in the 2018 presidential and parliamentary elections similar in size and direction to those in 2017. These findings validate that our results unveil systematic and potentially even fraudulent biases that require further attention in order to combat electoral malpractices.
Project description:Do elections motivate incumbent politicians to serve their voters? In this paper, we use millions of service requests placed by residents in US cities to measure constituency responsiveness. We then test whether an unusual policy change in New York City, which enabled city councilors to run for three rather than two terms in office, improved constituency responsiveness in previously term-limited councilors' districts. Using difference-in-differences, we find robust evidence for this. Taking advantage of differential timing of local election races in New York City and San Francisco, we also find late-term improvements to responsiveness in districts represented by reelection-seeking incumbents. Elections improve municipal services, but also create cycles in constituency responsiveness. These findings have implications for theories of representative democracy.
Project description:Are voters as polarized as political leaders when it comes to their preferences about how to cast their ballots in November 2020 and their policy positions on how elections should be run in light of the COVID-19 outbreak? Prior research has shown little party divide on voting by mail, with nearly equal percentages of voters in both parties choosing to vote this way where it is an option. Has a divide opened up this year in how voters aligned with the Democratic and Republican parties prefer to cast a ballot? We address these questions with two nationally diverse, online surveys fielded from April 8 to 10 and June 11 to 13, of 5,612 and 5,818 eligible voters, respectively, with an embedded experiment providing treated respondents with scientific projections about the COVID-19 outbreak. We find a nearly 10 percentage point difference between Democrats and Republicans in their preference for voting by mail in April, which had doubled in size to nearly 20 percentage points in June. This partisan gap is wider still for those exposed to scientific projections about the pandemic. We also find that support for national legislation requiring states to offer no-excuse absentee ballots has emerged as an increasingly polarized issue.
Project description:Before and after the 2016 US Presidential Election, this research examined Trump and Clinton supporters' attributions about behavior of each leader, both of whose ethicality had been publicly questioned. American voters (N = 268) attributed significantly more dispositional factors to the outgroup leader than to the ingroup leader. Moreover, when the ingroup candidate won the election (i.e., among Trump supporters), unethical leadership subsequently became more acceptable and there was less desire to tighten the election process when dealing with unethical candidates. The opposite pattern was found among voters whose ingroup candidate lost the election (Clinton supporters). The results and implications are discussed.
Project description:Internet search rankings have a significant impact on consumer choices, mainly because users trust and choose higher-ranked results more than lower-ranked results. Given the apparent power of search rankings, we asked whether they could be manipulated to alter the preferences of undecided voters in democratic elections. Here we report the results of five relevant double-blind, randomized controlled experiments, using a total of 4,556 undecided voters representing diverse demographic characteristics of the voting populations of the United States and India. The fifth experiment is especially notable in that it was conducted with eligible voters throughout India in the midst of India's 2014 Lok Sabha elections just before the final votes were cast. The results of these experiments demonstrate that (i) biased search rankings can shift the voting preferences of undecided voters by 20% or more, (ii) the shift can be much higher in some demographic groups, and (iii) search ranking bias can be masked so that people show no awareness of the manipulation. We call this type of influence, which might be applicable to a variety of attitudes and beliefs, the search engine manipulation effect. Given that many elections are won by small margins, our results suggest that a search engine company has the power to influence the results of a substantial number of elections with impunity. The impact of such manipulations would be especially large in countries dominated by a single search engine company.
Project description:High-quality historical data about US Congressional elections has long provided common ground for electoral studies. However, advances in geographic information science have recently made it efficient to compile, distribute, and analyze large spatio-temporal data sets on the structure of US Congressional districts. A single spatio-temporal data set that relates US Congressional election results to the spatial extent of the constituencies has not yet been developed. To address this, existing high-quality data sets of elections returns were combined with a spatiotemporal data set on Congressional district boundaries to generate a new spatio-temporal database of US Congressional election results that are explicitly linked to the geospatial data about the districts themselves.
Project description:This paper tests whether economic growth and unemployment rates matter in the re-election of incumbent district leaders in Indonesia. Applying the Probit and Hekcprobit model on Indonesia's local direct elections during 2005-2013, we find that both unemployment and GDP per capita growth has an impact on election outcomes in the election year. However, for incumbent district leaders' it is only the average annual GDP per capita growth that matters for re-election. However, when we separate luck (district's performance due to regional or national economy) from competence (district's own economic performance), we find that competence matters for re-election in the election year, while luck matters for re-election in the average annual performance of the incumbents' tenure. The findings suggest that voters put more attention and vigilance on the incumbents' performances in the last year of their tenure, rather than on their whole tenure.
Project description:AIM: To compare the results of a series of public opinion surveys on experiences with the health care sector in Croatia conducted in the time of elections and to analyze whether political party affiliation had any influence on issues of priority ranking. METHODS: The surveys were conducted during 2005, 2007, and 2009. They were administered through a Computer Assisted Telephone Interviewing method to representative samples of Croatian population and were statistically weighted according to sex, age, level of education, and political party affiliation. The random sampling of the person within the household was done using the table of random numbers. RESULT: Health and health care system was the most important issue (58%) during the 2007 parliamentary election and the second most important issue during the 2005 and 2009 elections (46% and 28%). In the 2007 election, health care was viewed as most important by women, respondents with lower education levels, and respondents with lower income. In 2005, the most important health care issues were corruption and lack of funding (45% and 43%, respectively), in 2007 poor organization and lack of funding (43% and 42%, respectively), and in 2009 lack of funding and corruption (51% and 45%, respectively). CONCLUSION: Health and health care system were consistently among the top two issues in all elections from 2005 to 2009. The top three most important health care sector issues were corruption, poor organization, and lack of funding. This indicates that political parties should include solutions to these issues in their health care policymaking.
Project description:BACKGROUND:The COVID-19 pandemic has caused major disruptions worldwide since March 2020. The experience of the 1918 influenza pandemic demonstrated that decreases in the infection rates of COVID-19 do not guarantee continuity of the trend. OBJECTIVE:The aim of this study was to develop a precise spread model of COVID-19 with time-dependent parameters via deep learning to respond promptly to the dynamic situation of the outbreak and proactively minimize damage. METHODS:In this study, we investigated a mathematical model with time-dependent parameters via deep learning based on forward-inverse problems. We used data from the Korea Centers for Disease Control and Prevention (KCDC) and the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University for Korea and the other countries, respectively. Because the data consist of confirmed, recovered, and deceased cases, we selected the susceptible-infected-recovered (SIR) model and found approximated solutions as well as model parameters. Specifically, we applied fully connected neural networks to the solutions and parameters and designed suitable loss functions. RESULTS:We developed an entirely new SIR model with time-dependent parameters via deep learning methods. Furthermore, we validated the model with the conventional Runge-Kutta fourth order model to confirm its convergent nature. In addition, we evaluated our model based on the real-world situation reported from the KCDC, the Korean government, and news media. We also crossvalidated our model using data from the CSSE for Italy, Sweden, and the United States. CONCLUSIONS:The methodology and new model of this study could be employed for short-term prediction of COVID-19, which could help the government prepare for a new outbreak. In addition, from the perspective of measuring medical resources, our model has powerful strength because it assumes all the parameters as time-dependent, which reflects the exact status of viral spread.