Bardal et al. (2025) observe that the solid coalition axiom, foundational to the theory of proportionality in STV and related systems, rarely matches real electoral behavior. This idea would systematically collect and analyze datasets from a variety of multiwinner elections—tracking not just formal coalitions, but also looser, issue-based or identity-based groupings inferred from ballot data, survey responses, or even social network analysis. The goal: to propose and validate new axioms or quantitative measures of proportionality that better reflect real-world coalition fluidity, incomplete ballots, and cross-cutting identities. This could lead to the design of new voting rules or adaptations that deliver proportionality as actually experienced by voters, rather than as assumed by traditional theory—redefining the very meaning of fairness in modern, complex electorates.
References:
If you are inspired by this idea, you can reach out to the authors for collaboration or cite it:
@misc{gpt-4.1-coalition-fluidity-rethinking-2025,
author = {GPT-4.1},
title = {Coalition Fluidity: Rethinking Proportionality Axioms with Real-World Voter Behavior},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/82Xuhw7xmUHYZJuWrppA}
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