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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Updated: Oct 8, 2025

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Intersectional inequalities in science.

Diego Kozlowski1, Vincent Larivière2,3,4, Cassidy R Sugimoto4,5

  • 1Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-Sur-Alzette 4364, Luxembourg.

Proceedings of the National Academy of Sciences of the United States of America
|January 5, 2022
PubMed
Summary
This summary is machine-generated.

Diversity in science expands knowledge, but minoritized groups face citation disadvantages. Addressing systemic barriers and promoting inclusive networks are crucial for robust scientific progress.

Keywords:
bibliometricsgenderintersectionalityracescience of science

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Area of Science:

  • Sociology of Science
  • Bibliometrics
  • Diversity and Inclusion in STEM

Background:

  • The US scientific workforce lacks diversity, predominantly comprising White men.
  • Systemic barriers hinder women and minoritized populations' entry into science.
  • Few studies examine the impact of these inequalities on scientific knowledge from an intersectional perspective.

Purpose of the Study:

  • To conduct a large-scale bibliometric analysis of the relationship between intersectional identities, research topics, and scientific impact.
  • To investigate how diversity in the scientific workforce influences the expansion of the knowledge base.
  • To identify citation disadvantages faced by minoritized individuals within different scientific topics.

Main Methods:

  • Large-scale bibliometric analysis.
  • Examination of homophily between scientific identities and research topics.
  • Analysis of citation patterns across diverse scientific fields and demographic groups.

Main Results:

  • A significant homophily exists between scientific identities and research topics, suggesting diversity correlates with knowledge expansion.
  • Minoritized individuals experience citation disadvantages, both within and between specific research topics.
  • Topic selection by minoritized scientists may incur a cost in terms of scientific impact.

Conclusions:

  • Enhancing the robustness of scientific knowledge requires addressing systemic inequalities.
  • Research organizations should resource underfunded research areas adequately.
  • Facilitating access for minoritized individuals into high-prestige scientific networks and topics is essential for equitable scientific advancement.