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.
Translators: Mitsue Sugimoto, Ph.D. candidate in the philosophy of science, University of Toyko
Mariko Ogawa, Professor Emerita of Mie University
Disclaimer – Only the English version of the ‘Guidelines for Intersectional Analysis in Science and Technology: Implementation and Checklist Development’ has been fully approved by the EASE Council. Translations into other languages are provided by volunteers as a service to our readers and have not been validated by EASE or any other organisation. EASE therefore accepts no legal responsibility for the consequences of the use of the translations.
Author(s)
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
Publisher
European Science Editing
DOI
https://doi.org/10.3897/ese.2025.e162102.jp
Categories
Guidelines