Misrepresentation in District Voting
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 81-86.
Abstract
Voting systems in which voters are partitioned to districts encourage accountability by providing voters an easily identifiable district representative, but can result in a selection of representatives not representative of the electorate's preferences. In some cases, a party may have a majority of the popular vote, but lose the elections due to districting effects. We define the Misrepresentation Ratio which quantifies the deviation from proportional representation in a district-based election, and provide bounds for this ratio under various voting rules. We also examine probabilistic models for election outcomes, and provide an algorithm for approximating the expected Misrepresentation Ratio under a given probabilistic election model. Finally, we provide simulation results for several such probabilistic election models, showing the effects of the number of voters and candidates on the misrepresentation ratio.
@inproceedings{ijcai2016p19,
title = {Misrepresentation in District Voting},
author = {Bachrach, Yoram and Lev, Omer and Lewenberg, Yoad and Zick, Yair},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {81--86},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/19},
}
TY - CPAPER TI - Misrepresentation in District Voting AU - Bachrach, Yoram AU - Lev, Omer AU - Lewenberg, Yoad AU - Zick, Yair T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 81 EP - 86 UR - https://ijcai.org/proceedings/2016/19 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
