Guidelines for Intersectional Analysis in Science and Technology: Implementation and Checklist Development

European Science Editing 51: e162102, doi: 10.3897/ese.2025.e162102

Londa Schiebinger^‡, Mathias Wullum Nielsen^§, Elena Gissi^|, Shirin Heidari^¶, Richard Horton^#, Kari C. Nadeau^¤, Dorothy Ngila^«, Safiya Umoja Noble^», Hee Young Paik^˄, Girmaw Abebe Tadesse^˅, Eddy Y. Zeng^¦, James Zou^‡, Joan Marsh^ˀ

‡ Stanford University, Stanford, United States of America§ University of Copenhagen, Copenhagen, Denmark| National Biodiversity Future Centre, Venice, Italy¶ Geneva Graduate Institute, Geneva, Switzerland# The Lancet, London, United Kingdom¤ Harvard University, Boston, United States of America« National Research Foundation of South Africa, Pretoria, South Africa» University of California, Los Angeles, United States of America˄ Seoul National University, Seoul, Republic of Korea˅ Microsoft AI for Good Research Lab, Nairobi, Kenya¦ South China University of Technology, Guangzhou, Chinaˀ The Lancet Psychiatry, London, United Kingdom

Corresponding author: Londa Schiebinger ( schieb@stanford.edu )

Academic editor: Ksenija Bazdaric

© Londa Schiebinger, Mathias Wullum Nielsen, Elena Gissi, Shirin Heidari, Richard Horton, Kari C. Nadeau, Dorothy Ngila, Safiya Umoja Noble, Hee Young Paik, Girmaw Abebe Tadesse, Eddy Y. Zeng, James Zou, Joan Marsh.

This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Citation: Schiebinger L, Nielsen MW, Gissi E, Heidari S, Horton R, Nadeau KC, Ngila D, Noble SU, Paik HY, Tadesse GA, Zeng EY, Zou J, Marsh J (2025) Guidelines for Intersectional Analysis in Science and Technology: Implementation and Checklist Development. European Science Editing 51: e162102. https://doi.org/10.3897/ese.2025.e162102

Abstract

Intersectional analysis goes beyond consideration of single variables to examine the compounded impact at the intersections of, for example, gender and race, or geographical location and caste. The Guidelines for Intersectional Analysis in Science and Technology (GIST) help researchers, journal editors, and funding agencies systematically integrate intersectional analysis into relevant domains of science and technology. These guidelines serve as a roadmap for quantitative intersectional analysis throughout the research process—from setting strategic research priorities and shaping research questions to data collection, analysis, and interpretation. Here we provide a checklist to facilitate author and journal editor compliance with the guidelines. We recommend that the GIST checklist be added to journals’ “Information for Authors”. The goal is to reset the research default to include intersectional analysis, where appropriate. Intersectional analysis leads to better science: precision in research best guides effective social and environmental policies that, in turn, enhance global equity and sustainability.

Keywords

Editorial process, Intersectional analysis, Information for authors, Research equity, Sex and Gender Equity in Research