PANDEMIC POLITICS
The COVID-19 pandemic has generated vitriolic debates over the appropriate balance between public health mandates and civil liberties. My NSF-funded research analyzes public perceptions of health-rights tradeoffs as well as determinants of vaccine hesitancy, the dynamics of blame attribution, and emergent forms of anti-vax fringe fluidity. Additional research examines the securitization of health and implications for asylum policy.
Due to the COVID-19 pandemic, emergency laws and powers on a scale not seen since the 9/11/2001 terrorist attacks have been enacted, with implications for the everyday lives of Americans. Building on research on public perceptions of trade-offs between security protections and restrictions on personal freedoms in the post-9/11 environment, this project will use surveys that explore COVID-19 pandemic mitigation efforts that potentially constrain legal freedoms. As a result, this research will determine popular tolerance for perceived public health protections versus legal restrictions.
Employing several waves of survey analyses of a nationally representative sample of the US population, this project will explore public views on government actions taken during the COVID-19 pandemic. Econometric models and machine learning techniques will be utilized to analyze the survey data. Findings will have implications on several theoretical literatures across disciplines, which will inform policy makers, scholars, and the public of the balance between competing public health imperatives and legal protections.
This project is jointly supported by the Law and Science Program (LS) and the Office of Multidisciplinary Activities (SMA) in the Directorate for Social, Behavioral & Economic Sciences (SBE).
Designing effective public health campaigns to combat COVID-19 vaccine hesitancy requires an understanding of i) who the vaccine hesitant population is, and ii) the determinants of said population’s hesitancy. While researchers have identified a number of variables associated with COVID-19 vaccine hesitancy that could inform such campaigns, little is known about the cumulative or relative predictive power of these factors. In this article, we employ a machine learning model to analyze online survey data collected from 3,353 respondents. The model incorporates an array of variables that have been shown to impact vaccine hesitancy, allowing us to i) test how well we can predict vaccine hesitancy, and ii) compare the relative predictive impact of each covariate. The model allows us to correctly classify individuals that are vaccine acceptant with 97% accuracy, and those that are vaccine hesitant with 72% accuracy. Trust in and knowledge about vaccines is, by far, the strongest predictor of vaccination choice. While our results demonstrate that public health campaigns designed to increase vaccination rates must find a way to increase public trust in COVID-19 vaccines, our results cannot speak to the malleability of such beliefs, nor how to enhance trust.
POLITICIZATION OF SCIENCE
We use survey data collected from 12,037 US respondents to examine the extent to which the American public believes that political motives drive the manner in which scientific research is conducted and assess the impact that such beliefs have on COVID-19 risk assessments. We find that this is a commonly held belief and that it is negatively associated with risk assessments. Public distrust in scientists could complicate efforts to combat COVID-19, given that risk assessments are strongly associated with one’s propensity to adopt preventative health measures.
As the COVID-19 pandemic swept the world in Spring 2020, the Trump administration invoked war against the coronavirus to severely restrict admission of migrants and asylum seekers into the United States. At the same time, it declined to enact national measures to control viral community spread and sharply criticized public health policies. We analyse this notable inconsistency as a case of opportunistic oppression whereby policymakers take advantage of a crisis to pursue pre-existing, and often unrelated, policy preferences. We identify how the securitisation of health and the crisis-enabled politics of enmity allowed the Trump administration to cynically erode migrant human rights protections while simultaneously failing to contain the pandemic. Opportunistic oppression represents an attractive strategy for states facing real and imagined emergencies to pursue political agendas that are not necessarily part of a coherent and effective response to the crisis at hand.
BLAME ATTRIBUTION
When disaster strikes in federal systems, who do citizens blame and why? While several literatures posit that partisanship shapes patterns of blame attribution, the mechanism driving this relationship remains disputed. Specifically, whereas partisan blame attribution (PBA) suggests that partisans hold distinct preferences regarding which level of government should devise policies in times of crisis—and subsequently hold said level accountable when failure is observed—partisan federalism (PF) suggests that citizens opportunistically assign blame to the level of government controlled by their disfavored party. In this study, we examine the extent to which each theory explains patterns of blame attribution related to the ongoing COVID-19 pandemic. Leveraging panel survey-data collected before the 2020 election and after the 2021 transition, we find that Democrats follow PF expectations, whereas Republicans follow PBA expectations. Our findings indicate that scholars should revisit blame attribution and more carefully consider the role of federalism in determining citizen preferences.