onto those who haven’t been reared in our context.
Adding insult to injury, we’re professionally trained and rewarded to make White people the default referent group that Blacks are measured against. In doing so, we acquire a tendency to center White people in our work.
I was first introduced to the practice of White centering later in life as a graduate researcher, when I first learned how to carry out a regression analysis, a staple of quantitative research. Regression analyses examine the relationship between two or more variables—say, the impact of race on academic achievement. For a category like race, one must pick a referent group for the purposes of comparison. I was taught to make White men (not White women) the default referent in most of my models. In the aforementioned example, achievement test scores of White women, Black women and men, as well as their Hispanic non-White, Asian, and Native American counterparts are measured against White men. Regression models are mathematically most stable if the referent group is the largest within the sample you are drawing from. For that reason, in the United States, data sources that make note of racial categories are generally presented sequentially, with “White,” the largest single racial group, listed first.
But if we really are interested in improving Black communities, it’s much less useful to select Whites as the referent. Historical discrimination categorically leveled against Black people makes it difficult for many research projects to make a true apples-to-apples comparison with White people. For instance, to compare a Black person’s income to that of a White person without accounting for wealth that was systematically denied to Black people by federal policy is to bury one’s head in the sand and ignore the roles of racism and White privilege. Racism is a common denominator for Black people; it’s a given. It’s much more useful, in many cases, to examine the variation within the Black population to see what factors and conditions can be attributed to differences.
In leading up to my study on devaluation (presented in chapter 2), I examined incomes of Black families living in Black-majority cities. It was a very simple study that simply asked, “Where are Blacks with high incomes living?” Incomes are proxies for decent job opportunities, good schools, and safe living environments. Figure I-1, a national map of Black-majority cities ranked by median household incomes of Black families, shows that 124 communities outpace the national median household income for all races ($53,889), according to data from the 2015 American Community Survey.3 Black families are especially thriving in various city/suburbs in Maryland, which hosts more than half the top 124 Black-majority cities. The DMV—that is, the D.C.-Maryland-Virginia area—is Black bougie heaven.
Using median income as a proxy for financial status is a very imperfect practice. Measuring the middle of an income distribution—median income—of a particular city often masks the earning and labor disparities of particular groups that are not employed by the dominant industries in a market. That’s especially the case for Black families when popular publications put out various lists for the wealthiest places to live. Not everyone benefits from a thriving economy. That’s why colleagues of mine within the Brookings Metro program encourage more robust measures of economic health that include growth, inclusion, and prosperity.4 However, detailing strength among Black populations within Black cities offers a vantage point to opportunities that may lead to investments.
FIGURE I-1. BLACK-MAJORITY CITIES WITH MEDIAN HOUSEHOLD INCOME ABOVE THE NATIONAL AVERAGE ($57,652) IN 2017
SOURCE: American Community Survey U.S. Census Bureau estimates.
I examined home prices in these neighborhoods and found that many of the homes were of similar quality and had similar neighborhood amenities as those in similarly situated White neighborhoods. However, they were priced significantly less—the basis for my devaluation studies. One might say homeowners in Black neighborhoods received a discount. However, those same communities are hemorrhaging vital tax revenues and equity merely because of the concentration of Black people. The price difference excited me because it was clear that homes in Black neighborhoods were not the problem society portends them to be—they were devalued. Instead of centering White neighborhoods as a standard to be reached, I sought Black assets and found a path toward a solution that didn’t involve fixing Black people. We can pursue solving for devaluation.
When acclaimed author Toni Morrison was asked in a 1998 interview whether she would begin to feature White characters more prominently in her work, she responded, “You can’t understand how powerfully racist that question is, can you? Because you could never ask a White author, ‘When are you going to write about Black people?’ … Even the inquiry comes from a position of being in the center.” Morrison continued, “There are no pluses for me. Being an African-American writer is sort of like being a Russian writer, who writes about Russia, in Russian, for Russians. And the fact that it gets translated and read by other people is a benefit. It’s a plus. But he’s not obliged to ever consider writing about French people or Americans or anybody.”5
A critical disadvantage in public policy research with the use of White centering in disparity research is that it distracts our attention from finding potential solutions that can positively impact the Black community. It keeps a focus on having Black people strive for benchmarks made impossible through racism. My examinations of Black people among Black-majority cities is a deliberate attempt to look for variations, evidence that may be signs of positive resistance, adaptation, and struggle that similarly situated people can learn from and use. It’s also about my learning how to tell our story.
Ultimately, the point of view of the researcher determines what group becomes the standard against which all others are measured. All researchers are filled with cultural norms and traditions that are inextricably linked to the racial setting, which ultimately influences our frameworks, methods, and findings. And it’s impossible to remove our childhood experiences from our point of view. Our segregated histories influence the subtle perspectives of our work. Research can never be neutral, above the fray. All research is imbued with the norms and values of the person conducting it. Inclusion is in my family history and subsequently inseparable from my scholarship. That is to say, there is nothing dispassionate about research. This truth is especially true when it comes to privilege and racial bias. I once heard author and scholar Brittany Cooper say, “Ain’t shit about White supremacy rigorous.”6 In other words, Whiteness gets in the way of quality. This is why truly rigorous research actively addresses our biases, particularly around racial prejudice.
Think tanks and universities must see diversifying the stable of researchers as a proactive solution to hedge against bias and to add value to Black communities. While there is no guarantee that Black, Latino, Asian, or Indigenous researchers will challenge the orthodoxy they were trained in, they are more likely to have insights into how the methods and findings may or may not serve the community the person lives in or is from. When the Public Health Service began studying, in 1932, the progression of syphilis—the Tuskegee Experiment—by giving hundreds of Black men the disease without their consent, it’s a severe understatement to say they could have used some Black researchers (from any hood). That study went on for forty years.
Investment in researchers from underrepresented groups is an investment in rigor. It’s also an ethical and moral investment. However, the methods and perspectives researchers are trained to use must also change if we are going to add value to communities that have been robbed of vital resources by racism.
All researchers need to learn how to center a community or group other than White people. The default position of
