Interdisciplinary Laboratory for Computational Social Science (iLCSS)
The All Minorities at Risk (AMAR) project is a university-based research project that monitors and analyzes the status and conflicts of socially relevant communal groups in countries with a current population of at least 500,000. The project is designed to provide information in a standardized format that aids comparative research and contributes to the understanding of politics involving relevant groups.
The project was founded in 1986 as the Minorities at Risk (MAR) data by Ted Robert Gurr,
one of the preeminent scholars of political violence and ethnic conflict. Since 1988, the
Center for International Development and Conflict Management (CIDCM) at the University
of Maryland has hosted the project. The MAR Project has been led by Ted Robert Gurr
(1986-2004), Christian Davenport (2004-2006), and Jonathan Wilkenfeld (2007-2010).
The AMAR project is led by Jóhanna Birnir (2010-present). The MAR and AMAR project
have been funded by various agencies, including the Carnegie Corporation, the Hewlett
Foundation, the National Consortium for the Study of Terrorism and Responses to
Terrorism (START), the National Science Foundation, the State Failure (now Political
Instability) Task Force, the United States Institute of Peace, the U.S. Department of
Homeland Security, and the Department of Government and Politics at the University of
The article introduces the All Minorities at Risk (AMAR) data, a sample of socially
recognized and salient ethnic groups. Fully coded for the forty core Minorities at
Risk variables, this AMAR sample provides researchers with data for empirical
analysis free from the selection issues known in the study of ethnic politics to date.
We describe the distinct selection issues motivating the coding of the data with an
emphasis on underexplored selection issues arising with truncation of ethnic group
data, especially when moving between levels of data. We then describe our sampling
technique and the resulting coded data. Next, we suggest some directions for the
future study of ethnicity and conflict using our bias-corrected data. Our preliminary
correlations suggest selection bias may have distorted our understanding about both
group and country correlates of ethnic violence.
Jóhanna K. Birnir, David D. Laitin,
Jonathan Wilkenfeld, David M. Waguespack,
Agatha S. Hultquist, and Ted R. Gurr
Protracted conflicts over the status and demands of ethnic and religious groups have caused more instability and loss
of human life than any other type of local, regional, and international conflict since the end of World War II. Yet we
still have accumulated little in the way of accepted knowledge about the ethnic landscape of the world. In part this is
due to empirical reliance on the limited data in the Minorities at Risk (MAR) project, whose selection biases are well
known. In this article we tackle the construction of a list of ‘socially relevant’ ethnic groups meeting newly justified
criteria in a dataset we call AMAR (A for All). We find that one of the principal difficulties in constructing the list is
determining the appropriate level of aggregation for groups. To address this issue, we enumerate subgroups of the
commonly recognized groups meeting our criteria so that scholars can use the subgroup list as one reference in the
construction of the list of ethnic groups most appropriate for their study. Our conclusion outlines future work on
the data using this expanded dataset on ethnic groups.
Jóhanna K Birnir, Jonathan Wilkenfeld, James D Fearon,
David D Laitin, Ted Robert Gurr, Dawn Brancati,
Stephen M Saideman, Amy Pate, and Agatha S Hultquist