# A calibrated BISG for inferring race from surname and geolocation

arXiv: https://arxiv.org/abs/2304.09126 · HTML: https://mlsanity.com/paper/2304.09126/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Apr 2023.

## Built on by (most cited first, 2 of 2)

- [Addressing Discretization-Induced Bias in Demographic Prediction](https://mlsanity.com/paper/2405.16762/) (2024)
- [Using Embedding Models to Improve Probabilistic Race Prediction](https://mlsanity.com/paper/2604.22555/) (2026)

## Abstract (arXiv)

Bayesian Improved Surname Geocoding (BISG) is a ubiquitous tool for predicting race and ethnicity using an individual's geolocation and surname. Here we demonstrate that statistical dependence of surname and geolocation within racial/ethnic categories in the United States results in biases for minority subpopulations, and we introduce a raking-based improvement. Our method augments the data used by BISG--distributions of race by geolocation and race by surname--with the distribution of surname by geolocation obtained from state voter files. We validate our algorithm on state voter registration lists that contain self-identified race/ethnicity.