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Survey research methodology is evolving rapidly, as new technologies provide new opportunities. One of the areas of innovation regards the development of online interview best practices, and the advancement of methods that allow researchers to measure the attention that subjects are devoting to the survey task. Reliable measurement of subject attention can yield important information about the quality of the survey response. In this paper, we take advantage of an innovative survey we conducted in 2018, in which we directly connect survey responses to administrative data, allowing us to directly assess the association between survey attention and response quality. We show that attentive survey subjects are more likely to provide accurate survey responses regarding a number of behaviors and attributes that we can validate with our administrative data. The best strategy to deal with inattentive respondents, however, depends on the correlation between respondent attention and the outcome of interest.

Objective: Racial minority groups are often assumed to support equal opportunity policies, with most research focused on biracial contexts between Whites and Blacks. With a unique opportunity to study richer contexts from California’s 2020 elections, we test whether Latino voters supported ballot measures associated with equal opportunity. Methods: Using data on vote choice for Propositions 15 (raising commercial property taxes) and 16 (repealing prohibition of affirmative action) from a post-election survey of California registrants, we use logistic regression to test whether Latino support for equal opportunity policies is higher than that of Whites. Results: For both propositions, while Latino support was higher than White support, it was not statistically different when controlled for partisanship. Conclusion: There is little evidence to suggest that California Latinos support equal opportu- nity policies more strongly than White voters. This lukewarm support may explain the fates of both propositions in the election.

Voting technologies and election administration have become a growth area for academic research. Before the 2000 US presidential election, a strong body of research in election science did not exist. However, in the decades since that close and contested presidential election, researchers from multiple academic disciplines have produced many excellent studies of election procedures, laws, administration, and technologies. This chapter provides an overview of the political science and political administration research literature on voting technologies and election administration in the United States.

How do we ensure a statewide voter registration database’s accuracy and integrity, especially when the database depends on aggregating decentralized, sub-state data with different list maintenance practices? We develop a Bayesian multivariate multilevel model to account for correlated patterns of change over time in multiple response variables, and label statewide anomalies using deviations from model predictions. We apply our model to California’s 22 million registered voters, using 25 snapshots from the 2020 presidential election. We estimate countywide change rates for multiple response variables such as changes in voter’s partisan affiliation and jointly model these changes. The model outperforms a simple interquartile range (IQR) detection when tested with synthetic data. This is a proof-of-concept that demonstrates the utility of the Bayesian methodology, as despite the heterogeneity in list maintenance practices, a principled, statistical approach is useful. At the county level, the total numbers of anomalies are positively correlated with the average election cost per registered voter between 2017 and 2019. Given the recent efforts to modernize and secure voter list maintenance procedures in the For the People Act of 2021, we argue that checking whether counties or municipalities are behaving similarly at the state level is also an essential step in ensuring electoral integrity.

Are political representatives responsive to the public in determining the issues they publicly address? Our paper takes a novel approach to this question with innovative data and state-of-the-art methodology. While previous research on issue responsiveness has focused on the United States and its unique political institutions, we study a multi-party parliamentary setting: the Canadian House of Commons. We focus our analysis on a prominent policy issue: climate change. Using transcripts from the Question Period between April 2006 and June 2021, we measure the attention political parties attribute to the various policy issues. We use Google Trends data to measure policy issues' public salience. We implement an instrumental variable estimation strategy to causally estimate how much climate change's public salience drives elite attention. Our analysis reveals that climate change's public salience significantly affects the attention political parties pay to that policy issue, though with significant partisan heterogeneity.

What spurs voters to vote in person, despite an established universal vote-by-mail (VBM) system and a once-in-a-century pandemic? We explore this question with official voter data from Colorado, a vote-by-mail state since 2013, but where 6% of voters still vote in person. Using multiclass classification, we analyze (1) the choice between voting by mail (VBM), voting in person, and not voting in the 2020 general election, and (2) the choice to switch to in-person voting despite having used VBM in previous cycles. The results suggest that the choice of voting modes is mainly habitual, and local variations of COVID-19 and demographics hardly mattered. Notably, Republican partisanship plays an important role in predicting "switchers" to in-person voting; indeed, the probability of switching to in-person voting was 5.2% conditional on being a Republican as opposed to 1.9% conditional on being a Democrat.

Are political representatives responsive to their constituents in determining the issues they address? Our paper takes a novel approach to this critical question using innovative data and state-of-the-art methodology. While most previous research on issue responsiveness has looked at the United States and its unique political institutions, we study a multi-party, parliamentary setting: Canada. We focus our analysis on two prominent issues: the environment and climate change. Using transcripts from the House of Commons’ Question Period from 2006 to 2021, we measure the attention political parties attribute to the various issues. We use Google Trends data to measure policy issues’ public salience. We implement an instrumental variable estimation strategy to identify and estimate how the environment and climate change’s public salience drives elite attention. Our analysis demonstrates that public salience significantly affects political parties’ interest in the environment and climate change but unveils appreciable partisan heterogeneity in this regard.

Objective: Assuring voter confidence is important for the legitimacy of democratic elections. In this article, we test four hypotheses about the correlates of voter confidence at various levels of election administration. Methods: We take advantage of a large online survey of registered voters in a single election jurisdiction, Orange County (CA), which was implemented immediately after the November 2018 midterm elections. We measure voting experience and social media usage using item response theory as well as voters' perceptions of various election or voter fraud, and estimate their association with voter confidence via logistic regression models. Results: Our results show that voters who cast mail ballots are less confident about their own votes being counted correctly than in‐person voters. For both types of voters, those who have poor experiences with the voting process are much less likely to report confidence in the election. We also find that voters who have strong concerns about election fraud are less likely to report being confident in the election. Our last result indicates that information from news and social media is associated with a decline in voter confidence in election administration at the national level. Conclusion: Given the many conversations about election fraud that have occurred since the 2016 presidential election, this research provides important implications for election administration in future elections in the United States.

Some American states have transitioned to universal voting-by-mail, where all registered voters receive a ballot in the mail. While this practice was growing in popularity prior to the 2020 general election, universal voting-by-mail was suddenly used in a larger number of states due to the COVID-19 pandemic. In this paper, we utilize a unique situation in which registered voters in some legislative districts in Los Angeles County were subjected to universal voting-by-mail in the March 2020 primary, while most of the rest of the Los Angeles County electorate was not. Using difference-in-difference and regression discontinuity designs, we estimate the causal effects of universal voting-by-mail on voter turnout and on who votes. Our results indicate that voter turnout increased by around 3\% for voters who do not automatically receive a ballot in the mail otherwise, and the increase is larger for registered partisan voters than those without a party affiliation.

Objective: We analyze the significant increase in the residual vote rate in the 2016 presidential election. The residual vote rate, which is the percentage of ballots cast in a presidential election that contain no vote for president, rose nationwide from 0.99 to 1.41 percent between 2012 and 2016. Method: We use election return data and public opinion data to examine why the residual vote rate increased in 2016. Results: The primary explanation for this rise is an increase in abstentions, which we argue results primarily from disaffected Republican voters rather than alienated Democratic voters. In addition, other factors related to election administration and electoral competition explain variation in the residual vote rates across states, particularly the use of mail/absentee ballots and the lack of competition at the top of the ticket in nonbattleground states. However, we note that the rise in the residual vote rate was not due to changes in voting technologies. Conclusion: Our research has implications for the use of the residual vote as a metric for studying election administration and voting technologies.

Inferences about individual campaign contributors are limited by how the Federal Election Commission collects and reports data. Only transactions that exceed a cycle-to-date total of $200 are individually disclosed, so that contributions of many donors are unobserved. We contrast visible and "hidden" donors, i.e., small donors who are invisible due to censoring—and routinely ignored in existing research. We use the Sanders presidential campaign in 2016, whose unique campaign structure received money only through an intermediary/conduit committee. These are governed by stricter disclosure statutes, allowing us to study donors who are normally hidden. For Sanders, there were seven hidden donors for every visible donor, and altogether, hidden donors were responsible for 33.8% of Sanders' campaign funds. We show that hidden donors start giving relatively later, with contributions concentrated around early primaries. We suggest that as presidential campaign strategies change towards wooing smaller donors, more research on what motivates them is necessary.

The administration of elections depends crucially upon the quality and integrity of voter registration databases. In addition, political scientists are increasingly using these databases in their research. However, these databases are dynamic and may be subject to external manipulation and unintentional errors. In this article, using data from Orange County, California, we develop two methods for evaluating the quality of voter registration data as it changes over time: (a) generating audit data by repeated record linkage across periodic snapshots of a given database and monitoring it for sudden anomalous changes and (b) identifying duplicates via an efficient, automated duplicate detection, and tracking new duplicates and deduplication efforts over time. We show that the generated data can serve not only to evaluate voter file quality and election integrity but also as a novel source of data on election administration practices.

Who leads and who follows in Congress? By leveraging the Twitter accounts of U.S. House of Representatives members, we develop a new understanding of House leadership power using natural language processing methods in new ways. Formal theoretic work on congressional leadership suggests a tension in legislative party members' policy stances as they balance coordination and information problems. When their coordination problem is more pressing, the model predicts that legislative members will follow their party leaders' policy positions. When the information problem is more acute, party members coordinate and give their leaders direction for the party's agenda. Specifically, we exploit the network structure of retweets to derive measures of House leadership centrality within each party. We also use Joint Sentiment Topic modeling to quantify the discussion space for House members on Twitter. Our results provide support for the theoretical insights.

The integrity of democratic elections, both in the United States and abroad, is an important problem. In this Element, we present a data-driven approach that evaluates the performance of the administration of a democratic election, before, during, and after Election Day. We show that this data-driven method can help to improve confidence in the integrity of American elections.

This paper is the result of a nationwide study of polling place dynamics in the 2016 presidential election. Research teams, recruited from local colleges and universities and located in twenty-eight election jurisdictions across the United States, observed and timed voters as they entered the queue at their respective polling places and then voted. We report results about four specific polling place operations and practices: the length of the check-in line, the number of voters leaving the check-in line once they have joined it, the time for a voter to check in to vote (i.e., verify voter’s identification and obtain a ballot), and the time to complete a ballot. Long lines, waiting times, and times to vote are closely related to time of day (mornings are busiest for polling places). We found the recent adoption of photographic voter identification (ID) requirements to have a disparate effect on the time to check in among white and nonwhite polling places. In majority-white polling places, scanning a voter’s driver’s license speeds up the check-in process. In majority nonwhite polling locations, the effect of strict voter ID requirements increases time to check in, albeit modestly.

Recent, non-peer-reviewed reports and meta-analyses suggest that smoking may reduce the risk of hospitalization with COVID-19, because the prevalence of smoking among hospitalized COVID-19 is less than that of the general population. However, there are two alternative classes of explanations for this phenomenon. Class (1) is the failure to report, or to accurately record, smoking history during emergency hospital admissions and other interviews. Face-to-face interviews can introduce bias into the responses to attitudinal and behavioral questions not present in the self-completion interviews typically used to measure smoking prevalence in the general population. Subjects in face-to-face interviews may be unwilling to admit socially undesirable behavior and attitudes under direct questioning. For example, urine testing of hospitalized patients for cotinine showed that smokers were under-counted by 37% because incoming patients failed to inform staff about their smoking behavior. Class (2), various types of “reverse” causation, including a pre-disposition to avoid smoking among COVID-19 patients with tobacco-related comorbidities, may also contribute to the difference between smoking prevalence in the COVID-19 and general population. Patient cohorts hospitalized with COVID-19 may be less prone to use tobacco than the general population. A potentially robust “reverse causation” hypothesis for reduced prevalence of smokers in the COVID-19 population is enrichment of patients in the population with serious comorbidities that have previously motivated them to quit smoking. We ask whether this “smoking cessation” mechanism accounts for a detectable fraction of the reduced prevalence of smokers in the COVID-19 population. Testing this hypothesis will require a focused research program.

Does attentiveness matter in survey responses? Do more attentive survey participants give higher quality responses? Using data from a recent online survey that identified inattentive respondents using instructed-response items, we demonstrate that ignoring attentiveness provides a biased portrait of the distribution of critical political attitudes and behavior. We show that this bias occurs in the context of both typical closed-ended questions and in list experiments. Inattentive respondents are common and are more prevalent among the young and less educated. Those who do not pass the trap questions interact with the survey instrument in distinctive ways: they take less time to respond; are more likely to report nonattitudes; and display lower consistency in their reported choices. Inattentiveness does not occur completely at random and failing to properly account for it may lead to inaccurate estimates of the prevalence of key political attitudes and behaviors, of both sensitive and more prosaic nature.

Building on past research, we implement a hierarchical latent class model to analyze political participation from a comparative perspective. Our methodology allows simultaneously: (i) estimating citizens’ propensity to engage in conventional and unconventional modes of participation; (ii) classifying individuals into underlying “types” capturing within- and cross-country variations in participation; and (iii) assessing how this classification varies with micro- and macro-level factors. We apply our model to Latin American survey data. We show that our method outperforms alternative approaches used to study participation and derive typologies of political engagement. Substantively, we find that the distribution of participatory types is similar throughout the continent, and that it correlates strongly with respondents’ socio-demographic characteristics and crime victimization.

How do we ensure the accuracy and integrity of a statewide voter registration database, which often depends on aggregating decentralized, sub-state data with different list maintenance practices? We present Bayesian multivariate multilevel model to account for common patterns in local data while detecting anomalous patterns, using Florida as our example. We use monthly snapshots of state's voter database to estimate countywide change rates for multiple response variables (e.g., changes in voter's partisan affiliation), and then jointly model their changes. We show that there is much heterogeneity in how counties manage voter lists, resulting in very different patterns in additions, deletions, or changes of records. Our method identifies several Florida counties with anomalous rates of changes in the 2016 election.

Observers of elections often report that voters have engaged in protest voting. We find that “protest voting” refers to a wide range of behaviors, and we create a taxonomy of these phenomena. Support for fringe or insurgent parties is often labeled as protest voting. Voting theorists have used the term in a completely different way, identifying an unusual type of tactical voting as protest voting. Protest voting also occurs when voters cast blank, null, or spoiled ballots. There are also instances when protest voting is organized and directed by political elites. Finally, several countries provide voters with the option of casting a vote for “None of the Above,” which some see as a form of protest voting. In addition to developing this taxonomy, we discuss the analytical and empirical challenges confronting research on each type of protest voting.

In this article, we study previous experiences with voting technologies, support for e-voting, and perceptions of voter fraud, using data from the 2015 Cooperative Congressional Election Study. We ...

With the discipline’s push toward data access and research transparency (DA-RT), journal replication archives are becoming increasingly common. As researchers work to ensure that replication materials are provided, they also should pay attention to the content—rather than simply the provision—of journal archives. Based on our experience in analyzing and handling journal replication materials, we present a series of recommendations that can make them easier to understand and use. The provision of clear, functional, and well-documented replication materials is key for achieving the goals of transparent and replicable research. Furthermore, good replication materials enhance the development of extensions and related research by making state-of-the-art methodologies and analyses more accessible.

The counting of votes in contemporary American elections is usually not completed on Election Night. There has been an increasing tendency for vote shares to shift toward Democratic candidates after Election Day in general elections, in particular, in recent U.S. elections. Leveraging important snapshots of precinct-level election returns and precinct-level demographic and political composition from Orange County, California, we conduct the first full-fledged analysis of the potential drivers of vote share shifts. Using an original large-scale post-election survey and unique snapshots of individual-level administrative records, we also provide the first analysis of the characteristics of voters whose ballots were tallied later versus earlier in the process. Far from being anomalous, our results indicate that the shifts are consistent with underlying precinct voter compositions and the order of precinct and mail ballot processing at the individual level in accordance with election administration practices. We find the same driving forces in North Carolina and Colorado, and discuss the consequences of the “Blue Shift” for public concerns about election integrity as states push policy changes regarding access to voting by mail.

Social media data is now widely used by many academic researchers. However, long-term social media data collection projects, which most typically involve collecting data from public-use APIs, often encounter issues when relying on local area network servers (LANs) to collect high-volume streaming social media data over long periods of time. In this paper, we present a cloud-based data collection, pre-processing, and archiving infrastructure, and argue that this system mitigates or resolves the problems most typically encountered when running social media data collection projects on LANs at minimal cloud-computing costs. We show how this approach works in different cloud computing architectures, and how to adapt the method to collect streaming data from other social media platforms. The contribution of our research lies in the development of methodologies that researchers can use to monitor and analyze phenomena including how public opinion and public discourse change in response to events, monitoring the evolution and change of misinformation campaigns, and studying how organizations and entities change how they present and frame information online.

There at least two important questions about voter behavior in California's blanket primary. The first is: How many voters took the opportunity to cast a ballot for a candidate of a party different than that of the voter's registration or identification? The second question is: Why did these crossover voters decide to defect from their own party's nomination campaign and support a candidate from another party? In this chapter, we focus on these two questions at the Assembly district level.

Social scientists have long made use of advanced computational techniques in their research. There have been two very different applications of computational technologies in social science: one largely about simulation of complex political interactions, the other focused on the use of computational approaches with data to estimate models of political phenomenon. In this chapter, our emphasis is generally on the latter area of computational social science, and while we provide some grounding in the early and foundational work in this area, we mainly discuss recent research in computational social science applications involving data and model estimation.

Supplemental material, appendix_revised_redacted for Evaluating the Quality of Changes in Voter Registration Databases by Seo-young Silvia Kim, Spencer Schneider and R. Michael Alvarez in American Politics Research

While inferences of traits from unfamiliar faces prominently reveal stereotypes, some facial inferences also correlate with real-world outcomes. We investigated whether facial inferences are associated with an important real-world outcome closely linked to the face bearer’s behavior: political corruption. In four preregistered studies ( N = 325), participants made trait judgments of unfamiliar government officials on the basis of their photos. Relative to peers with clean records, federal and state officials convicted of political corruption (Study 1) and local officials who violated campaign finance laws (Study 2) were perceived as more corruptible, dishonest, selfish, and aggressive but similarly competent, ambitious, and masculine (Study 3). Mediation analyses and experiments in which the photos were digitally manipulated showed that participants’ judgments of how corruptible an official looked were causally influenced by the face width of the stimuli (Study 4). The findings shed new light on the complex causal mechanisms linking facial appearances with social behavior.

Using data from eight recent California initiatives and data provided by the California Secretary of State's Office, this research explores the geographic source of signatures and their distribution across counties, investigates both total signatures and valid signatures, and presents a regression analysis to study how characteristics of counties relate to the number of signatures gathered. The findings indicate a high rate of equity in the distribution of signature gathering and little demographic targeting across measures. The study also finds that a variety of social and political factors influence the number of total and valid signatures across counties, though the results are more consistent for the former.

Polling and survey methods is an interdisciplinary activity and includes actors in all areas of society, including academia, government, and the private sector. Designing, implementing, and analyzing high-quality, accurate, and cost-effective polls and surveys requires a combination of skills and methodological perspectives. Despite the well-publicized issues that have cropped up in recent political polling, a great deal is known today about how to collect high-quality polling and survey data even in complex and difficult environments. Quality surveys and good survey data are important because social scientists are only as good as the data produced. Therefore, it is critical to follow best practices and guidelines and help researchers assess a variety of factors to make good choices when collecting and analyzing data. Equally important is transmitting those results to others in a clear and accessible manner.

Supplemental material, Appendix for Answering Questions About Race: How Racial and Ethnic Identities Influence Survey Response by Marisa Abrajano and R. Michael Alvarez in American Politics Research

Supplemental material, LinSupplementalMaterial for Inferring Whether Officials Are Corruptible From Looking At Their Faces by Chujun Lin, Ralph Adolphs and R. Michael Alvarez in Psychological Science

Objective. This article examines public opinion on the effectiveness and consequences of voter identification laws, focusing on the core issue in the Supreme Court's reasoning in the 2008 case that upheld an Indiana photo-ID law, Crawford v. Marion County Election Board. Method. We use a unique survey from New Mexico, where voter identification policies have recently undergone important changes. Questions in the survey examine whether voters think that ID laws protect against fraud and prevent legitimate participation, which point of view voters find more compelling, and whether attitudes toward voter identification are related to voter confidence. Results. Most voters think that voter ID laws prevent fraud, but many voters think that ensuring access to the polls is more important than preventing fraud. Among other variables that explain differences among individuals, partisanship plays an important role. Conclusion. The framing of voter identification policies plays an important role in how such laws are interpreted by the public and Republicans are especially concerned about fraud in elections.

We examine the quality of two probability-based polls, one interviewer administered (telephone) and one self-administered (Internet and mail mixed mode survey). The polls use the same sampling frame (registered voters) and the same questions. First, we examine the representativeness of both surveys using information known about the population, and although we find important differences between the two in terms of sampling and nonresponse bias, we also find that both surveys represent the underlying population despite low response rates. We also test for mode effects between surveys due to social desirability and how it influences nondifferentiation or satisficing. Using a variety of methods (t-tests, multivariate regression, and genetic propensity matching), we find evidence that the presence of an interviewer alters response patterns on ego-driven questions. The implications of our work are important, due to the increasing popularity of mixed mode surveys. Researchers need to be methodologically sensitive to these differences when analyzing surveys that allow for different response modes.

Over the last decade the survey environment has been rapidly changing, creating new opportunities and new challenges for survey methodologists. These include: relatively low response among all contact modes and designs; the rapid replacement of landline telephones for mobile and smart phones; the integration of new and different types of data for sampling and new sampling methods; the use of different survey interview modes; how to study behaviors and opinions about sensitive topics; and the development of survey designs for experts and opinion leaders. All have implications for data quality and for our ability to consistently and reliably answer substantive and theoretical questions about politics and society. Obviously, a comprehensive survey of how survey methodologists are advancing new approaches to deal with this vast array of challenges and opportunities is not possible in a mini-symposium in Political Analysis. Nevertheless, in this Mini-Symposium on Advances in Survey Methodology, we include five papers that focus on new directions that survey methodologists, especially those working in political science, are developing in response to the changing environment.

Objective: This article studies the effect of initiative signature-gathering campaigns on political participation within a state. Methods: Using data on signatures gathered for eight initiatives and four different elections, we conduct grouped logit regression to test whether counties that are subject to more intense signature-gathering campaigns, measured by the number of signatures gathered per capita, experience greater levels of turnout and ballot roll-off in the subsequent election. Results: Our analysis provides evidence that the intensity of signature-gathering campaigns has a moderate effect on both of these measures of political participation. Conclusion: Initiative campaigns influence turnout not just at the state level, but variation in campaigns leads to differences within states as well.

Voting technologies frame the voting experience. Different ways of presenting information to voters, registering voter choices and counting ballots may change the voting experience and cause individuals to re-evaluate the legitimacy of the electoral process. Yet few field experiments have evaluated how voting technologies affect the voting experience. This article uses unique data from a recent e-voting field experiment in Salta, Argentina to study these questions. It employs propensity-score matching methods to measure the causal effect of replacing traditional voting technology with e-voting on the voting experience. The study's main finding is that while e-voters perceive the new technology as easier to use and more likely to register votes as intended—and support replacing traditional voting technologies with e-voting—the new technologies also raise some concerns about ballot secrecy. Fil: Alvarez, R. Michael. California Institute of Technology; Estados Unidos Fil: Levin, Inés. University of Georgia; Estados Unidos Fil: Pomares, Julia. Center for the Implementation of Public Policies Promoting Equity and Growth; Argentina Fil: Leiras, Marcelo Carlos César. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

DOI 10.1515/cjpp-2012-0024 Calif. J. Politics Policy 2013; 5(1): 47–66 Research Article R. Michael Alvarez and J. Andrew Sinclair* Who Are California’s “Decline to State” Voters? Abstract: California has a large, and growing, number of voters who decline to affiliate with a major political party. This study uses a large sample survey from the 2010 election cycle to ask: who are these “decline to state” voters? This article explores their positions on issues, their attitudes toward parties, their opinions on government, their political knowledge and involvement, their 2010 voting preferences, and their voting behavior in general. We find the data supports a nuanced view of California’s “DTS” voters – in some ways more like “independ- ents” and in other ways strikingly partisan. Keywords: California politics; independent voters; decline to state; DTS *Corresponding author: J. Andrew Sinclair, California Institute of Technology, Pasadena, CA, USA, e-mail: jsinclair08@gmail.com R. Michael Alvarez, California Institute of Technology, Pasadena, CA, USA 1 Introduction In June 2012, the unaffiliated voters of California had a new opportunity to influence politics through the “top-two” primary. These unaffiliated (or “non- partisan” or “decline to state”) voters are widely assumed to be “independents”, and under the new law, they could play a central role in selecting candidates. As politicians and pundits examine the results of this new system though, mis- understanding the unaffiliated voters will muddle the picture. In this article, we argue that these voters should not be treated as uniform group of political independents. Assumptions about the unaffiliated voters frame our expectations for the new primary, passed as Proposition 14 in 2010. The Los Angeles Times, in an endorsement of this Proposition, postulated, “It’s a route to more pragmatic officeholders and elections controlled more by voters than by political parties – which is why the Democratic and Republican parties both oppose it so

Rapid decisions about political candidates, made solely on the basis of candidate appearance, associate with real electoral outcomes. A prevailing interpretation is that these associations result from heuristic cognitive processing of cues from the face to yield a judgment about the candidate, processing that is shared by both voters and experimental participants. Here, we report findings suggesting that nonfacial aspects of a candidate's appearance are important cues for voter decision making. We asked participants to look at pairs of candidate images and decide (a) whom to vote for (SimVote), (b) who looks more physically threatening (Threat), and (c) who looks more competent to hold congressional office (Competence). When participants saw only the candidates' faces, there was no association between their decisions and electoral outcomes, except for Threat. Yet when participants saw the candidate images with the faces removed, there was a strong association between their decisions and voters' decisions, for all decision types. This suggests that the appearance-related heuristics that some voters use to guide their decisions may include mental schemas for processing appearance cues other than those associated with facial features. Such schema-based processing has implications for understanding the neurobiological system underlying thin-slice decisions from appearance alone.

Empirical researchers studying party systems often struggle with the question of how to count parties. Indexes of party system fragmentation used to address this problem (e.g., the effective number of parties) have a fundamental shortcoming: since the same index value may represent very different party systems, they are impossible to interpret and may lead to erroneous inference. We offer a novel approach to this problem: instead of focusing on index measures, we develop a model that predicts theentire distributionof party vote-shares and, thus, does not require any index measure. First, a model of party counts predicts the number of parties. Second, a set of multivariatetmodels predicts party vote-shares. Compared to the standard index-based approach, our approach helps to avoid inferential errors and, in addition, yields a much richer set of insights into the variation of party systems. For illustration, we apply the model on two data sets. Our analyses call into question the conclusions one would arrive at by the index-based approach. Software is provided to implement the proposed model.

To what extent did the extensive flooding caused by Hurricane Katrina affect voter participation in the 2006 mayoral election? This article uses voting record data from 20 election cycles, GIS-coded flood-depth data, and census data to examine the voting behavior of registered voters in New Orleans before and after Hurricane Katrina. We use a variety of statistical techniques, primarily propensity score matching methods, to examine how flooding affected mayoral turnout. We find that flooding decreased participation, but registered voters who experienced more than 6 ft of flooding were more likely to participate in the election than those who experienced less flooding. This finding confirms that increasing the cost of voting decreases turnout and suggests several mechanisms motivating an expressive component of voting behavior. Our results indicate there is a complex relationship between participation and the costs and benefits of turnout. Our findings about the characteristics of the voters who participated in the mayoral election provide insights into the scope of change for the political landscape of New Orleans.

We study public opinions about convenience voting reforms, using a unique state-by-state survey conducted in the 2008 presidential election. Our analysis of the American voting public's support for convenience voting reforms provides a variety of important insights into the potential direction of innovations in the electoral process in the near future. First, we find that the most prominent convenience voting reforms have mixed support. These include attitudes toward automatic voter registration, Election Day voter registration, and moving Election Day to a weekend. These reforms do not have majority support among all voters nationwide, but some enjoy majority support within some states. Second, we find that Internet voting and voting by mail do not receive a great deal of support from American voters. There is no state in which a majority of voters supports Internet voting, nor are there states where expanded vote-by-mail has majority support (other than states which have already implemented the...

The authors analyze the choice of voting mode in the 2008 presidential election using a large-sample survey with national coverage that allows a new perspective of convenience voting. Most importantly, they make clear distinctions among the major forms of convenience voting and demonstrate that not all “convenience voters” share the same attributes. In addition, the authors find little support for the hypothesis that convenience voting methods have partisan implications, despite the differences among mail, early, and election-day voters. Results like these have important implications for future moves toward convenience voting and the design of new outreach campaigns.

We analyze trust in electronic voting in Latin America using data from two field experiments conducted in Argentina and Colombia. We find that voters generally exhibit high levels of confidence in e-voting, although this depends on individual characteristics such as age and educa- tion, as well as on the particular type of technology used. We contrast our findings with those from industrialized democracies and show that conclusions derived from American and European e-voting experiences cannot be directly extrapolated to the Latin American context. Overall, our results suggest that e-voting could provide an attractive alternative to traditional voting procedures in the region.

Ordinal variables—categorical variables with a defined order to the categories, but without equal spacing between them—are frequently used in social science applications. Although a good deal of research exists on the proper modeling of ordinal response variables, there is not a clear directive as to how to model ordinal treatment variables. The usual approaches found in the literature for using ordinal treatment variables are either to use fully unconstrained, though additive, ordinal group indicators or to use a numeric predictor constrained to be continuous. Generalized additive models are a useful exception to these assumptions (Beck and Jackman 1998). In contrast to the generalized additive modeling approach, we propose the use of a Bayesian shrinkage estimator to model ordinal treatment variables. The estimator we discuss in this paper allows the model to contain both individual group level indicators and a continuous predictor. In contrast to traditionally used shrinkage models that pull the data toward a common mean, we use a linear model as the basis. Thus, each individual effect can be arbitrary, but the model “shrinks” the estimates toward a linear ordinal framework according to the data. We demonstrate the estimator on two political science examples: the impact of voter identification requirements on turnout (Alvarez, Bailey, and Katz 2007), and the impact of the frequency of religious service attendance on the liberality of abortion attitudes (e.g., Singh and Leahy 1978, Tedrow and Mahoney 1979, Combs and Welch 1982).