City Sampling for Citizens' Assemblies

Fuente: arXiv
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Main Authors: Gölz, Paul, Maly, Jan, Schmidt-Kraepelin, Ulrike, Utke, Markus, Verpoort, Philipp C.
Format: Preprint
Published: 2025
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_version_ 1866914029680721920
author Gölz, Paul
Maly, Jan
Schmidt-Kraepelin, Ulrike
Utke, Markus
Verpoort, Philipp C.
author_facet Gölz, Paul
Maly, Jan
Schmidt-Kraepelin, Ulrike
Utke, Markus
Verpoort, Philipp C.
contents In citizens' assemblies, a group of constituents is randomly selected to weigh in on policy issues. We study a two-stage sampling problem faced by practitioners in countries such as Germany, in which constituents' contact information is stored at a municipal level. As a result, practitioners can only select constituents from a bounded number of cities ex post, while ensuring equal selection probability for constituents ex ante. We develop several algorithms for this problem. Although minimizing the number of contacted cities is NP-hard, we provide a pseudo-polynomial time algorithm and an additive 1-approximation, both based on separation oracles for a linear programming formulation. Recognizing that practical objectives go beyond minimizing city count, we further introduce a simple and more interpretable greedy algorithm, which additionally satisfies an ex-post monotonicity property and achieves an additive 2-approximation. Finally, we explore a notion of ex-post proportionality, for which we propose two practical algorithms: an optimal algorithm based on column generation and integer linear programming and a simple heuristic creating particularly transparent distributions. We evaluate these algorithms on data from Germany, and plan to deploy them in cooperation with a leading nonprofit organization in this space.
format Preprint
id arxiv_https___arxiv_org_abs_2509_07557
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle City Sampling for Citizens' Assemblies
Gölz, Paul
Maly, Jan
Schmidt-Kraepelin, Ulrike
Utke, Markus
Verpoort, Philipp C.
Computer Science and Game Theory
Probability
In citizens' assemblies, a group of constituents is randomly selected to weigh in on policy issues. We study a two-stage sampling problem faced by practitioners in countries such as Germany, in which constituents' contact information is stored at a municipal level. As a result, practitioners can only select constituents from a bounded number of cities ex post, while ensuring equal selection probability for constituents ex ante. We develop several algorithms for this problem. Although minimizing the number of contacted cities is NP-hard, we provide a pseudo-polynomial time algorithm and an additive 1-approximation, both based on separation oracles for a linear programming formulation. Recognizing that practical objectives go beyond minimizing city count, we further introduce a simple and more interpretable greedy algorithm, which additionally satisfies an ex-post monotonicity property and achieves an additive 2-approximation. Finally, we explore a notion of ex-post proportionality, for which we propose two practical algorithms: an optimal algorithm based on column generation and integer linear programming and a simple heuristic creating particularly transparent distributions. We evaluate these algorithms on data from Germany, and plan to deploy them in cooperation with a leading nonprofit organization in this space.
title City Sampling for Citizens' Assemblies
topic Computer Science and Game Theory
Probability
url https://arxiv.org/abs/2509.07557