Cues sent by political elites are known to influence public attitudes and behavior. Polarization in elite rhetoric may hinder effective responses to public health crises, when accurate information and rapid behavioral change can save lives. We examine polarization in cues sent to the public by current members of the U.S. House and Senate during the onset of the COVID-19 pandemic, measuring polarization as the ability to correctly classify the partisanship of tweets’ authors based solely on the text and the dates they were sent. We find that Democrats discussed the crisis more frequently–emphasizing threats to public health and American workers–while Republicans placed greater emphasis on China and businesses. Polarization in elite discussion of the COVID-19 pandemic peaked in mid-February—weeks after the first confirmed case in the United States—and continued into March. These divergent cues correspond with a partisan divide in the public’s early reaction to the crisis.
Political scientists have increasingly begun to study how citizen characteristics shape whether-and how-they interact with the police. Less is known about how officer characteristics shape these interactions. In this article, we examine how one officer characteristic-officer sex-shapes the nature of police-initiated contact with citizens. Drawing on literature from multiple fields, we develop and test a set of competing expectations. Using over four million traffic stops made by the Florida State Highway Patrol and Charlotte (North Carolina) Police Department, we find that female officers are less likely to search drivers than men on the force. Despite these lower search rates, when female officers do conduct a search, they are more likely to find contraband and they confiscate the same net amount of contraband as male officers. These results indicate that female officers are able to minimize the number of negative interactions with citizens without losses in effectiveness.
Evidence that racial minorities are targeted for searches during police traffic stops is widespread, but observed differences in outcomes following a traffic stop between white drivers and people of color could potentially be due to factors correlated with driver race. Using a unique dataset recording over 5 million traffic stops from 90 municipal police departments, we control for and evaluate alternative explanations for why a driver may be searched. These include: (1) the context of the stop itself, (2) the characteristics of the police department including the race of the police chief, and (3) demographic and racial composition of the municipality within which the stop occurs. We find that the driver's race remains a robust predictor: black male drivers are consistently subjected to more intensive police scrutiny than white drivers. Additionally, we find that all drivers are less likely to be subject to highly discretionary searches if the police chief is black. Together, these findings indicate that race matters in multiple and varied ways for policing outcomes.
We investigate a possible linkage between municipal reliance on fines, fees, and forfeitures as a revenue source and policing behavior. With a dataset of four million traffic stops made by North Carolina municipalities, we demonstrate that a regular reliance on fines, fees, and forfeitures has powerful, predictable, and racially distinct impacts on black and white drivers, and that fiscal stress exacerbates these differences. A greater regular reliance on fines, fees, and forfeitures is linked to a decrease in the probability of white, but not black, drivers being searched; and increased odds of finding contraband among those white drivers who are searched, but no such change for black drivers. We validate the North Carolina tests with aggregate analyses of municipalities across four states.
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