What is it about?
This article explores how research practices often misrepresent or exclude nonbinary people, especially through the use of outdated or binary-only gender questions. The paper includes a quick reference table for practical use, which provides a clear, comparative guide to the most ethical and accurate ways to ask about gender, including examples of question formats, their pros and cons, and when each is appropriate. The authors examine the entire research data lifecycle, planning, collecting, analyzing, and sharing, and offer concrete guidance for inclusive gender representation at every stage.
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Why is it important?
More than 2 million people in the U.S. identify as nonbinary or gender nonconforming, yet most datasets still use only “male” and “female” options, or lump everyone else into “Other.” This exclusion contributes to what scholars refer to as data violence, thereby undermining the ethical and accurate conduct of research. By offering a practical, quick-reference Table and grounding it in lived experience, this paper empowers researchers to do better. It provides evidence-based recommendations for designing inclusive gender questions and outlines ethical data practices that avoid misgendering or erasure. It also calls on data repositories to adopt inclusive metadata and ontologies that support gender-diverse identities long-term.
Perspectives
This paper provides researchers something they often lack: a tangible, vetted way to ask the gender question the right way. As a nonbinary researcher and contributor to this piece, I’ve repeatedly encountered forms and datasets that ask me to be an “Other” just to show up in the data. This work is about making sure no one has to experience that. It’s about helping researchers understand that inclusion isn’t just a checkbox; it’s a matter of justice, accuracy, and dignity. Good data starts with good questions, and if we want research that reflects the richness of the world we live in, we need to change how we define, collect, and share gender data. This article is a guide on how to do that better.
Dr Sam Leif
Read the Original
This page is a summary of: Do I Have To Be An “Other” To Be Myself? Exploring Gender Diversity In Taxonomy, Data Collection, And Through The Research Data Lifecycle, Journal of eScience Librarianship, November 2021, University of Massachusetts Medical School,
DOI: 10.7191/jeslib.2021.1219.
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