Collaborative Research: Advancing the study of repression: The Global Surveillance and Censorship Scores (GSCS) dataset

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

Part 1 Under what conditions do states surveil and censor their citizens? How are the two tactics related to each other and other forms of repression and control? To what extent have states concealed their use of these tactics? States have increasingly wielded surveillance and censorship, both digital and physical, as tools of political influence at home and abroad. Yet, there exist scant theoretical and empirical advances to help understand these phenomena. Consequently, scholars know little of how and when states employ these levers and how their use has evolved with technological advancements. To address this critical knowledge gap, the investigators produce, analyze, and disseminate a novel dataset, the Global Surveillance and Censorship Scores (GSCS) database. The project utilizes mixed methods to collate quantitative and qualitative historical and contemporary data, including a diverse set of existing human rights reports. The resulting dataset allows academics, practitioners, and policymakers to advance the study of human rights and repression. The project has key implications for American national security and policy, ranging from finance and healthcare to human and drug trafficking, which have been affected by surveillance and censorship practices. Part 2 Surveillance and censorship are key levers of power to control information. States have increasingly wielded them, digitally and physically, to compete for political influence at home and abroad. Yet, scant theoretical and empirical advances exist to help understand the phenomena. Consequently, we know little of how and when actors employ these levers, and how their use as repressive techniques evolve with technological advancements in the 21st century. The investigators use mixed-methods to collect quantitative and qualitative historical and contemporary data to develop the Global Surveillance and Censorship Scores (GSCS) database. Information is extracted on surveillance and censorship from a diverse set of existing human rights reports and other documents. Given the clandestine nature of surveillance and censorship, a latent variable models developed to address missing information and to assess the sensitivity of the model estimates to understand the extent to which states conceal the use of such tools. This Bayesian latent variable model is able to predict cases of missing information and aggregate information into country-year estimates. To further address bias in the reports, the investigators also conduct case studies using expert information, interviews, and archival research to validate the data. The project will allow researchers to generate new theories and empirical evidence to advance the study of human rights, censorship, and surveillance. The data and analytic deliverables will serve as a public good for the community of academics, practitioners, and policymakers. Surveillance and censorship increasingly shape geopolitics by controlling and manipulating information; understanding the evolution of censorship and surveillance can thus contribute to the development of sound foreign and security policies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.