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Abstracts Globalization has consistently challenged the authority of territorial states, with the internet serving as a prominent site of this disruption. We use a bordering lens to understand how states have attempted to manage global information interdependence. States have used cyberborders—content removal, website blocking, and routing infrastructure—to create distinctions between foreign and domestic information environments. We show that efforts to control digital information are robustly correlated with the concept of “border orientation”—or the degree of a state’s efforts to filter the movement of people and goods into and out of their jurisdiction. Cyberborders are correlated with terrestrial, suggesting a common underlying preference for assertively managing globalization more generally. This research supplements existing analyses of digital censorship that highlight vertical state–society relationships with a focus on horizontal inside–outside bordering relationships. The evidence suggests that digital policies are deeply tied to broader preferences for managing globalization that do not correspond exclusively with regime type. 

Researchers in the social sciences are interested in the consequences of institutions, increasingly on a global scale. Institutions that may be negotiated between states can have consequences at a microlevel, as local populations adjust their expectations and ultimately even their behavior to take institutional rules into account. However, large-scale fine-grained analyses that test for the complex evidence of such institutions locally are rare. This article focuses on a key institution: International borders. Using computer vision techniques, we show that it is possible to produce a geographically specific, validated, and replicable way to characterizeborder legibility, by which we mean the ability to visually detect the presence of an international border in physical space. We develop and compare computer vision techniques to automatically estimate legibility scores for 627,656 imagery tiles from virtually every border in the world. We evaluate statistical and data-driven computer vision methods, finding that fine-tuning pretrained visual recognition models on a small set of human judgments allows us to produce local legibility scores globally that align well with human notions of legibility. Finally, we interpret these scores as useful approximations of states’ border orientations, a concept that prior literature has used to capture the visible investments states make in border areas to maintain jurisdictional authority territorially. We validate our measurement strategy using both human judgments and five nomological validation indicators. 

The Border Crossings of the World (BCW) dataset explores state authority spatially by collecting information about infrastructure built where highways cross internationally recognized borders. This geolocated information is recorded using high-altitude imagery from 1993 to 2020. We describe how the data were collected, demonstrate the dataset’s utility, and offer advice and best practices regarding use of the data. These data present clear evidence of visible and long-term state investments in authoritative displays of states’ intention to ‘filter’ entry into and exit out of their national jurisdiction. Researchers can use these data to test theories on the causes and consequences of border hardening for security outcomes, border management cooperation, political violence, terrorism, trade and migration flows, transnational crime patterns, and human rights conditions. Because the data are precisely geolocated, they are easy to combine with existing spatial datasets. 

Key aspects of international policy, such as those pertaining to migration and trade, manifest in the physical world at international political borders; for this reason, borders are of interest to political science studying the impacts and implications of these policies. While some prior efforts have worked to characterize features of borders us- ing trained human coders and crowdsourcing, these are limited in scale by the need for manual annotations. In this paper, we present a new task, dataset, and baseline approaches for estimating the legibility of international political borders automatically and on a global scale. Our contributions are to (1) define the border legibility estimation task; (2) collect a dataset of overhead (aerial) imagery for the entire world’s international borders, (3) propose several classical and deep-learning-based approaches to establish a baseline for the task, and (4) evaluate our algorithms against a validation dataset of crowdsourced legibility com- parisons. Our results on this challenging task confirm that while low-level features can often explain border legibility, mid- and high-level features are also important. Finally, we show preliminary results of a global analysis of legibility, confirming some of the political and geographic influences of legibility. 

Abstract Pandemics are imbued with the politics of bordering. For centuries, border closures and restrictions on foreign travelers have been the most persistent and pervasive means by which states have responded to global health crises. The ubiquity of these policies is not driven by any clear scientific consensus about their utility in the face of myriad pandemic threats. Instead, we show they are influenced by public opinion and preexisting commitments to invest in the symbols and structures of state efforts to control their borders, a concept we call border orientation . Prior to the COVID-19 pandemic, border orientation was already generally on the rise worldwide. This trend has made it convenient for governments to “contain” the virus by externalizing it, rather than taking costly but ultimately more effective domestic mitigation measures. We argue that the pervasive use of external border controls in the face of the coronavirus reflects growing anxieties about border security in the modern international system. To a great extent, fears relating to border security have become a resource in domestic politics—a finding that does not bode well for designing and implementing effective public health policy.