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Local election officials are the administrators of democracy, but we know little about their views. This paper draws from two national surveys of local election officials. The authors find that local election officials generally support the goals of the federal Help America Vote Act but are less enthusiastic about the actual impact of the legislation. Implementation theory helps explain their evaluation of federal reforms. Goal congruence with reform mandates, resource availability, and a willingness to accept federal involvement predicts support for these reforms. Federal policy changes have promoted electronic systems, and some of the authors' findings are relevant to research on e‐government. Users of electronic voting machines tend to have high confidence in them despite the significant criticism the machines have faced. Local election officials who support e‐government generally are more likely to more positively evaluate federal reforms.

Objective. Our objective is to explain how scientists interpret less‐than‐certain scientific findings to inform policymakers' choices on controversial science policy issues. We focus on two particularly difficult policy cases concerning global climate change and low‐dose radiation protection.Methods. Our method is to analyze data from a unique multination survey of scientists to analyze the ways their views about what is scientifically correct are translated into judgments about appropriate policy. The surveys asked scientists, randomly drawn from U.S. and E.U. subscribers to the journal Science, to indicate the "most likely" relationships between greenhouse gas emissions and average global temperatures and between radiation dose and incidence of cancer in humans. Follow‐up questions asked for their judgments about appropriate policy targets for reductions in greenhouse gas emission and safety standards for radiation exposure. The data permit analysis of the relationships between scientific certainty and policy judgments in these two cases.Results. Our results shed light on when and how scientists reach precautionary policy conclusions, demonstrating that scientists' application of precaution is dependent on context. In the case of radiation protection, greater certainty is associated with less precaution. But with respect climate change, we found the opposite relationship.Conclusions. We conclude with a discussion of the implications for the role of scientists, and scientific advice, in the policy process.

ObjectiveOur objective is to explain how scientists interpret less-than-certain scientific findings to inform policymakers' choices on controversial science policy issues. We focus on two particularly difficult policy cases concerning global climate change and low-dose radiation protection. MethodsOur method is to analyze data from a unique multination survey of scientists to analyze the ways their views about what is scientifically correct are translated into judgments about appropriate policy. The surveys asked scientists, randomly drawn from U.S. and E.U. subscribers to the journal Science , to indicate the "most likely" relationships between greenhouse gas emissions and average global temperatures and between radiation dose and incidence of cancer in humans. Follow-up questions asked for their judgments about appropriate policy targets for reductions in greenhouse gas emission and safety standards for radiation exposure. The data permit analysis of the relationships between scientific certainty and policy judgments in these two cases. ResultsOur results shed light on when and how scientists reach precautionary policy conclusions, demonstrating that scientists' application of precaution is dependent on context. In the case of radiation protection, greater certainty is associated with less precaution. But with respect climate change, we found the opposite relationship. ConclusionsWe conclude with a discussion of the implications for the role of scientists, and scientific advice, in the policy process. Adapted from the source document.

In the face of the reemerging threat of preventable diseases and the simultaneous vaccine risk controversy, what explains variations in Americans' policy preferences regarding childhood vaccinations? Using original data from a recent nationwide Internet survey of 1,213 American adults, this research seeks to explain differing public opinions on childhood vaccination policies and related issues of governance. As Mary Douglas and Aaron Wildavsky's grid‐group cultural theory of policy preference formation suggests, cultural biases have a significant impact on the formation of preferences toward various vaccination policies. Hierarchs are in support of mandatory vaccination, oppose religious and philosophical exemption, and believe the government should preside over vaccination‐related decisions. Fatalists strike a bold contrast in their opposition to mandatory vaccination policy and support for religious and philosophical exemptions and the role of parents in deciding on vaccinations. Falling between hierarchs and fatalists, egalitarian support for vaccinations is stronger than individualists'.

In Federalist no. 65, Alexander Hamilton wrote that the impeachment process is a decidedly political one. We use data from a national survey conducted in September and October 1998 to examine explanations for Bill Clinton's survival of the impeachment crisis: the robust economy, his own high popular standing with the public, and the concomitantly lower public evaluations of his principal investigators, Independent Counsel Kenneth Starr and the Republican-controlled U.S. Congress. Our analysis demonstrates that the performance of the U.S. economy did directly influence public support for impeachment, resignation, continued congressional hearings, and censure (four potential punishment options), but not in the manner most often hypothesized. More favorable assessments of the U.S. economy actually were related to higher levels of support for punishing the president. Evaluations of the president proved to be a double-edged sword. Although higher evaluations of Clinton's personal job approval ratings and of his personal ethics ratings are related to lower levels of support for punishment, Clinton benefited more from the former than the latter, as his approval ratings were high while the public held considerable doubts about his ethics. Finally, we show that higher public evaluations of Clinton's primary investigators, Starr and the U.S. Congress, were related to higher levels of support for punishing the president. As both actors had an exceedingly low average approval rating, however, this dynamic worked to Clinton's advantage. Adapted from the source document.

"For decades, public expectations of U.S. presidents have become increasingly excessive and unreasonable. Despite much anecdotal evidence, few scholars have attempted to test the expectations gap thesis empirically. This is the first systematic study to prove the existence of the expectations gap and to identify the factors that contribute to the public's disappointment in a given president. Using data from five original surveys, the authors confirm that the expectations gap is manifest in public opinion. It leads to lower approval ratings, lowers the chance that a president will be reelected, and even contributes to the success of the political party that does not hold the White House in congressional midterm elections. This study provides important insights not only on the American presidency and public opinion, but also on citizens' trust in government"--

"For decades, public expectations of U.S. presidents have become increasingly excessive and unreasonable. Despite much anecdotal evidence, few scholars have attempted to test the expectations gap thesis empirically. This is the first systematic study to prove the existence of the expectations gap and to identify the factors that contribute to the public's disappointment in a given president. Using data from five original surveys, the authors confirm that the expectations gap is manifest in public opinion. It leads to lower approval ratings, lowers the chance that a president will be reelected, and even contributes to the success of the political party that does not hold the White House in congressional midterm elections. This study provides important insights not only on the American presidency and public opinion, but also on citizens' trust in government"--

Field survey experiments often measure amorphous concepts in discretely ordered categories, with postsurvey analytics that fail to account for the discrete attributes of the data. This article demonstrates the use of discrete distribution tests, specifically the chi-square test and the discrete Kolmogorov—Smirnov (KS) test, as simple devices for comparing and analyzing ordered responses typically found in surveys. In Monte Carlo simulations, we find the discrete KS test to have more power than the chi-square test when distributions are right or left skewed, regardless of the sample size or the number of alternatives. The discrete KS test has at least as much power as the chi-square, and sometimes more so, when distributions are bi-modal or approximately uniform and samples are small. After deriving rules of usage for the two tests, we implement them in two cases typical of survey analysis. Using our own data collected after Hurricanes Katrina and Rita, we employ our rules to both validate and assess treatment effects in a natural experimental setting.

Social scientists have argued about the role of political beliefs in highly charged policy debates among scientific experts. In debates about environmental hazards, the focus of contention is likely to rest on the appropriate scientific assumptions to inform safety standards. When scientific communities are polarized, one would expect to find systematic differences among combatants in the choice of appropriate assumptions, and variation in the application of "precaution" in standard setting. We test this proposition using an experiment applied in a mail survey format to groups of scientists from opposing sides of the nuclear policy debate. Questions were asked about the role of political, social, and epistemological beliefs in reaching scientific and policy judgments about the relationship between radiation dose and cancer incidence in human populations. We find that the precautionary tendency is pervasive regardless of whether the scientist is associated with a putatively pro‐ or anti‐nuclear group. Using a multinomial logit model, we explain a modest percentage of the variation in the choice of preferred judgments about safety standards, but find that distinct sets of political and social values are significantly associated with policy positions among scientists. Implications for scientific advice to policymakers are discussed.