Carry the Two

Mathematics & Political Geography

Oct 17, 2024

Ranthony Clark, an NSF postdoctoral fellow at Duke University focused on mathematics and social justice, discusses her work identifying communities of interest in Ohio’s redistricting. Jiajie Luo, a recent UCLA PhD graduate, dives into how topological data analysis uncovers polling site coverage gaps in urban areas. The conversation highlights innovative approaches to fair representation and the importance of community engagement, revealing how mathematics can drive democratic accessibility.

35:31

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Episode guests

Jiajie Luo

Ranthony Clark

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Episode notes

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Quick takeaways

Identifying communities of interest in redistricting requires a collaborative approach that integrates both geographic data and resident narratives for accurate representation.

The utilization of topological data analysis helps uncover underrepresented polling sites in urban areas, enhancing democratic participation in elections.

Deep dives

Understanding Communities of Interest in Redistricting

Communities of interest are defined by two key aspects: geographic proximity and shared connections that bind them, such as ethnic or economic interests. These communities play a significant role in redistricting as preserving them can help ensure that residents have representatives who are attuned to their shared concerns. Notably, over half of U.S. states include language about maintaining these communities during the redistricting process for congressional districts, highlighting their importance for political representation. The example of diverse neighborhoods in Chicago illustrates how cultural heritage can influence political views, making the preservation of these communities even more crucial.

Intro

2min

Mapping Communities of Interest in Redistricting

13min

Crafting Community Clusters Through Data

6min

Navigating the Challenges of Fair Redistricting

4min

Polling Locations and Geographical Accessibility

8min

Using Mathematics to Enhance Electoral Accessibility

3min

In this episode, the fourth episode of our mathematics and democracy season, we dig into two stories about the intersection of political geography and mathematics. The first story comes from Ranthony Clark and is about her work with the Metric Geometry and Gerrymandering Group around identifying communities of interest, with a focus on her in Ohio alongside CAIR Ohio, the Ohio Organizing Collaborative (OOC), the Ohio Citizens Redistricting Commission, and the Kirwan Institute for the Study of Race and Ethnicity at Ohio State. The second story is about polling sites in cities, and the places in those cities that may not be covered as well as they should be. We hear from Mason Porter and Jiajie (Jerry) Luo, two members of the team, about how they used topological data analysis to find these holes in coverage.

Find our transcript here: Google Doc or .txt file

Curious to learn more? Check out these additional links:

Ranthony Clark

Collaborators for the data science team: Erin Chambers, Ranthony A. Clark, Moon Duchin, Parker Edwards, JN Matthews, Anthony Pizzimenti, Chanel Richardson, Parker Rule, and Ari Stern

Communities of Interest Paper

Persistent Homology for Resource Coverage: A Case Study of Access to Polling Sites Authors: Abigail Hickok, Benjamin Jarman, Michael Johnson, Jiajie Luo, Mason A. Porter

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Music by Blue Dot Sessions