Theoretical models have struggled to make sharp predictions of which governments form in parliamentary systems and how long these governments last. We develop an AI algorithm to solve an analytically intractable coalition bargaining game. While AI models have penetrated most aspects of daily life, they have largely been ignored by political scientists. Formidable successes by AI models in solving games like Chess, Go, and especially a bluffing game like Poker, suggest they also have the potential to attack difficult political games.

Since the 1960s, the study of policy and politics in American cities – and to a considerable degree, in the American national government – has revolved around the role of race or the interaction of race and class. My own work has largely followed that path. This project, however, examines the degree to which race/class hierarchy should remain the dominant paradigm in research on inequality in the United States. I consider four policies in four large American cities in order to see how well race/class intersection explains their trajectories.