Towards Statistical Best Practices For Gender And Sex Data

Authors

Suzanne Thornton, Swarthmore College
D. Roy
S. Parry
D. Lalonde
W. Martinez
R. Ellis
D. Corliss

Document Type

Article

Publication Date

2-1-2022

Published In

Significance

Abstract

Suzanne Thornton, Dooti Roy, Stephen Parry, Donna LaLonde, Wendy Martinez, Renee Ellis and David Corliss call for a more inclusive – and informative – approach to collecting data on human gender and sex.

Comments

This is a pre-copyedited, author-produced version of an article accepted for publication in Significance following peer review. The version of record is available online.

Recommended Citation

Suzanne Thornton, D. Roy, S. Parry, D. Lalonde, W. Martinez, R. Ellis, and D. Corliss. (2022). "Towards Statistical Best Practices For Gender And Sex Data". Significance. Volume 19, Issue 1. 40-45. DOI: 10.1111/1740-9713.01614
https://works.swarthmore.edu/fac-math-stat/307