| Last week, I participated in the “Ensuring the Economy Works for Black Women” webinar hosted by the Women’s Initiative, Center for American Progress. One of the questions from the audience was if data disaggregation is about data collection or analysis. The answer is both. Surveys must ask questions about race, ethnicity, sexual orientation, gender identity, family structure, education, physical and mental ability, etc. When data is collected in this way, researchers are afforded the opportunity to disaggregate data for analysis.
I describe data disaggregation as the mechanics behind how data are analyzed and intersectionality as the lens for interpreting the results. Data disaggregation moves us away from gender bias; men are assumed to be the norm, and racial bias, white, is assumed to be the norm. It allows us to center the conversation on different groups, to see the nuances in outcomes, and to craft more effective policies.
Tomorrow is “Equal Pay Day” for Black women. This day represents how much additional time Black women would have to work to earn as much money as White men did for the same year. While this data is disaggregated by race, it is not disaggregated by family structure or educational attainment, which research shows influences earnings. Additional disaggregation is needed to see the disparities by education attainment and family structure.
I’d like to share with you an important piece by our Board Secretary, Pedro Da Costa, titled “The COVID-19 Crisis Has Wiped Out Nearly Half Of Black Small Businesses.” Pedro’s article is an important reminder of the loss of economic well-being experienced by small businesses. It is based on a New York Federal Reserve Bank report that suggests the fragility of Black-owned small banks is rooted in finance—lower profits, savings, and banking relationships.
Rhonda V. Sharpe is president of the Women’s Institute for Science, Equity and Race. |
