Privatized Democracy: The Role of Election Services Vendors in the United States

2020 ◽  
Vol 48 (6) ◽  
pp. 705-708 ◽  
Author(s):  
Nadine Suzanne Gibson

Election equipment in the United States is exclusively purchased from private-sector vendors. When a jurisdiction purchases voting equipment, it is actually purchasing the hardware and software along with a variety of services for the initial implementation and long-term maintenance and support of the system. Election services constitute roughly one third of county-level election expenditures. The results of logistic regression analyses estimating the likelihoods of county purchases of different election services from election services vendors suggest a relationship between purchasing decisions and county demographics, namely the size of the minority population. Localities in states with centralized contracting systems were also substantially more likely to purchase all forms of vendor services.

2018 ◽  
Vol 120 (9) ◽  
pp. 1-28
Author(s):  
Brady K. Jones

Background Creating greater stability in the teacher labor force and improving teacher quality is an important education policy priority in the United States. While there is a robust literature on the external, environmental reasons teachers stay in or leave the occupation, little is known about the role internal, person-level factors play in teacher retention, especially among academically elite teachers. Focus of Study This study explores the role of personality, holistically defined, in teacher commitment. Participants The sample for this study consists of 107 graduates of a single teacher preparation program. They are classified as “academically elite,” as this preparation program is very selective and demands high GRE scores. Research Design Discriminant function and regression analyses are used to test which of a rich set of personality measures, both traditional self-report measures and coded narrative accounts of life and career high points, predict long-term commitment to teaching in this sample. Results Discriminant function analysis exploring differences between very long-term committers (15+ years) and short-term committers (7- years) suggests that long-term committers are distinguished by a “special kind of ambition”: they set goals that are both more difficult and more prosocial than their counterparts with a shorter commitment to the occupation, and in personal narratives they more often show “enlightened self-interest,” a combination of self-interest/self-promotion with concern for and connection to others. In addition, regression analyses show that these personality variables significantly predict retention in the sample as a whole, even when controlling for school advantage. Conclusions These results provide evidence that personality does play an important role in teachers’ occupational commitment, call into question pervasive stereotypes in the United States of teachers as unambitious, and suggest ways academically elite teachers might be able to shift the ways they think about their work in order to sustain themselves in the occupation.


2014 ◽  
Vol 6 (4) ◽  
pp. 318-332
Author(s):  
Kathryn Simms

This study evaluates the effectiveness of extant financial education in the United States (i.e., employer-provided education, financial education in high school, and financial education in college) via linear regression and logistic regression analyses conducted on data from the 2012 National Financial Capability Study (NFCS). It concludes that although formal financial education is associated with improved financial literacy above and beyond general educational attainment, employer-provided education and financial education in US high schools are frequently associated directly or indirectly with increased odds of an adverse personal financial event (i.e., foreclosure, bankruptcy, or being underwater). Financial education in college is either not significant or is indirectly associated with reduced odds of some these adverse events. Given these findings, it seems that generating and evaluating rigorous empirical evidence about effective methods and curriculums for teaching financial education should be an immediate policy priority rather than requiring universal financial education in haste. However, requiring universal financial education may be a worthy long-term goal, after these more immediate policy needs are achieved. These findings and recommendations contribute to the literature by helping to resolve relatively intense debate among researchers about the effectiveness of financial education via the first study that examines the efficacy of financial literacy in a nationally representative, US database.


Public Voices ◽  
2017 ◽  
Vol 9 (2) ◽  
pp. 9
Author(s):  
John C. Morris

The role of the policy entrepreneur in the policy process forms an integral part of our understanding of the formulation and implementation of policy in the United States. For all its theoretical importance, however, little work has been done to develop or test the propositions of entrepreneurship offered by Kingdon (1984). By examining the life of Ansel Adams (1902-1984), this paper explores more fully the concept of policy entrepreneurship and seeks to develop a more robust concept that accounts for the long-term, diffuse series of activities that precede Kingdon’s “stream coupling” in the policy process. The analysis suggests that such an approach offers some promise for capturing a broader spectrum of policy activity.


Author(s):  
Alasdair Roberts

This chapter assesses the role of planning in the design of governance strategies. Enthusiasm for large-scale planning—also known as overall, comprehensive, long-term, economic, or social planning—boomed and collapsed in twentieth century. At the start of that century, progressive reformers seized on planning as the remedy for the United States' social and economic woes. By the end of the twentieth century, enthusiasm for large-scale planning had collapsed. Plans could be made, but they were unlikely to be obeyed, and even if they were obeyed, they were unlikely to work as predicted. The chapter then explains that leaders should make plans while being realistic about the limits of planning. It is necessary to exercise foresight, set priorities, and design policies that seem likely to accomplish those priorities. Simply by doing this, leaders encourage coordination among individuals and businesses, through conversation about goals and tactics. Neither is imperfect knowledge a total barrier to planning. There is no “law” of unintended consequences: it is not inevitable that government actions will produce entirely unexpected results. The more appropriate stance is modesty about what is known and what can be achieved. Plans that launch big schemes on brittle assumptions are more likely to fail. Plans that proceed more tentatively, that allow room for testing, learning, and adjustment, are less likely to collapse in the face of unexpected results.


2020 ◽  
pp. 135910532092516
Author(s):  
Julia Schindler ◽  
Simon Schindler ◽  
Stefan Pfattheicher

This study tested the idea that faith in intuition (people’s reliance on their intuition when making judgments or decisions) is negatively associated with vaccination attitudes in the U.S. populace. Intuition is an implicit, affective information processing mode based on prior experiences. U.S. citizens have few threatening experiences with vaccines because vaccination coverage for common vaccine-preventable diseases is high in the United States. Experiences with vaccination-side effects, however, are more prevalent. This is likely to shape an intuition that favors refusal over vaccination. Results of multiple regression analyses support this supposition. With increasing faith in intuition, people’s vaccination attitudes become less favorable.


2009 ◽  
Vol 110 (1) ◽  
pp. 89-94 ◽  
Author(s):  
Eric B. Rosero ◽  
Adebola O. Adesanya ◽  
Carlos H. Timaran ◽  
Girish P. Joshi

Background Malignant hyperthermia (MH) is a potentially fatal pharmacogenetic disorder with an estimated mortality of less than 5%. The purpose of this study was to evaluate the current incidence of MH and the predictors associated with in-hospital mortality in the United States. Methods The Nationwide Inpatient Sample, which is the largest all-payer inpatient database in the United States, was used to identify patients discharged with a diagnosis of MH during the years 2000-2005. The weighted exact Cochrane-Armitage test and multivariate logistic regression analyses were used to assess trends in the incidence and risk-adjusted mortality from MH, taking into account the complex survey design. Results From 2000 to 2005, the number of cases of MH increased from 372 to 521 per year. The occurrence of MH increased from 10.2 to 13.3 patients per million hospital discharges (P = 0.001). Mortality rates from MH ranged from 6.5% in 2005 to 16.9% in 2001 (P < 0.0001). The median age of patients with MH was 39 (interquartile range, 23-54 yr). Only 17.8% of the patients were children, who had lower mortality than adults (0.7% vs. 14.1%, P < 0.0001). Logistic regression analyses revealed that risk-adjusted in-hospital mortality was associated with increasing age, female sex, comorbidity burden, source of admission to hospital, and geographic region of the United States. Conclusions The incidence of MH in the United States has increased in recent years. The in-hospital mortality from MH remains elevated and higher than previously reported. The results of this study should enable the identification of areas requiring increased focus in MH-related education.


Author(s):  
Xiao Wu ◽  
Rachel C Nethery ◽  
M Benjamin Sabath ◽  
Danielle Braun ◽  
Francesca Dominici

AbstractObjectivesUnited States government scientists estimate that COVID-19 may kill tens of thousands of Americans. Many of the pre-existing conditions that increase the risk of death in those with COVID-19 are the same diseases that are affected by long-term exposure to air pollution. We investigated whether long-term average exposure to fine particulate matter (PM2.5) is associated with an increased risk of COVID-19 death in the United States.DesignA nationwide, cross-sectional study using county-level data.Data sourcesCOVID-19 death counts were collected for more than 3,000 counties in the United States (representing 98% of the population) up to April 22, 2020 from Johns Hopkins University, Center for Systems Science and Engineering Coronavirus Resource Center.Main outcome measuresWe fit negative binomial mixed models using county-level COVID-19 deaths as the outcome and county-level long-term average of PM2.5 as the exposure. In the main analysis, we adjusted by 20 potential confounding factors including population size, age distribution, population density, time since the beginning of the outbreak, time since state’s issuance of stay-at-home order, hospital beds, number of individuals tested, weather, and socioeconomic and behavioral variables such as obesity and smoking. We included a random intercept by state to account for potential correlation in counties within the same state. We conducted more than 68 additional sensitivity analyses.ResultsWe found that an increase of only 1 μg/m3 in PM2.5 is associated with an 8% increase in the COVID-19 death rate (95% confidence interval [CI]: 2%, 15%). The results were statistically significant and robust to secondary and sensitivity analyses.ConclusionsA small increase in long-term exposure to PM2.5 leads to a large increase in the COVID-19 death rate. Despite the inherent limitations of the ecological study design, our results underscore the importance of continuing to enforce existing air pollution regulations to protect human health both during and after the COVID-19 crisis. The data and code are publicly available so our analyses can be updated routinely.Summary BoxWhat is already known on this topicLong-term exposure to PM2.5 is linked to many of the comorbidities that have been associated with poor prognosis and death in COVID-19 patients, including cardiovascular and lung disease.PM2.5 exposure is associated with increased risk of severe outcomes in patients with certain infectious respiratory diseases, including influenza, pneumonia, and SARS.Air pollution exposure is known to cause inflammation and cellular damage, and evidence suggests that it may suppress early immune response to infection.What this study addsThis is the first nationwide study of the relationship between historical exposure to air pollution exposure and COVID-19 death rate, relying on data from more than 3,000 counties in the United States. The results suggest that long-term exposure to PM2.5 is associated with higher COVID-19 mortality rates, after adjustment for a wide range of socioeconomic, demographic, weather, behavioral, epidemic stage, and healthcare-related confounders.This study relies entirely on publicly available data and fully reproducible, public code to facilitate continued investigation of these relationships by the broader scientific community as the COVID-19 outbreak evolves and more data become available.A small increase in long-term PM2.5 exposure was associated with a substantial increase in the county’s COVID-19 mortality rate up to April 22, 2020.


10.2196/23902 ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. e23902
Author(s):  
Kevin L McKee ◽  
Ian C Crandell ◽  
Alexandra L Hanlon

Background Social distancing and public policy have been crucial for minimizing the spread of SARS-CoV-2 in the United States. Publicly available, county-level time series data on mobility are derived from individual devices with global positioning systems, providing a variety of indices of social distancing behavior per day. Such indices allow a fine-grained approach to modeling public behavior during the pandemic. Previous studies of social distancing and policy have not accounted for the occurrence of pre-policy social distancing and other dynamics reflected in the long-term trajectories of public mobility data. Objective We propose a differential equation state-space model of county-level social distancing that accounts for distancing behavior leading up to the first official policies, equilibrium dynamics reflected in the long-term trajectories of mobility, and the specific impacts of four kinds of policy. The model is fit to each US county individually, producing a nationwide data set of novel estimated mobility indices. Methods A differential equation model was fit to three indicators of mobility for each of 3054 counties, with T=100 occasions per county of the following: distance traveled, visitations to key sites, and the log number of interpersonal encounters. The indicators were highly correlated and assumed to share common underlying latent trajectory, dynamics, and responses to policy. Maximum likelihood estimation with the Kalman-Bucy filter was used to estimate the model parameters. Bivariate distributional plots and descriptive statistics were used to examine the resulting county-level parameter estimates. The association of chronology with policy impact was also considered. Results Mobility dynamics show moderate correlations with two census covariates: population density (Spearman r ranging from 0.11 to 0.31) and median household income (Spearman r ranging from –0.03 to 0.39). Stay-at-home order effects were negatively correlated with both (r=–0.37 and r=–0.38, respectively), while the effects of the ban on all gatherings were positively correlated with both (r=0.51, r=0.39). Chronological ordering of policies was a moderate to strong determinant of their effect per county (Spearman r ranging from –0.12 to –0.56), with earlier policies accounting for most of the change in mobility, and later policies having little or no additional effect. Conclusions Chronological ordering, population density, and median household income were all associated with policy impact. The stay-at-home order and the ban on gatherings had the largest impacts on mobility on average. The model is implemented in a graphical online app for exploring county-level statistics and running counterfactual simulations. Future studies can incorporate the model-derived indices of social distancing and policy impacts as important social determinants of COVID-19 health outcomes.


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