The Dynamic Returns of Descriptive Representation: A Study of Race, Politics and Policy in Urban Governments

In 2015, 78% of Detroit\u27s city council was African American--the highest percentage in the country. For decades, there had been an assumption in the academic and activist fields that a legislative body with such a high percentage of minority presence would produce incredible policy gains for that group (i.e. African American Detroiters). Instead, the council passed no Black racial policy. In a city where there were ostensibly no barriers for passing racial policy -- there were no subsequent policy gains. Though running contrary to existing scholarship, Detroit is not an anomaly; it is an indicator of the larger trend. Using a mixed methods approach, I consider the impact of descriptive representation (i.e. presence of a minority group) on representation in policy (i.e. policy outcomes). The thesis that emerges from my examination is that the relationship between descriptive representation and representation in policy is not static, as has been suggested, but dynamic. The amount of representation in policy that a group achieves is a function of descriptive representation, but the relationship is not linear. More descriptive representation does not always predict more representation in policy. And indeed, cities with the most descriptive representation often have relatively low levels of representation in policy. This work challenges the current body of literature and calls for substantial revision of seminal theory