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Disproportional Representation: A Mixed Methods Analysis of Educational Attainment Representation in State Government

Jayme Neiman, University of Nebraska - Lincoln


The present dissertation examines unequal political representation in the United States. More specifically, I ask whether American citizens with low relative levels of education are under-represented by their state governments compared to their well-educated counterparts. I posit that this question is vital to our understanding of the quality of democracy in America. In order to answer the primary question, I take a mixed-methods approach, using a combination of quantitative and qualitative data to obtain a clearer picture of the representation scene. In the quantitative chapters, I demonstrate that in terms of both service responsiveness and policy responsiveness, those individuals with less education are not being appropriately represented. Additionally, I interviewed legislators from around the country to gain insight into how they perceive their representativeness. This adds depth and a more personal angle to the quantitative studies. I take additional steps to examine wither the education levels of the legislators themselves affects their representation of less-educated constituents. Not only is legislator education an area that has not been often studied, I use an original data set of state legislator educational attainment that provides the most extensive look at this topic that, to my knowledge, has ever been conducted. Finally, I conclude by relating this work back to that on state politics and inequality and by highlighting a series of policy recommendations addressing issues in civic education and participation, and the weighting of citizen political interests in the policymaking process.

Subject Area

Political science

Recommended Citation

Neiman, Jayme, "Disproportional Representation: A Mixed Methods Analysis of Educational Attainment Representation in State Government" (2014). ETD collection for University of Nebraska - Lincoln. AAI3629435.