Local governments play a fundamental role in shaping US public policy. Scholars have studied the extent to which the US federal government and mass public allocate attention to certain issues. Studying such issue attention at the local level has been much more challenging, due in part to a lack of centralized data on local policymaking. The recently released LocalView corpus (https://localview.net) includes transcripts of more than 100,000 city council meetings across the United States in the years between 2006 and the present. In this project, CCC researchers are collaborating with the LocalView developers to apply recent advances in natural language processing to this corpus (including large language models). Our goal is to investigate the relationship between place-based policy discussions and outcomes in the places where they occur, and to build a practical suite of summarization, topic modeling, and search tools to help policymakers and the public at large to solve problems in their communities. .