Party Over Principles: Determinants of Public Opinion on Redistricting Reform

Peter T. McLaughlin

State Politics and Policy Quarterly2025https://doi.org/10.1017/spq.2024.34article
AJG 2
Weight
0.41

What the paper says

How does the mass public form attitudes on electoral rules and reforms? Existing research on this question reveals a trade-off between principles, such as fairness, and partisan self-interest. I use two survey experiments on state legislative redistricting to explore how voters weigh principles against partisan self-interest when forming opinions on electoral reforms. First, I ask whether the public’s partisan self-interest motivation stems more from individual representation considerations or broader partisan power considerations. I find that both considerations provide a powerful enough incentive to activate partisan self-interest regarding preferences for state legislative district maps. Unexpectedly, the two considerations have quite similar effects on public support for redistricting reforms. Second, I explore the principles versus partisan self-interest trade-off through the lens of loss aversion, a concept developed in behavioral economics. In line with expectations, I find that preventing loss provides a more powerful incentive for Americans to violate democratic principles than achieving partisan gain. In sum, this research sheds light on voters’ decision between principles and partisan self-interest in the formation of opinion on electoral reform.

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https://doi.org/https://doi.org/10.1017/spq.2024.34

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@article{peter2025,
  title        = {{Party Over Principles: Determinants of Public Opinion on Redistricting Reform}},
  author       = {Peter T. McLaughlin},
  journal      = {State Politics and Policy Quarterly},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1017/spq.2024.34},
}

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Evidence weight

0.41

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

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 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.