For millennia, political entities have declared a “state of emergency” when facing acute danger or distress. Traditionally, the entity declaring the emergency was a sovereign ruler or nation-state and the threat was geopolitical or insurrectionary in nature. In response, the sovereign authority would categorically suspend political and legal-juridical norms, turning instead to extraordinary measures of control. During such “exceptional” periods, democratic rule and constitutional order were abrogated on the grounds that necessitas non habet legem (“necessity knows no law”). More recently, emergency-based techniques of governance have been used to address a rapidly growing and diversifying list of threats and disruptions, including (but not limited to): natural and human-made disasters, infrastructural and technological failures, fiscal and financial crises, terrorist threats, and public health hazards. This has entailed a proliferation of entities that possess the power to declare an emergency and implement extra-democratic modes of governance. These entities deploy emergency measures in a geographically targeted fashion, such that specific districts, cities, counties, regions, and states are subject to them.
Emergency management is on the rise. From school systems, to waste authorities, to electric grids, to U.S. Territories, the technique is appearing in a growing number of different juridical and sociopolitical contexts. And yet, while emergency intervention seems to be emerging as the de rigueur response to local and regional problems of all types, there is no central repository or database tracking the practice. “Everyday Emergencies” seeks to fill this critical gap in our knowledge.
“Everyday Emergencies” addresses this problem in two primary ways. First and foremost, the lacuna that needs to be filled is an empirical one. Researchers currently lack the data necessary to make basic statements with respect to who, why, where, and how frequently emergency management is being administered. Hence, the proposed project will research, record, and visualize the recent implementation of emergency management across the United States. Specifically, by utilizing recent advances in big data analytics and machine learning to extract cases of emergency management from large databases (covering U.S. newspapers, periodicals, and industry newsletters), this project will develop an original national dataset of all cases of emergency intervention in the U.S. from 1998-2018. Such a dataset would serve as the empirical foundation needed for the development of a comprehensive typology of emergency interventions. It would also provide the basis for subsequent mapping efforts.
Second, “Everyday Emergencies” also seeks to understand the deeper patterns and broader implications of emergency management practices. Targeted emergency management is a phenomenon based largely on the negative applications of state power whereby citizens are deprived of certain rights and protections during periods of crisis. As such it is exceedingly important to understand who is being subjected to these provisions and for what reasons. For instance, a recent analysis of fiscal emergency management in Michigan finds that while the fiscal prognosis of local municipalities and school districts will explain a great deal in terms of the distribution of emergency managers (EMs), the proportion of black residents is also a determining factor (Kirkpatrick and Breznau, in progress). Specifically, when we control for fiscal health, the odds that an EM will be assigned increase by 50% for every 10% increase in the local black population. Obviously, such findings raise grave questions concerning the relationship between emergency management and disenfranchisement in Michigan. It is imperative that such patterns are also interrogated on the national scale. In order to do so, however, it is necessary to build out a more robust dataset that includes additional demographic and political variables. This will be accomplished with the help of a team of undergraduate research assistants (RAs), who will “clean” the raw dataset (described above) and construct a short case study of each emergency management event. This will allow for deeper and more sophisticated forms of analysis. “Everyday Emergencies” is thus a stand-alone project that will both empirically establish the frequency and distribution of emergency management strategies over a two-decade period, as well as provide a framework for identifying and critically analyzing patterns that may emerge from said data. This helps us to better understand the social and political effects of emergency intervention, and better predict its future use. If successful, however, the project may also serve as a blueprint for a larger project that could be expanded longitudinally and/or geographically (e.g. cross-nationally).