Newsletter

APSA Annals of Comparative Democratization is the official newsletter of the American Political Science Association’s Democracy Autocracy section. Formerly first known as CompDem, it has been published three times a year (October, January, and May) since 2003. In October 2010, the newsletter was renamed APSA-CD and expanded to include substantive articles on democracy, as well as news and notes on the latest developments in the field. In September 2018 it was renamed the Annals to reflect the increasingly high academic content and recognition of the symposia.

The current issue of the Annals of Comparative Democratization, 2019(3) September, is available in the complete archive of past issues. To inquire about submitting an article to the Annals, please contact Dan Slater and Robert Mickey.

Executive Editors:

Dan Slater specializes in the politics and history of enduring dictatorships and emerging democracies, with a regional focus on Southeast Asia. At the University of Michigan, he serves as the Ronald and Eileen Weiser Professor of Emerging Democracies, the Director of the Weiser Center for Emerging Democracies, and Professor of Political Science. Previously, he served for 12 years on the faculty at the University of Chicago, where he was the Director of the Center for International Social Science Research, Associate Professor in the Department of Political Science, and associate member in the Department of Sociology.

 

Robert Mickey is Associate Professor of Political Science and Director of Graduate Studies at the University of Michigan. His research focuses on U.S. politics in historical perspective. He is interested in American political development, political parties, racial politics, and policy responses to inequality. He has taught undergraduate courses on the political development of the U.S. South in comparative perspective and directed the department’s honors thesis program. At the graduate level, he has taught American Political Development; U.S. Parties; Regimes and Regime Change; and Causal Inference in Small-n Research.