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<p>Scholarly interest in how the interactions among identities—e.g., race, sex, and differing-ability—influence social outcomes such as socioeconomic status—has outpaced methodological advances allowing us to understand these dynamics. Using data measuring the characteristics of 8,332,687 people across 478 U.S. counties and a novel suite of machine learning methods, we investigate geographic manifestations of intersectionality. As the key outcome, we use socioeconomic status as a proxy for wellbeing. We find, first, that there are distinct patterns among the specific dimensions of identity that operate interactively to determine earning differences. Disaggregating by occupation, our results show considerable additional county level intersectionality variation. Third, inspecting two counties with the greatest level of detail, we find varying contributions of each dimension of identity to the baseline disparity of earnings by sex. Our results depict an unprecedented level of geographic complexity in how intersectionality conditions earnings in the U.S.</p>

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Intersectionality in the United States: examining impacts of identity using us census microdata

  • 期刊论文

  • 发表日期：

    2026年7月28日

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  • Serena Madsen,
  • Richard Medina,
  • Simon Brewer,
  • Andrew Linke

摘要

Scholarly interest in how the interactions among identities—e.g., race, sex, and differing-ability—influence social outcomes such as socioeconomic status—has outpaced methodological advances allowing us to understand these dynamics. Using data measuring the characteristics of 8,332,687 people across 478 U.S. counties and a novel suite of machine learning methods, we investigate geographic manifestations of intersectionality. As the key outcome, we use socioeconomic status as a proxy for wellbeing. We find, first, that there are distinct patterns among the specific dimensions of identity that operate interactively to determine earning differences. Disaggregating by occupation, our results show considerable additional county level intersectionality variation. Third, inspecting two counties with the greatest level of detail, we find varying contributions of each dimension of identity to the baseline disparity of earnings by sex. Our results depict an unprecedented level of geographic complexity in how intersectionality conditions earnings in the U.S.