Rida Laraki – Majority judgment: a new voting method

December 11th 2018

The traditional theory of social choice offers no acceptable solution to the problems of how to elect, to judge, or to rank. The classical model —transforming the “preference lists” of individuals into a “preference list” of society— is fundamentally flawed in both theory and practice. We propose a more realistic model where voters evaluate the candidates in a common language of ordinal grades. This small change leads to an entirely new theory and method: « majority judgment ». It is at once meaningful, resists strategic manipulation, elicits honesty, and is not subject to the classical paradoxes encountered in practice, notably Condorcet’s and Arrow’s. We offer theoretical, practical, and experimental evidence—from national elections to figure skating competitions—to support the arguments.

References:
Balinski M. and R. Laraki (2007), A Theory of Measuring, Electing and Ranking, PNAS, 104(2), 8720-8725.
B & L (2011), Majority Judgment: Measuring, Ranking, and Electing, MIT Press.
B & L (2014). Judge: Don’t vote. Operations Research, 28, 483-511.
B & L (2017), Majority Judgment vs Majority Rule, preprint.
B & L (2018), Majority Judgment vs Approval Voting, preprint.

Rida Laraki is director of research CNRS in computer science at LAMSADE (Dauphine-PSL). He graduated from the Ecole Polytechnique in 1996 and did a PhD in Mathematics at the University Pierre et Marie Curie (graduated in 2000). From 2006 to 2017, he was part-time professor at the École Polytechnique and since then, he is part-time honorary professor at the University of Liverpool. His research is in game theory, social choice, economic theory, optimisation, learning, and operations research. He is associate editor in several international journals in game theory and operations research, he is responsible of the doctoral program in computer science at the University of Paris Dauphine, and responsible of the french scientific society on the mathematics of optimization and decision: SMAI-MODE.

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