Rum Histories: Drinking in Atlantic Literature and Culture

The book examines rum in anglophone Atlantic literature between 1945 and 1973, the period of decolonization, and explains the adaptation of these images for the era of globalization. Rum’s alcoholic nature links it to stereotypes (e.g., piracy, demon rum, Caribbean tourism) that have constrained serious analysis in the field of colonial commodities. Insights from anthropology, history, and commodity theory yield new understandings of rum’s role in containing the paradox of a postcolonial world still riddled with the legacies of colonialism. The association of rum with slavery causes slippage between its specific role in economic exploitation and moral attitudes about the consequences of drinking. These attitudes mask history that enables continued sexual, environmental, and political exploitation of Caribbean people and spaces. Gendered and racialized drinking taboos transfer blame to individuals and cultures rather than international structures, as seen in examinations of works by V. S. Naipaul, Hunter S. Thompson, Jean Rhys, and Sylvia Townsend Warner. More broadly, these stereotypes and taboos threaten understanding West Indian nationalism in works by Earl Lovelace, George Lamming, and Sylvia Wynter. The conclusion articulates the popular force of rum’s image by addressing the relationship between a meme from the "Pirates of the Caribbean" films and rhetoric during the 2016 election year.

Partisan Fertility and Presidential Elections

Changes in political leadership drive large changes in economic optimism. We exploit the surprise 2016 election of Trump to identify the effects of a shift in political power on one of the most consequential household decisions: whether to have a child. Republican-leaning counties experience a sharp and persistent increase in fertility relative to Democratic counties: a 1.1 to 2.6 percentage point difference in annual births, depending on the intensity of partisanship. In addition, Hispanics see fertility fall relative to non-Hispanics, especially compared to rural or evangelical whites. Further, following Trump pre-election campaign visits, relative Hispanic fertility declines.

The Tribal Economy: Economic Perceptions, Economic Anxiety and the Prospects for Political Accountability

Whether American citizens hold presidents accountable for changes in the condition of the economy has increasingly been questioned. At the same time, the outcome of the 2016 election has been widely interpreted in economic terms. Press and pundits on both sides of the aisle have endorsed the “left behind” voter thesis suggesting that those who were economically dissatisfied or anxious voted against the incumbent party and thus elected Donald Trump. Likewise, some have argued that Trump would have won again in 2021 if not for the economic downturn caused by the COVID19 pandemic. In this study I use seven waves of nationally-representative panel data to examine change over time in individuals’ perceptions of the economy across the two most recent presidential election periods. I compare the magnitude of change from partisan rationalization of the economy to the magnitude of changes in perceptions due to the record-breaking decline in GDP during the year that COVID19 hit the US. My results provide little to no evidence that changes in perceptions due to real economic change were strong enough to overcome the effects of partisan rationalization. Given that the COVID19 recession was unusually severe, these results provide little reason for optimism that voters can hold leaders accountable for economic change.

The Impact of Mask Usage on COVID-19 Deaths: Evidence from US Counties Using a Quasi-Experimental Approach

I examine the relationship between mask usage and COVID-19 deaths at the county level. When examining this relationship, even the direction caused by the potential endogeneity bias is unclear. In one direction, characteristics that are known to correlate with a larger amount of potential COVID-19 deaths, such as an older population, may make people more likely to wear masks. This will cause a bias that makes mask usage look less effective than it truly is. In the other direction, areas with higher risk tolerances may have less mask usage, but may at the same time be engaging in other behavior that puts them at higher risk for contracting COVID-19. This will cause a bias that makes mask usage look more effective than it truly is. The identification approach exploits a large set of controls and employs percentage of vote for Donald Trump in the 2016 election as an instrumental variable for mask usage. The main finding is that a one percentage point increase in the number of individuals who say they often or frequently wear a mask when within six feet of people will reduce COVID-19 deaths in a county by 10.5%, or six deaths in the average county.

Perspectives on Gender Stereotypes: How Did Gender-Based Perceptions Put Hillary Clinton at an Electoral Disadvantage in the 2016 Election?

Research on gender stereotypes has largely emphasized that women candidates are evaluated differently compared to their male counterparts. In this article, I argue that such differential evaluation put Clinton at an electoral disadvantage in the 2016 election. I develop my expectations based on the differences between feminine stereotypes and masculine stereotypes and how voters’ perceptions of the latter match the longstanding popular expectations for political leaders, in a way that advantages men as candidates and disadvantages women. I also expect that a “gender affinity effect” influenced the election, with Democratic women being more likely to vote for Clinton. In this article, I rely on data from the 2016 American National Election Survey to evaluate the role of gender affinity effect and gender stereotypes in Clinton’s electability. The results show that masculine personality traits had the largest effect and were more fundamental for winning the White House. They also show that there was no significant evidence of a gender affinity effect among Democratic women in terms of voting for Clinton. These results offer new insights into voters’ gender stereotypic perceptions of Clinton and their consequences for the electoral fortunes of women candidates in general.

The Accidental Origins, Underappreciated Limits, and Enduring Promises of Platform Transparency Reporting about Information Operations

Intense public and regulatory pressure following revelations of Russian interference in the US 2016 election led social media platforms to develop new policies to demonstrate how they had addressed the troll-shaped blind spot in their content moderation practices. This moment also gave rise to new transparency regimes that endure to this day and have unique characteristics, notably: the release of regular public reports of enforcement measures; the provision of underlying data to external stakeholders and, sometimes, the public; and collaboration across industry and with government. Despite these positive features, platform policies and transparency regimes related to information operations remain poorly understood. Underappreciated ambiguities and inconsistencies in platforms’ work in this area create perverse incentives for enforcement and distort public understanding of information operations. Highlighting these weaknesses is important as platforms expand content moderation practices in ways that build on the methods used in this domain. As platforms expand these practices, they are not continuing to invest in their transparency regimes, and the early promise and momentum behind the creation of these pockets of transparency are being lost as public and regulatory focus turns to other areas of content moderation.

Will I die of coronavirus? Google Trends data reveal that politics determine virus fears

Is Google Trends (GT) useful to survey populations? Extant work has shown that certain search queries reflect the attitudes of hard-to-survey populations, but we do not know if this extends to the general population. In this article, we leverage abundant data from the Covid-19 pandemic to assess whether people’s worries about the pandemic match epidemiological trends as well as political preferences. We use the string ‘will I die from coronavirus’ on GT as the measure for people’s level of distress regarding Covid-19. We also test whether concern for coronavirus is a partisan issue by contrasting GT data and 2016 election results. We find strong evidence that (1) GT search volume close matches epidemiological data and (2) significant differences exist between states that supported Clinton or Trump in 2016.

Candidate Preference, State Context, and Voter Turnout: Comparing Non-Voters and Voters in the 2016 Presidential Election

While much attention has been paid to understanding the drivers of support for Donald Trump, less focus has been placed on understanding the factors that led individuals to turn out and vote or stay home. This paper compares non-voters and voters in the 2016 election and explores how self-reported candidate preference prior to the election predicted turnout across three different state contexts: (1) all states, (2) closely contested states won by Trump, and (3) closely contested states won by Clinton. We find that preference for both candidates predicted turnout in the aggregate (all states) and in closely contested states won by Clinton, but only preference for Trump predicted turnout in the closely contested states won by Trump. Moreover, we find that political interest is negatively associated with preference for Clinton when examining candidate preferences among non-voters. Our analysis suggests that non-voters in the 2016 election held meaningful candidate preferences that impacted voter turnout but that state context played an important role in this relationship. This study sheds light on an understudied component of the 2016 election, the attitudes and behavior of non-voters, as well as points to the importance of incorporating contextual variation in future work on electoral behavior and voter turnout.