Sunita Parikh examines the history and fate of affirmative action programs in two ethnically heterogeneous democracies, the United States and India. Affirmative action programs in the United States represent a controversial policy about which the American public feel at best ambivalence and at worst hostility, while in India the expansion of reservation policies in recent years has led to riots and contributed to the fall of governments. And yet these policies were not particularly controversial when they were introduced. How the policy traveled from these auspicious beginnings to its current predicament can best be understood, according to Parikh, by exploring the changing political conditions under which it was introduced, expanded, and then challenged. Although they are in many respects very different countries, India and the United States are important countries in which to study the implementation of ascriptive policies like affirmative action, according to Parikh. They are both large, heterogeneous societies with democratic political systems in which previously excluded groups were granted benefits by the majorities that had historically oppressed them. Parikh argues that these policies were the product of democratic politics–which required political parties to mobilize existing groups as voters–and the ethnically heterogeneous nature of Indian and U.S. society–where ethnic markers are particularly salient sources of identification as groups. Affirmative action in both countries was introduced because it could be used to solidify and expand electoral coalitions by giving benefits to defined minority groups, according to Parikh. As the policy became better known, it became more disliked by non-targeted groups, and it was no longer an appeal which was cost free for politicians. This book will be of interest to social scientists concerned with race and ethnic relations and with the comparative study of political and social systems. Sunita Parikh is Assistant Professor of Political Science, Columbia University.
