Temporal Panel Selection in Ongoing Citizens' Assemblies
Yusuf Hakan Kalayci, Evi Micha

TL;DR
This paper introduces a formal framework and algorithms for selecting rotating panels in ongoing citizens' assemblies, ensuring proportional representation and individual fairness over time in a dynamic, metric space population.
Contribution
It formalizes the concept of temporal panel selection, extending proportional representation to a sequential setting with algorithms guaranteeing fairness and representation.
Findings
Algorithms achieve proportional representation within panels and across sequences.
The framework ensures individual fairness over multiple rounds.
Extension of existing models to a temporal, metric space setting.
Abstract
Permanent citizens' assemblies are ongoing deliberative bodies composed of randomly selected citizens, organized into panels that rotate over time. Unlike one-off panels, which represent the population in a single snapshot, permanent assemblies enable shifting participation across multiple rounds. This structure offers a powerful framework for ensuring that different groups of individuals are represented over time across successive panels. In particular, it allows smaller groups of individuals that may not warrant representation in every individual panel to be represented across a sequence of them. We formalize this temporal sortition framework by requiring proportional representation both within each individual panel and across the sequence of panels. Building on the work of Ebadian and Micha (2025), we consider a setting in which the population lies in a metric space, and the goal…
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Taxonomy
TopicsGame Theory and Voting Systems · Mobile Crowdsensing and Crowdsourcing · Ethics and Social Impacts of AI
