Civic Tech

Tools for Democratic Participation

Democracy works best when everyone can participate in shaping it. This section brings together the software, data, code, and interactive tools the Lab has built and collected to democratize access to sophisticated methods for redistricting and electoral analysis.

All our tools are open-source and freely available. We believe the methods for analyzing democracy should be democratic themselves: transparent, accessible, and community-owned. Whether you’re a community member who wants to draw your own district map, a researcher analyzing voting patterns, a journalist covering redistricting, or an advocate building a voting rights case, these tools put computational methods in your hands.

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  Districtr

  This mapping tool lets you draw and share redistricting plans as well as draw and describe your “community of interest.”

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  GerryChain

  This is the open-source Python library powering our redistricting analyses. GerryChain is tech for ensemble analysis that’s been used in major redistricting cases.

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  MAUP

  MAUP is the geospatial toolkit for redistricting data. The package streamlines the basic workflows that arise when working with blocks, precincts, and districts, such as assigning precincts to districts, aggregating block data to precincts, disaggregating data from precincts down to blocks, prorating data when units do not nest neatly, and fixing topological issues, overlaps, and gaps.

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  VoteKit

  VoteKit is our “Swiss army knife for computational social choice research.” This Python package provides an end-to-end pipeline for reading in ballot data, running ballots through a voting rule to get election outcomes, and then visualizing and analyzing the preferences and winners.

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  VoteKit Lite

  Don’t want to touch Python code yourself? VoteKit Lite is a web app that replicates some of the basic features of VoteKit, allowing you to compare electoral outcomes under a variety of assumptions through a more user-friendly interface.

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  PyEI

  Since ballots don’t actually include demographic information, statistical inference methods are needed to estimate whether different demographic groups have different voting patterns. We can use this to identify polarized voting, which is required by courts in Voting Rights Act cases. PyEI is a Python toolkit that lets users apply a range of methods (especially variants of ER and EI) via an easy-to-use interface, with flexible options for saving and visualizing the outputs.

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  Interactives

  These visualizations allow you to explore concepts like compactness and proportionality.