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Gerrymandering refers to drawing legislative districts so that one political party wins a disproportionate number of seats. 听But how can we quantify it? 听One promising approach uses computational and statistical tools to compare a districting plan to an 鈥渆nsemble鈥� of many possible plans. 听Precinct-level election results are overlaid on each plan in the ensemble to determine how many seats each party would have won under that plan, and the results are plotted on a bell curve. 听If a particular plan is an 鈥渆xtreme outlier鈥� on this bell curve, this is considered strong evidence that the plan may have been intentionally gerrymandered to achieve a specific partisan outcome.

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This analytic approach can account for a state鈥檚 particular political geography more effectively than simpler measures, and it has already been used in several major court cases regarding redistricting. 听The challenge is that this analysis requires lots of data about small geographic units (e.g., voting precincts): geographic information, population data, and election results for each unit. 听This data is surprisingly hard to collect; much of it is available only at the county level, and compiling the data for the entire state can be a laborious process. 听

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Fortunately, it turns out that we don鈥檛 have to start from scratch! 听During the summer of 2019, a student research group at Colorado College collected and processed precinct and election data for Colorado's 2018 election. 听This data is now ready to analyze, and some initial analysis is already in progress.

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For this project, students will 鈥済o back in time鈥� and gather this data for Colorado's elections from 2016 and (if time permits) 2014 so that we can extend our analysis to understand recent historical trends. 听The main tasks will be:

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(1) Determine which precinct boundaries have changed between 2010 and 2018, and construct historically accurate precinct maps to match with election data for the 2016 and (if time permits) 2014 Colorado elections.

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(2) Join precinct maps with election and population data to create a clean data set that can be used for analysis.

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(3) Use analytical tools developed by the Metric Geometry and Gerrymandering Group to analyze how the enacted plans perform vs. an ensemble of districting plans.听

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The results will contribute to a longer-term effort, joint with Beth Malmskog of Colorado College and her students, to understand the current state of Colorado鈥檚 legislative districts and to provide quantitative information that may help inform the next round of redistricting in 2021.

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