Description
This webinar will review forced displacement data collected by the United Nations High Commissioner for Refugees (UNHCR) and other organizations and common strategies for quantitative analyses of these data to gain insights on both global and country-specific internal forced displacement trends. These datasets consist of counts representing the observed number of individuals moving from a particular location to another location (i.e., dyadic data).
Methodologies explored including gravity models and regression analysis along with newer methodological advancements that may more effectively address topic specific complexities. We will discuss a case study of the international outflow caused by the ongoing invasion of Ukraine. We discuss strategies for blending organic data( e.g., data collected from social media, or search engines) with conventional data sources such as official statistics and macroeconomic data allowing us to better understand human movement. Opportunities and challenges of using organic data in modeling and forecasting will be highlighted.
Speakers
Nathan Wycoff is a Data Science Fellow at the Massive Data Institute in the McCourt School of Public Policy at Georgetown University studying forced migration using internet data and machine learning. Previously, he acquired a PhD in Statistics from Virginia Tech with a dissertation on sensitivity analysis for computationally intensive models.
Geraldine Henningsen is a Data Scientist at UNHCR, the UN Refugee Agency, where she specializes in predictive analyses on forcibly displaced populations using machine learning and econometric/statistical approaches to support UNHCR’s anticipatory action efforts. Before joining UNHCR, she worked in academia, conducting quantitative research on climate and energy related topics.
Ali Arab is the Director of Graduate Studies and Associate Professor of Statistics in the Department of Mathematics and Statistics of Georgetown University. His methodological research is in spatio-temporal and spatial statistics, and hierarchical Bayesian modeling. He is interested in applications of statistics in environmental science, epidemiology of infectious diseases, ecology, and human rights problems. His current research is focused on developing methodological tools for studying problems in the intersection of climate change and social/natural phenomena, in particular, bird phenology and climate change, climate and conflict driven forced migration, and climate change and vector-borne diseases. Ali serves as one of the American Statistical Association representatives to the American Association for the Advancement of Science (AAAS) Science and Human Rights Coalition.
Mindy Reiser (Moderator) is a sociologist with rich and diverse public policy experience in the United States and internationally. She has directed international development programs and evaluated their impacts for the United Nations, the US Agency for International Development, the Ford Foundation and a wide array of non-governmental organizations. She is Vice President of Global Peace Services USA and a member of the Board of Governors of the Washington, DC Chapter of the Labor and Employment Relations Association. Mindy holds a PhD in Social Policy from Brandeis University and Masters’ Degrees in International Affairs and Journalism from Columbia University.
John Dale (Host) is Director of Movement Engaged Research Hub, Center for Social Science Research at George Mason University and Associate Professor at the Department of Sociology and Anthropology (GMU). His current research and book project explore how big data and digital technologies reshape the practices and politics of human rights, and understandings of humanity.
This webinar series is a project of the AAAS Science and Human Rights Coalition. The team organizer is Oliver Moles, Ph.D.
To view past webinars in this series, please visit Scientific Collaborations with Human Rights Organizations.
