Rebecca Cordell, Ph.D.
Rebecca.Cordell@utdallas.edu
Assistant Professor
University of Texas at Dallas
Year of PhD: 2017
Address: School of Economic, Political and Policy Sciences, University of Texas at Dallas, 800 West Campbell Road
City: Richardson, Texas - 75080
Country: United States
About Me:
I am an Assistant Professor of political science in the School of Economic, Political and Policy Sciences, University of Texas at Dallas. I received my Ph.D in Political Science from the Department of Government, University of Essex in 2017. My research focuses on human rights and state repression. I am particularly interested in why countries cooperate in transnational repression, measuring human rights using machine learning and text analysis, and examining public opinion and human rights. I also work on the Sub-national Analysis of Repression Project (SNARP). My research is published in International Interactions, International Studies Quarterly, Journal of Conflict Resolution, Journal of Human Rights, and Journal of Peace Research. In 2024, I received the International Studies Association (ISA) Human Rights Section's Best Paper Award for my paper Transnational Repression: International Cooperation in Silencing Dissent. In 2018, I received the ISA Human Rights Section's Steven C. Poe Best Graduate Student Paper Award for my paper Security-Civil Liberties Trade-offs: International Cooperation in Extraordinary Rendition.
Research Interests
Political Violence
Human Rights
Repression
State Repression
Conflict Processes & War
Text Analysis
Machine Learning
Spatial Analysis
Measurement
International Relations
Survey Experiments
Publications:
Journal Articles:
We identify a set of potential theoretical mechanisms that link the outbreak and spread of communicable diseases to temporal and spatial patterns of social unrest. Despite the proliferation of research since 2020 analyzing the social impact of the Covid-19 pandemic, we examine the broader relationship between less severe epidemic outbreaks and their social consequences. Epidemics, as well as the policies that governments implement to tackle them, often generate acute grievances among the public and create new opportunities for collective dissent, the combination of which promotes unrest. Nonetheless, perceived opportunities for unrest are influenced by the scale and scope of the disease outbreak, and particularly lethal disease outbreaks may therefore offset the incentives for collective mobilization. We examine these relationships using sub-national data on communicable disease outbreaks and geo-located social unrest events data in 60 African and Latin American countries from 1990 to 2017 and find support for our argument. However, we observe a curvilinear relationships between the severity of the epidemic and the incidence of unrest.
In many American Indian nations the security situation is dire. While scholars have studied how institutions shape economic development in American Indian and Alaska Native (AIAN) nations, the role of AIAN institutions for security and violent crime has received much less attention—despite the extensive literature highlighting the important role of effective and legitimate institutions in the long-term decline of violence. We analyze how varying types of American Indian polities and judiciary institutions fare in tackling violent crime using data across 146 American Indian polities. Our findings indicate that more autonomous American Indian criminal justice institutions with specialized court systems are associated with lower violent crime. However, customary justice institutions do not appear to be effective in reducing violent crime, highlighting the problem of cultural mismatch between traditional and formal justice systems. We argue that analyzing AIAN nations provides important insights into how institutional legitimacy can shape violent crime.
Most cross-national human rights datasets rely on human coding to produce yearly, country-level indicators of state human rights practices. Hand-coding the documents that contain the information on which these scores are based is tedious and time-consuming, but has been viewed as necessary given the complexity and detail of the information contained in the text. However, advances in automated text analysis have the potential to streamline this process without sacrificing accuracy. In this research note, we take the first step in creating this streamlined process by employing a supervised machine learning automated coding method that extracts specific allegations of physical integrity rights violations from the original text of country reports on human rights. This method produces a dataset including 163,512 unique abuse allegations in 196 countries between 1999 and 2016. This dataset and method will assist researchers of physical integrity rights abuse because it will allow them to produce allegation-level human rights measures that have previously not existed and provide a jumping-off point for future projects aimed at using supervised machine learning to create global human rights metrics.
Do aspects of current UN peacekeeping operations affect the willingness of that body to authorize new operations? Our theoretical arguments center on the capacity and costs of the organization – specifically the committed resources and risks associated with ongoing operations – with the assumption that greater existing commitments and perceived risks lessen the likelihood that the UN will create new operations. Related to the concern with risk, does successful diplomacy that produces a peace agreement in the conflict at hand lessen expected costs and therefore make authorizing new peacekeeping operations more attractive? To answer these questions, we examine UN peacekeeping authorization decisions over the period 1989–2016. Our results demonstrate that UN decisions to authorize new peacekeeping missions are connected to two forms of conflict management. First, successful attempts at peacemaking (evidence by peace agreements) increased the likelihood that a UN peacekeeping operation would be sent to that conflict in the aftermath of the agreement. We also demonstrate that the number of ongoing UN peacekeeping efforts are a strong negative predictor of whether or not the UN authorizes new missions. Theoretically, the concepts of perceived carrying capacity and risk, derived from other conflict management efforts, provided the explanatory bases for these effects.
From 2001 to 2005, over a quarter of all countries in the world cooperated in a secret rendition network that enabled the transfer of CIA terrorist suspects to secret detention sites. While governments in some states have not been punished for participating, others have incurred political costs, including electoral defeats. What explains variation in the political costs of participation in the post-9/11 extraordinary rendition program? I argue that left of center governments, particularly those in democracies, suffered greater political costs from being caught because of the perception that they are better at protecting civil liberties in the name of national security. I test the effect of party orientation on electoral defeat at the election following the revelation of participation in extraordinary rendition using a matched sample where the party in office at the time of participation remained the same. The analysis provides empirical support for my theoretical argument.
The annual US State Department Country Reports on Human Rights Practices represents one of the principal data sources used to generate multiple commonly used human rights measures. Despite the frequency with which these indicators are used in quantitative studies of human rights, scholars have rarely considered how the qualitative information in the source has varied over time. We contribute to this area of research by investigating the general changes in the amount of information included in the reports as well as the administration-specific changes in this information. Using automated text analysis techniques, we find that the amount of information in the reports generally increases over time. However, our analysis also reveals that the rate (and direction) of change varies across different human rights topics and across presidential administrations. Consequently, we find evidence to support a changing standard of accountability as well as evidence that political considerations shape human rights reporting.
Effectively measuring variation in institutions over time and across jurisdictions is important for examining how institutional characteristics shape political, social, and economic issues. We present a new dataset of American Indian and Alaska Native (AIAN) constitutions and a new approach for measuring variation in polities using machine learning techniques. Existing data on AIAN institutions have largely been based on costly and time-consuming expert coding and survey approaches, where the end product will become obsolete once institutions change. Our automated content analysis of AIAN constitutional documents allows for more flexible and customizable measurement of the variation, using a larger corpus of data than existing approaches, limited by data collection and coding costs. We consider variation in judicial institutions, previously shown to play a crucial role in AIAN development, and compare our machine coded measures to existing hand coded data for a sample of 97 American Indian constitutions. We show that machine coding replicates expert coded data. Our approach can be easily extended to other topics, including the executive, and shows the potential of automated measures to complement or confirm traditional coding of political institutions.
Following the launch of the WoT, the United States established a global rendition network that saw the transfer of Central Intelligence Agency (CIA) terrorist suspects to secret detention sites across the world. Conventional accounts of foreign complicity show that 54 diverse countries were involved, including many established democracies. What determined more than a quarter of the world’s countries to participate in RDI operations during the post-9/11 period? Given the sensitive nature of cooperation required, I argue that the United States screened countries according to their preferences on security-civil liberties trade-offs. Countries with similar preferences to the United States on human rights were cheaper to buy off and would have required less persuasion to cooperate. This theory is consistent with the existing claim that cooperation is more likely between countries with similar preferences as both actors are better off when the partnership increases. I test this hypothesis on global data using UNGA voting data as a proxy for common interest and develop a spatial variable that models a country’s logistical utility during the transfer of a detainee based on its distance to a central rendition transit corridor between the United States and Afghanistan. The analysis provides robust empirical support for my theoretical argument.
In my article, “Measuring extraordinary rendition and international cooperation” I present a model that can be used to measure extraordinary rendition and identify international cooperation in the Central Intelligence Agency’s Rendition, Detention and Interrogation program using public flight data and information on rendition flight characteristics. My analysis identifies 307 new likely rendition flights and 15 previously unidentified countries potentially involved. In response, Blakeley and Raphael argue that these results do not move beyond what they have already published, and also challenge the claim that these flights are “likely rendition flights” as they have not been triangulated by further evidence. However, it seems inconsistent to claim both that: (a) the findings are not new; and (b) the findings are wrong. I respond to their concerns by providing a detailed evaluation of my results in relation to their own findings. I demonstrate that there are important differences between the results in Blakeley and Raphael’s previous work and my own. I reinforce my earlier claim that triangulating these new results with reliable qualitative evidence is a crucial step.
Following the launch of the War on Terror, the United States of America established a global rendition network that saw the transfer of US Central Intelligence Agency terrorist suspects to secret detention sites across the world. There has been considerable debate over how many countries participated in rendition, secret detention and interrogation during the post-9/11 period, and conventional accounts of foreign complicity suggest that diverse countries were involved, including many established democracies. However, research on rendition has continually suffered from uncertainty, a lack of data, and systematic empirical evidence due to the secret nature of counterterrorism cooperation. In this article, I argue that it is possible to study the practice of rendition, unlike many other forms of clandestine security cooperation, as it is partially observable. Specifically, suspected extraordinary rendition flight paths can be tracked using publicly available flight data. This article uses the world’s largest set of public flight data relating to rendition to estimate cross-country collaboration in rendition, secret detention and interrogation. The result suggests 307 likely rendition flights and 15 new participating countries beyond the 54 known cases, with cross validation tests demonstrating high levels of model accuracy.