Exploring Fairness in District-based Multi-party Elections under different Voting Rules using Stochastic Simulations
Adway Mitra

TL;DR
This paper investigates fairness in district-based multi-party elections using stochastic simulations, proposing new measures and policies to improve voter satisfaction and reduce bias.
Contribution
It introduces a stochastic model for election simulation incorporating community identities and evaluates alternative voting rules for fairness.
Findings
Allowing voters to provide two preferences reduces bias.
Fairness measures help quantify voter satisfaction.
Alternative voting policies can improve election fairness.
Abstract
Many democratic societies use district-based elections, where the region under consideration is geographically divided into districts and a representative is chosen for each district based on the preferences of the electors who reside there. These representatives belong to political parties, and the executive powers are acquired by that party which has a majority of the elected district representatives. In most systems, each elector can express preference for one candidate, though they may have a complete or partial ranking of the candidates/parties. We show that this can lead to situations where many electors are dissatisfied with the election results, which is not desirable in a democracy. The results may be biased towards the supporters of a particular party, and against others. Inspired by current literature on fairness of Machine Learning algorithms, we define measures of fairness…
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Taxonomy
TopicsElectoral Systems and Political Participation · Game Theory and Voting Systems
