Interrogating Erasure in Systems Change by Centering the Stories of Black Women as Collective Power in Weaving Equitable Experiences

This article is part of Illuminate’s Equitable Horizon Blog Series. Find more from this series HERE.

Introduction

The paper is written from the perspectives and experiences of three Black women in the United States (US) who explore how operating from the margins in a country that constantly erases our stories fuels our work. Systems change and equity are embodied and connected through the various work examples highlighted to advance the current practice in the fields of equity, systems change, and collective leadership. We each express how erasure in our lives is connected to equity, systems change, and leadership from the perspectives of our work. We invite our readers to explore how the systems Black women like ourselves are poised to change are in fact, the ones that tend to cause harm by continuously stripping the very pieces of us that the systems need. Elizabeth kicks us off with the perspective of how measures used in our everyday lives in the American system erase a vital part of us; Kimberly invites us to explore the possibilities of how Culturally Responsive and Equitable Evaluation (CREE) methodological approaches (Expanding the Bench, 2019) can be used to “undo” the artifacts of Black women erasure, (Noble, 2022) and, in so doing, cultivate more human-centered ecosystems; and Sharon adds how we see erasure showing up in various social frameworks and propose a CREE-oriented framework. All these perspectives culminate in ways we address erasure, potential solutions on how we do the work while operating from the margins, and suggestions on how folks can join us in systems change work that makes space for collective power as the fuel in creating equitable experiences.

Measures can be a double-edged sword when you have Black or brown skin in the United States

Understandably, measurements and measuring systems create organization. However, using one single measurement as the sole predictor of poor health outcomes or privileges does more harm than good. In healthcare and public health especially, so much focus is placed on race as a biological characteristic instead of treating it as a social construct. Race, specifically the race checkbox, has a way of erasing so much of who we truly are as individuals. I am so much more than my race (black skin), but in various systems, I am reduced to the color of my skin (race). Humans who created race (and the thinking surrounding race) are those who produced racism, which is viewed as a threat to public health (O’Reilly, 2020). When we realize a system of measurement is outdated and exclusionary in nature, we should examine ways to improve it or cease using it, especially when the measurement creates erroneous data that inform policy and decision-making. One example of this in the medical and public health fields is the Body Mass Index (BMI), which is a calculation based on an individual’s weight and height (CDC, 2024). According to several sources, including a 2009 interview on National Public Radio (NPR) (Devlin, 2009) and a 2023 article in Yale Medicine (Katella, 2023), BMI is an outdated tool developed by a Belgian mathematician using European white men as his subjects, which ignores other individual characteristics that impact body fat (e.g., biological sex, social race, or ethnicity). Today, many providers are moving away from solely using BMI to determine if a patient is obese, especially after the American Medical Association (AMA) announced a policy acknowledging the limitations of BMI data (AMA, 2023).

Another example of an outdated measure is race data in America, specifically the race checkbox used in public health, healthcare, and many other systems (e.g., education, financial, judicial, social, etc.). The race checkbox, similar to the BMI calculation, is outdated and ignores individual characteristics and social-cultural factors (e.g., exclusionary policies and practices, systemic racism, and related stress) that impact health equity. Currently, in the US, we treat race as a biological feature; however, race (racism) is a social construct (Dordunoo, 2022). It is time we treat race as the social construct it is and measure it as such, especially as we collect, report, and interpret race data in public health and healthcare research (Hsu et al. 2019).

While many people tend to focus on race in terms of the present day and the last sixty years (e.g., 1960s Civil Rights Movement), we need to go back even further in history to the creation of the race checkbox and its rationale. Hsu et al. 2019 mentioned how the 1790 Naturalization Act defined citizenship and protections of citizenship as belonging to “free white persons.” According to an October 2023 New York Times article (Lai and Medina, 2023), the Census began collecting demographic data with only two checkboxes: “free white” and “slaves.” Now, we need to ask the question: Why was data collected in this manner? Similar to today’s purpose for collecting and reporting data, initial Census race data served as a method to organize data, support decision-making, and develop policies. Further, the distinction between skin color (white vs. black) and social status (free vs. enslaved) permitted some individuals to have privileges and protections while denying those privileges and protections to others. Let’s look at how the U.S. Census Bureau collected race data over time. We begin to see the evolution of the race checkbox from white or nonwhite (19th and 20th centuries), the addition of mulatto (mid-late 1800s), to the addition of Indian (late 1800s), Chinese (late 1800s), Japanese (1900), and Filipino, Korean, and Hindu (early 1900s) (Gibson and Kay, 2002). By the 1970s, we began to see the transformation to the race checkboxes we are more familiar with today.

Now, the Office of Management and Budget (OMB) seeks to enhance data collection efforts by adding more options to choose due to diversity in race and ethnicity (OMB, 2023). For example, they may include Jamaican, Haitian, Nigerian, and Ethiopian under the Black or African American checkbox. While the OMB seeks to improve race data collection, we are still missing a critical part related to race data collection and reporting in America. We are missing the fact that the race checkbox, with all of its additions and edits, is still a social construct developed by humans. The race checkbox, which supports race and systemic racism, is still an issue because the data is used to tell (and maintain) a storyline that Black/African Americans and other people of color are inferior or less than. For instance, think of the many research articles or media headlines that tell us Black/African Americans or brown individuals are more likely to have poor health outcomes.

Because racial disparities are not a consequence of black skin, but a consequence of treatment because of black skin, we need a credible social/racial privilege index to collect and report public health and disparities data (Brown, 2023). Such an index would capture lived social experiences in addition to treatment based on race to identify relationships between social/racial privilege and poor health outcomes (versus solely focusing on race collected as skin color). To change the narrative about Black/African Americans and brown individuals being inferior, we need to change how we collect data related to race and ethnicity for research and policy.

Creating human-centered systems with culturally responsive and equitable approaches

Historically, we have distinguished data from information and by so doing, crafted a “reality” wherein data, as the building blocks of information, are irrefutable and unchallenged. We often define data as an individual unit of fact; free of meaning and therefore carrying with it no inherent bias. However, just as researchers operationalize constructs based on the paradigms created by their research questions, data has been operationalized by the interaction of white, male, western, research culture (Harris, 2022), and the power wielded by policy actors. The fallacy in this approach is that while data is factual, it is never truly void of context, because data is shaped and fashioned by the contextual realities that bring it forth. For example, the contextual realities of slavery, Jim Crow, and the countless acts of terrorism (e.g. Memphis Murders (Malveaux, 2024), Wilmington Massacres (Biddle, 2023), Tulsa Terrorist Attacks (Madinga, 2021)) were organized to undermine the progress made by Black Americans immediately after slavery. These heinous acts of terror brought forth numerous data points showing the wealth that Black Americans lost (both human and fiscal). However, the contextual backdrop against which these data points occur is one of the government-sanctioned terror campaigns that served to destabilize Black homes, Black communities, and Black wealth in structural and systematic ways. Similarly, the racist policy of redlining (Gross, 2017) depressed home values in Black neighborhoods across the country, adversely impacting African Americans’ ability to build and grow wealth (Hamilton et al., 2015) through homeownership.

As if these atrocities were not enough on their own, they are compounded when the data borne from them (per capita household income, per capita household wealth, debt to asset ratios, etc.) are conflated with information (whether intentionally or not) and used to justify denying loans to Black people to start or grow a business, advance their education, or even purchase a home. Additionally, the medical industry is filled with policies, practices, and standards that were developed primarily, and in many cases exclusively from the data collected from white men. From the intentional exclusion of Black women in clinical trials (Cavallo, 2022) to the drugs brought to market through data collected on monochromatic and male-dominated (Kritz, 2005) clinical trial participants, to a BMI that was developed almost completely from the metrics and physiological data of white, European men (Stern, 2021); data collection and data exclusion have shored up oppressive systems within which Black women have been erased.

Data is not pristine nor free of the contextual soil from which it grows. Treating it as such dismisses and erases the voices of those most harmed by structural and systematic oppression. Far too often, those voices have been that of Black women (Emba, 2019). CREE is a philosophical and methodological approach that can play a tremendous role in undoing the practices and norms that uphold this erasure because it prioritizes the integration of both culture and equity into the practice by incorporating intentionality, transparency, and egalitarianism. By acknowledging community members’ wisdom as invaluable and integral to systematic inquiry, we also acknowledge the necessity of equitable partnership in response to structural inequities that have served to render them invisible. In my work as a researcher and evaluator, I endeavor to authentically partner with community, particularly members of community who have been systematically marginalized. Furthermore, I seek to comprehensively incorporate their wisdom throughout my research and evaluation work.

Any contemplation and subsequent conversation about Black female erasure must be grounded in the understanding that it is an artifact of economic exploitation legitimized via racialized and gendered oppression. Systemic and systematic oppression manifests as many adverse outcomes for Black people/communities, Indigenous people/communities, and Brown people /communities. Segregation, discrimination, and inequity have resulted in detriments to the quality of life for women, particularly Black women (Coles and Pasek, 2020), who reside at the intersection of two systematically marginalized groups. Codified and de facto policies and practices have systematically marginalized Black women (Paradies, 2015) and simultaneously cordoned opportunities to improve their life outcomes (Carney et al., 2023). Even among highly educated and more affluent (Lander and Santoro, 2017) Black women, research indicates they too are subjected to racialized (Williams and Lewis, 2019) micro and macro aggressions that adversely impact their wellness, and diminish the protective effects associated with socioeconomic and family status. Justice demands that those most proximal to impact be present in developing policy and informing practice. Consequently, a CREE methodological approach that comprehensively incorporates the voices and subject matter expertise of these most proximal community members into research, policy, and practice ensures validity and better alignment between process and outcomes (Harris & Chamberlain, 2023; Harris et al, 2023).

Empirically speaking, there are practical examples of initiatives that have endeavored to incorporate CREE practice into data collection, analysis, and subsequent recommendations. In my role as a research and evaluation consultant, I worked with a team of researchers and policymakers to incorporate culturally responsive and equitable data collection, analysis, and interpretation methods into a Marginal Tax Rate Calculator (Harris & Chamberlain, 2023). The purpose was to help benefits recipients and caseworkers understand how changes in household income impact the benefits that individuals receive. The implications of this work are far-reaching as understanding this relationship empowers benefits recipients to make informed decisions about employment, education, family formation, and navigating a path to economic stability.

As a Black woman, I came into this work well aware of the historical stigmatization that Black women have faced around social safety net benefits. Even now, I can distinctly recall my family’s conversations leading up to the 1980 presidential elections. The polarizing and triggering dog whistles Ronald Reagan deployed while on the stump (Borrelli, 2019), as he crafted his straw-man welfare queen (Covert, 2019), no doubt found home among those for whom such racist tropes aligned with their own bigotry and bias. Possibly even more diabolical was the fact that this race-baiting propaganda also served as the clay-footed foundation on which both policymakers and policy entrepreneurs, who knew full well that white households benefited more from government assistance (Keep, 2023) than Black households, could build their strategies to prioritize deep cuts in spending on social welfare, particularly education, workforce training, and other social service areas. Scapegoating Black women as the justification for spending cuts that overwhelmingly benefited white households, was a winning strategy in the short run. But the cost of the strategy would be paid by countless humans across the country for generations to come. This is the cost of erasure. By silencing the voices and ignoring the lived experiences of any of us, you ignore the commonalities and throughlines that impact all of us.

Therefore, for me, working on the Marginal Tax Rate Calculator (Harris & Chamberlain, 2023) was particularly powerful because it gave voice to the most proximal stakeholders. The process we co-created was both iterative and collaborative; incorporating the feedback of both case managers and benefits recipients into each iteration of the calculator, and in so doing, centering their wisdom to refine a tool they would be more inclined to use without feeling unsafe. For me, the takeaway from the Marginal Tax Rate Calculator Project was that integrating and prioritizing the most systematically marginalized as collaborative partners in research, evaluation, and policymaking, does not marginalize those who have enjoyed (and continue to enjoy) such respect and consideration. It does exactly the opposite. Centering the voices of the most proximal to impact reveals pain points too often overlooked. Addressing these pain points is a moral imperative that makes systems more human-centered and conducive to thriving. More often than not, populations who are most proximal to adverse policy impact are those most distal to the conversations shaping the places and spaces these policies target. Those most proximal have historically been non-white, non-male humans. Black women and other systematically marginalized populations have carried far more than their share of displacement, disenfranchisement, and destabilization. Yet these very individuals hold the wisdom that will unlock the answers to the problems that plague our society (Harris & Chamberlain, 2023; Harris et al, 2023).

Frameworks as a tool to combat erasure by interrogating social systems

Frameworks are used as mental models to either perpetuate narratives of systemic harms or to inform equitable systems change. An experience that exemplifies how I have seen these harmful narratives is sitting in a biostatics class as a requirement in my public health program, having transitioned from the engineering field, and hearing about the poor health outcomes of Black communities. I felt myself physically tensed up, and screaming inwardly “umm not me and my family”, because that statistic generalized the health outcomes for people who look like me without a consideration of contextual factors.

To explore this idea of frameworks serving as mental models for narratives in detail, we need to consider the seed that was planted centuries upon centuries ago, when the notion of whiteness (Smithsonian, 2024) took root and propelled lies to our Black ancestors around superiority in skin color to feed false narratives. Those lies propagated colonialism, which resulted in Black humans stolen from the ancestral roots of Africa to be enslaved across several parts of the world. These lies are still taking hold in various forms by reflecting through structural racism, because those systems that enslaved Black people navigated and fought for freedom from, have still not been built to fully center the stories of Black people. So with this vicious cycle of erasure taking different shapes and forms with the present narrative around “DEI must DIE” (Hart, 2023), is the consistent churning of this erasure seed planted centuries ago. So the question remains, do we just go through this churning cycle?

Black people have thrived through these churns and Black people believe we will continue to thrive, but we as a collective society of all races, must begin to strategize around what will ensure our existence and that of all humanity. Because the world as we know is not sustainable with a zero-sum approach (McGhee, 2022) to living. As a life-long student of statistics, I believe we need to look at the issue from the lens of a stepwise regression that yields an ultimate model of an equitable future that is driven by a society that harnesses collective indigenous ways of living. We can see the generational shifts that have passed and the current shifts as the variables being added to the regression model with observable outcomes reflected in the seasonal shifts of each generation.

Mental models in the form of frameworks can serve as tools that can be adapted across contexts and systems by systems change and equity practitioners who choose not to do the work in silos and tap into the collective power of the community. A community that sees us, supports us, and builds a fortress around us, especially when the world places a romanticized emphasis on the “first” Black of anything, only to not provide the critical support that is needed (Haidar and Kettles, 2024). I co-developed a framework (Attipoe-Dorcoo and Martínez-Rubin, 2024) that can be adapted for such work. The framework embodies the principles of CREE (Expanding the BenchTeam and Advisory Team, 2019) which are rooted in systems thinking, equity, indigenous ways of knowing, and collective power. The I.M.P.A.C.T. (Inclusive, Manumit, Practice-based, Accessible, Community-focused, and Timely) framework serves as a guide to: 1) foster a community-first approach to goal setting in systems change; 2) complement data-driven, measurement-oriented methodologies used in assessments; and 3) heighten the value of practice-based, culturally relevant, and experiential learning to a comparable level of worth and merit in social research.

Each I.M.P.A.C.T. component has corresponding reflection questions briefly described below:

Inclusive: For whom am I working?How do community members engage in defining the “problem” from a strength-based perspective to attain equitable and culturally derived solutions?

Manumit: What is important for the community to see, receive, accept, or believe about the work?What typically motivates community members to seek support and/or involvement with persons outside their community?

Practice-based: Are the voices of community members informing the benefit(s) of the work?Is the practitioner working with the community open to professional and personal growth, and reflective about their practice?

Accessible: How do we keep from misusing resources that only address symptoms, rather than root causes of a problem?How do we avoid perpetuating harm and ensure processes include the “people”?

Community-focused: How does continuously learning about the communities we work with play a role in our work?How does our sense of being result in how we relate to and see the community and, consequently, the world and the vulnerabilities or restraints that may influence the work?

Timely: Does the work approach highlight particular cultural subgroups i.e., those systemically marginalized or not ordinarily involved in decision-making?

What is the impact of findings on policies influencing people’s lives?Mental models such as the I.M.P.A.C.T. framework serve as a contextual and adaptable tool that can illuminate how erasure shows up, as well as serve as an avenue to center community to ensure equity is embedded a priori in systems change.

Conclusion

By exploring these concepts from each of the unique perspectives, we shine a light on the various ways that the same systems we as Black women are poised to change are, the very ones that cause us harm by continuously stripping us of the pieces the systems need. In short, we are using our collective voices and experiences through this paper to share our work and propose solutions for systems change and equity within systems of erasure. We hope readers recognize how people’s voices and lived experiences can be centered as fuel in the work for impact through our examples of (1) measuring social privilege and health disparities, (2) acknowledging that data can never be completely untethered from its context, therefore we must integrate culturally responsive and equitable approaches in our analyses, and (3) adopting mental models of frameworks that account for culture and equity in our work approaches.

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