# Neutralizing Self-Selection Bias in Sampling for Sortition

arXiv: https://arxiv.org/abs/2006.10498 · HTML: https://mlsanity.com/paper/2006.10498/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jun 2020.

## Built on by (most cited first, 7 of 7)

- [Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report](https://mlsanity.com/paper/2210.15767/) (2022)
- [Generative Social Choice: The Next Generation](https://mlsanity.com/paper/2505.22939/) (2025)
- [Differentially Private Condorcet Voting](https://mlsanity.com/paper/2206.13081/) (2022)
- [Online Selection of Diverse Committees](https://mlsanity.com/paper/2105.09295/) (2021)
- [Alternates, Assemble! Selecting Optimal Alternates for Citizens' Assemblies](https://mlsanity.com/paper/2506.15716/) (2025)
- [The Distortion of Binomial Voting Defies Expectation](https://mlsanity.com/paper/2306.15657/) (2023)
- [Temporal Panel Selection in Ongoing Citizens' Assemblies](https://mlsanity.com/paper/2602.16194/) (2026)

## Abstract (arXiv)

Sortition is a political system in which decisions are made by panels of randomly selected citizens. The process for selecting a sortition panel is traditionally thought of as uniform sampling without replacement, which has strong fairness properties. In practice, however, sampling without replacement is not possible since only a fraction of agents is willing to participate in a panel when invited, and different demographic groups participate at different rates. In order to still produce panels whose composition resembles that of the population, we develop a sampling algorithm that restores close-to-equal representation probabilities for all agents while satisfying meaningful demographic quotas. As part of its input, our algorithm requires probabilities indicating how likely each volunteer in the pool was to participate. Since these participation probabilities are not directly observable, we show how to learn them, and demonstrate our approach using data on a real sortition panel combined with information on the general population in the form of publicly available survey data.