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科技的交叉性分析

Intersectional analysis for science and technology.

作者信息

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

机构信息

Department of Sociology, University of Copenhagen, Copenhagen, Denmark.

National Research Council, Institute of Marine Sciences, Venice, Italy.

出版信息

Nature. 2025 Apr;640(8058):329-337. doi: 10.1038/s41586-025-08774-w. Epub 2025 Apr 9.

DOI:10.1038/s41586-025-08774-w
PMID:40205207
Abstract

Intersectionality describes interdependent systems of inequality related to sex, gender, race, age, class and other socio-political dimensions. By focusing on the compounded effects of social categories, intersectional analysis can enhance the accuracy and experimental efficiency of science. Here we extend intersectional approaches that were predominantly developed in the humanities, social sciences and public health to the fields of natural science and technology, where this type of analysis is less established. Informed by diverse global and disciplinary examples-from enhancing facial recognition for diverse user bases to mitigating the disproportionate impact of climate change on marginalized populations-we extract methods to demonstrate how quantitative intersectional analysis functions throughout the research process, from strategic considerations for establishing research priorities to formulating research questions, collecting and analysing data and interpreting results. Our goal is to offer a set of guidelines for researchers, peer-reviewed journals and funding agencies that facilitate systematic integration of intersectional analysis into relevant domains of science and technology. Precision in research best guides effective social and environmental policy aimed at achieving global equity and sustainability.

摘要

交叉性描述了与性别、种族、年龄、阶级及其他社会政治维度相关的相互依存的不平等系统。通过关注社会类别的复合效应,交叉性分析能够提高科学研究的准确性和实验效率。在此,我们将主要在人文、社会科学和公共卫生领域发展起来的交叉性方法扩展到自然科学和技术领域,而这类分析在这些领域的应用尚不广泛。基于全球和各学科的不同实例——从增强针对不同用户群体的面部识别到减轻气候变化对边缘化人群的不成比例影响——我们提炼出方法,以展示定量交叉性分析在整个研究过程中的作用,从确立研究重点的战略考量到提出研究问题、收集和分析数据以及解读结果。我们的目标是为研究人员、同行评审期刊和资助机构提供一套指导方针,以促进将交叉性分析系统地整合到科学技术的相关领域。研究的精确性最有助于制定旨在实现全球公平与可持续性的有效社会和环境政策。

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The Lancet Group's new guidance to authors on reporting race and ethnicity.
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