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  1. Home
  3. Residuals: (or On The Use Of Statistical Analysis To Perpetuate Systemic Racism).
  1. Home
  3. Residuals: (or On The Use Of Statistical Analysis To Perpetuate Systemic Racism).

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Residuals: (or On the Use of Statistical Analysis to Perpetuate Systemic Racism).

David Claudio1

  • 1Associate Professor of Industrial Engineering, Department of Mechanical and Industrial Engineering, UMass Lowell, Lowell, MA, USA.

Health Promotion Practice
|May 1, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

Structural racism in health systems marginalizes Hispanic communities. Analysis of public health programs reveals systemic exclusion, necessitating inclusive and equitable solutions for all minorities.

Keywords:
OutliersResidualsStatisticsSystemic Racism

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Area of Science:

  • Public Health
  • Industrial Engineering
  • Sociology

Background:

  • Personal experiences of marginalization as a Hispanic individual in the U.S. highlight systemic prejudices.
  • The term "Hispanic" is intentionally used to acknowledge a history of colonization and ongoing identity reclamation.
  • Current U.S. political climate exacerbates discrimination against Spanish speakers and people of color.

Purpose of the Study:

  • To examine structural racism within health systems through the lens of industrial engineering and public health.
  • To identify specific areas where Hispanic populations are underserved or excluded in public health programs.
  • To advocate for the development of more inclusive and equitable health systems.

Main Methods:

  • Utilizes a holistic process view, common in industrial engineering, to map public health programs.
  • Applies statistical knowledge to identify patterns of exclusion and bias within health data.
  • Integrates lived experiences and qualitative observations of prejudice into the analysis.

    • Main Results:

    • Public health programs, when analyzed holistically, reveal systemic oversights that leave Hispanic individuals behind.
    • Biases embedded in data categorization and public health systems create inherent structures of exclusion.
    • Instances of discrimination based on skin color, language, and accent underscore the reality of minority experiences.

    Conclusions:

    • Addressing structural racism in health systems requires acknowledging and studying the "residuals" of exclusion.
    • Data-driven insights, combined with an understanding of lived experiences, are crucial for creating equitable systems.
    • The goal is to move towards public health systems that are inclusive and equitable for all minority groups.