Best Practices for Collecting Gender and Sex Data

TL;DR

This paper discusses the complexities of collecting and analyzing human sex and gender data, emphasizing ethical considerations, privacy concerns, and proposing best practices for more accurate and respectful data collection.

Contribution

It offers statistically informed recommendations for collecting and analyzing sex and gender data that respect individual identities and enhance data quality.

Findings

Provides guidelines for ethical data collection

Highlights privacy protection strategies

Suggests standards for higher quality data

Abstract

The measurement and analysis of human sex and gender is a nuanced problem with many overlapping considerations including statistical bias, data privacy, and the ethical treatment of study subjects. Traditionally, human gender and sex have been categorized and measured with respect to an artificial binary system. The continuation of this tradition persists mainly because it is easy to replication and not, as we argue, because it produces the most valuable scientific information. Sex and gender identity data is crucial for many applications of statistical analysis and many modern scientists acknowledge the limitations of the current system. However, discrimination against sex and gender minorities poses very real privacy concerns when collecting and distributing gender and sex data. As such, extra thoughtfulness and care is essential to design safe and informative scientific studies. In this paper, we present statistically informed recommendations for the data collection and analysis of human subjects that not only respect each individual's identity and protect their privacy, but also establish standards for collecting higher quality data.