My research is moving toward a more comprehensive, large-scale model designed to stress-test the foundations of electoral theory. The bigger vision is to create a definitive computational framework that can simulate complex political ecosystems with high accuracy, providing data-driven insights into how different systems truly serve their constituents.
Next Steps
Testing Duverger's Law
I am currently developing a massive model planned for a September 2026 release that aims to directly prove or disprove Duverger's Law. This will involve simulating long-term electoral trends to see if plurality-rule systems truly inevitably gravitate toward a two-party result.
Ranked Choice Voting (RCV)
I plan to integrate RCV mechanics into the current simulation to see how preference-based voting affects the "optimal" number of parties. The goal is to see if RCV reduces the "wasted vote" penalty and naturally lowers collective alienation.
Geographic & District Modeling
The next iteration will move beyond a single national pool to model geographic concentration. This will allow for the simulation of gerrymandering and how winner-take-all districts impact the viability of third parties compared to proportional representation.
Dynamic Voter Sentiment
I want to add a "memory" component to voters, where past election outcomes influence future turnout and ideological firmness. This will help model how negative partisanship and polarization evolve over multiple election cycles.
Get Involved
I am always open to feedback, suggestions, or discussions regarding my modeling approach and findings. If you are interested in computational social science or have ideas on how to refine these simulations, please feel free to reach out—I'd love to hear from you.
Contact Me