This repository contains a comprehensive simulation and analysis toolkit for exploring the Impossibility Theorem for Gerrymandering, as described in the work of Alexeev and Mixon. Our project aims to provide a deeper understanding of the complexities involved in creating fair districting systems and the challenges in detecting and preventing gerrymandering.
- Develop a sophisticated simulation model for generating various districting scenarios.
- Evaluate the implications of different districting strategies on electoral fairness and efficiency.
- Refine and enhance the analysis of the interplay between voter distribution homogeneity, population balance, and geometric compactness in districting.
- simulation.ipynb: The core simulation code for the impossibility theorem.
- data_analysis.ipynb: Jupyter notebook for analyzing simulation outputs saved as CSV files.
- district_visualization: Folder containing a Python app that provides an interactive version of the simulation.
- interactivebook.ipynb: Jupyter notebook version of the district visualization web app.
- Live Demo: Try out our interactive visualization app!
- pdf: Folder containing related academic papers and resources.
Our research builds upon the foundational concepts laid out in "An Impossibility Theorem for Gerrymandering" by Alexeev and Mixon. We focus on computationally enhancing existing models to simulate and scrutinize the effects of varied district configurations on election results.
The core challenge we address is the development of objective, quantifiable measures to evaluate the fairness of district boundaries. Our approach combines mathematical rigor with practical applicability, offering insights valuable for policymakers, political analysts, and engaged citizens.
- Districting System: A method of dividing a larger electoral area into smaller districts, aiming for balanced populations and geometric compactness.
- Gerrymandering: The manipulation of electoral district boundaries for political gain.
- Efficiency Gap: A measure of wasted votes used to assess the fairness of district boundaries.
- Clone the repository
- Install required dependencies (list them here or refer to a requirements.txt file)
- Explore the Jupyter notebooks to run simulations and analyze results
- Check out the interactive visualization in the
district_visualizationfolder
We welcome contributions!
We hope this repository serves as a valuable resource for those interested in the mathematical and computational aspects of electoral fairness and the challenges of gerrymandering. Happy exploring!