Tool to Assess Survey Data for Racial Bias
Applying a Racial Equity Lens to Research
Researchers routinely use publicly available datasets to answer research questions.
Yet it is unclear how often researchers consider whether the dataset could be racially or ethnically biased. Such a bias could have implications for their analysis and the interpretations drawn from the data.
Chapin Hall developed a tool to assess survey datasets for racial and ethnic bias. This tool provides a clear, systematic method for researchers to determine whether survey data they plan to analyze were collected with a racial equity lens or not. Using the Racial Bias in Data Assessment Tool could lead to less racially biased research.
The goals of the project were to:
- Develop an evidence-based methodology to assess survey datasets for racial and ethnic bias.
- Call attention to potential ways research can contain racial and ethnic bias, especially when collecting data.
- Provide guidance to researchers for steps to take when survey datasets have moderate to high risk of racial and ethnic bias.
Our project began with a literature review that identified key topics to include in the data assessment tool and critical supplemental information. After developing the tool, we tested it by assessing a publicly available survey dataset for potential racial bias. We then sought advice and guidance from an Advisory Committee. The Committee was comprised of Chapin Hall experts specializing in applying a racial equity lens in research, data collection and analysis, and evidence use in policy and practice decisions.
The Racial Bias in Data Assessment Tool is available to anyone interested in assessing a survey dataset for potential racial and ethnic bias. We plan to collect feedback from researchers who use the tool to inform future revisions.
The Chapin Hall research team is led by Senior Researcher Dr. Tiffany Burkhardt and includes researchers  Lee Ann Huang, and Reiko Kakuyama-Villaber. Research Fellow Dr. Julie Spielberger served as a research consultant. Our advisory committee included Dr. Brian Chor, Dr. Karen Fenton-LeShore, Dr. Robert Goerge, Yolanda Green-Rogers, Dr. Kiljoong Kim, and Emily Wiegand.
For more information about this project, contact Dr. Tiffany Burkhardt.
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