Brown Bag Seminar| When Does Party Cooperation Inform Voter Judgments of Policy Proximity? A Cross-National Analysis of Heuristic Use in Multi-Party Democracies?

Brown Bag Seminar| When Does Party Cooperation Inform Voter Judgments of Policy Proximity? A Cross-National Analysis of Heuristic Use in Multi-Party Democracies?

Brown Bag Seminar| When Does Party Cooperation Inform Voter Judgments of Policy Proximity? A Cross-National Analysis of Heuristic Use in Multi-Party Democracies?

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Title:  When Does Party Cooperation Inform Voter Judgments of Policy Proximity? A Cross-National Analysis of Heuristic Use in Multi-Party Democracies

Presenter: Prof. Philip Santoso.  Assistant Professor of Political Science

Discussant: Prof. Jason Todd.  Assistant Professor of Political Science

Venue: IB 1050

Time: Jan 29 11am-12pm

Abstract

In complex multiparty democracies, citizens face the challenge of interpreting elite behavior to locate parties on the policy spectrum. This paper examines when and why voters use cooperation between their own party and an out-party as a heuristic for judging policy distance. Drawing on the theory of ecological rationality, I argue that cooperation functions as an efficient heuristic when it is cheap to observe, simple to apply, and sufficiently accurate to support inferences about policy alignment. Using original survey data from Canada, Denmark, Germany, and the United Kingdom across fifteen policy domains, I show that perceived cooperation between a voter’s party and an out-party is consistently associated with voters perceiving that out-party as closer to their own policy positions. This relationship is strongest among politically knowledgeable partisans, on polarized issues, and when the out-party is perceived as ideologically extreme. These findings demonstrate how ecological rationality conditions voter reasoning and highlight inter-party cooperation as a dynamic elite cue shaping mass perceptions of policy alignment and democratic representation.

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2026-01-29 @ 11:00 AM to
2026-01-29 @ 12:00 AM
 

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