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

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.

Authors

Institutions

Publication Details

Journal
European Science Editing
Published
2025-09-01
DOI
https://doi.org/10.3897/ese.2025.e162102
Citations
1
Primary Topic
Innovation Policy and R&D
Type
article
Field-Weighted Citation Impact
3.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Safiya Noble, Dorothy Ngila, James Zou, Girmaw Abebe Tadesse et al.
1 citations
European Science Editing
Innovation Policy and R&D
3.13
article

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

Safiya Noble, Dorothy Ngila, James Zou, Girmaw Abebe Tadesse, Kari Christine Nadeau, Shirin Heidari, Elena Gissi, Eddy Yongping Zeng, Mathias Wullum Nielsen, Hee Young Paik, Richard Horton, Londa Schiebinger, Joan Marsh
article en
1 citations

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.

European Science EditingVol. 51
University of Copenhagen (DK), Harvard University (US), Seoul National University (KR), University of California, Los Angeles (US), Lancet Laboratories (ZA), National Biodiversity Institute (CR), National Research Foundation (ZA), South China University of Technology (CN), Graduate Institute of International and Development Studies (CH), Stanford University (US)
Openalex Percentile: Top 7%
Innovation Policy and R&D
3.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.