Does Quadratic Voting for Survey Research Improve Policy-Making and Decision Outcomes?

Madeline E. Bassetti et al.

Review of Law & Economics2025https://doi.org/10.1515/rle-2025-0078article
AJG 2ABDC B
Weight
0.37

What the paper says

Abstract This pilot study explores the feasibility of using Quadratic Voting for Survey Research (QVSR) as an alternative to the traditional Likert scale in a municipal decision-making context. By observing decision-makers’ behavior and voting outcomes, the study provides descriptive evidence on how these two survey methodologies perform in practice. While standard democratic processes often overlook the intensity of citizen preferences, QVSR allows individuals to express preference strength using a limited credit system. In contrast, the Likert scale, though widely used, may be susceptible to response biases and assumptions about sincerity. Previous studies have demonstrated the theoretical and experimental promise of QVSR; this pilot extends that work by assessing its feasibility and practical implementation in a real-world policy environment. Conducted in the Gabba Ward municipality in Brisbane, Australia, the study randomly assigned citizens and policymakers to QVSR or Likert conditions and describes patterns in the alignment between citizen responses and councilor voting. The results are exploratory and intended to inform future, larger-scale evaluations of QVSR’s potential to support more nuanced and representative forms of democratic engagement.

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https://doi.org/https://doi.org/10.1515/rle-2025-0078

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@article{madeline2025,
  title        = {{Does Quadratic Voting for Survey Research Improve Policy-Making and Decision Outcomes?}},
  author       = {Madeline E. Bassetti et al.},
  journal      = {Review of Law & Economics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1515/rle-2025-0078},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.