Structural Racism and Rigorous Models of Social Inequity Proceedings of a Workshop (2022) / Chapter Skim
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2 Assessing the Landscape: The Measurement and Modeling of Structural Racism
2 Assessing the Landscape: The Measurement and Modeling of Structural Racism
Pages 19-46
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From page 19... ...
• Quasi-experimental approaches are useful in the study of structural racism in that they allow for estimates of causal parameters that policy makers can interpret; for example, the current use of lethal force among the police is driven primarily by governmental and institutional decisions rather than by intractable structural factors. (Jamein P
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From page 20... ...
• Novel data not only present new opportunities to measure state violence but also reveal the limits of official statistics. Building infrastructure for unofficial data col lection can enable valuable research on structural racism.
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Finally, a new survey experiment was designed for a nationally representative sample of 2,500 White adults using YouGov, in which each adult was randomly assigned to one of the 44 com binations of gender, class, and race, and determined their conformance to the 250 most popular stereotypes identified in the prior survey. Flores remarked that using the stereotype content model, one would expect to find the most common existing racial stereotypes to include degrees of competence (e.g., confidence, independence, competitiveness, organization, and intelligence)
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From page 22... ...
In closing, Flores discussed the benefits of the racial position model, which offered significant explanatory power to understand the racial stereo FIGURE 2-1 The overlap of racial stereotypes with class and gender stereotypes. SOURCE: Workshop presentation by René D
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Flores em phasized the value of using experimental design to observe the specific configurations of particular social situations, so as to better understand both the stereotypes that might be produced and their social consequences. In response to a question from David Takeuchi (workshop planning committee member and professor and associate dean for faculty excellence in the University of Washington School of Social Work)
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From page 24... ...
He emphasized that quasi-experimental methods are well-suited to study racial disparities in police violence and to isolate the effect because police violence is not random or conducted in a control environment, and these methods can exploit variation in exposure or treatment. Reflecting on whether structural factors influence racial disparities in police violence, Cunningham mentioned that segregation has long been presumed to have driven the increase in use of lethal force in the 1960s.
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From page 25... ...
Cunningham related that, to explore departmental factors that could influence racial disparities in police violence, Cox and colleagues (2021) exploited the variation in employment discrimination litigation against police departments in the 1970s and 1980s and found that racial diversity matters in police departments after a threat of affirmative action litigation, an effect that explains the relative decline in non-White deaths at the hands of police after 1970.
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From page 26... ...
Current use of lethal force is driven primarily by governmental and departmental decisions rather than by "intractable" structural factors; thus, he emphasized that institutions matter and ex pressed optimism that the public's perception has begun to shift -- political reform now seems feasible. He cautioned researchers against focusing too much on new research designs and losing sight of their research questions; context is important when thinking about the best way to answer these questions.
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From page 27... ...
The persistence of culture and inherited trauma also connect directly to historical measures, and biobehavioral responses demonstrate how histori cal patterns affect current outcomes. Bailey described her current collaborative research endeavor, which investigates how local histories of racial violence relate to contemporary pregnancy outcomes (e.g., racial inequities in preterm births, low birth weight, and infant mortality)
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From page 28... ...
She underscored that much of the quantitative historical data needed to conduct such analyses already exist -- for example, Census data (aggre gated data at the state and county levels, and individual data) , elections data for state and national offices (down to the county level)
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From page 29... ...
Historical data could also be used to study how inequality and access to opportunity structures affect social and health disparities. Public policies that shaped access to certain resources, the structure of the local labor market, and local school funding could all be analyzed; furthermore, data on multigenerational program participation (e.g., GI bill benefits were mostly for White men)
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. She reiterated that the way in which Indigenous peoples have been racialized and erased by federal systems affects data availability and data dependency, and this "assimilative effort to erase" occurs through this "mechanism of blood."
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She emphasized that Indigenous peoples consider data as sacred to sovereignty, and without sovereignty, equity and justice cannot be realized. Indigenous data sovereignty is "the right of Indigenous peoples and nations to govern the collection, owner ship, and application of their own data."1 Indigenous peoples have thus begun to reclaim data sovereignty by decolonizing data, moving from data dependency to control of data by Indigenous peoples and for Indigenous people in all aspects, including collection, analysis, reporting, and storage.
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Obermeyer pointed out that decision-making cur rently depends on radiologists' perspectives. Guidelines for receiving a life-transforming knee replacement, for example, are based on both the severity of knee pain and the severity of knee disease; by inserting the algorithm's prediction of severity to make this decision instead of relying on the radiologist's assessment, the fraction of Black people eligible for knee replacement doubled.
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From page 33... ...
Less than 20 of these projects used historical, machine learning, or experimental approaches, suggesting that these methods are significantly underused in the study of systemic racism and health. Further more, Takeuchi reported, only a small number of the funded projects on racism focused on Indigenous peoples, Asian Americans, Native Hawaiians, and Pacific Islanders.
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Small-Rodriguez emphasized the value of creating a tribal data standard in the United States, which would enable increased opportunities with comparative data. Furthermore, she pointed out that the United States has never conducted a national survey of Indigenous peoples, unlike its peer countries.
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Food and Drug A dministration could play a regulatory role in ensuring that algorithms eliminate rather than replicate biases. Obermeyer highlighted his work auditing a lgorithms that are widely used in the health care space and finding a significant amount of racial bias (e.g., algorithms that deprioritize care for sicker Black patients in favor of healthier White patients)
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From page 36... ...
She encouraged researchers to pair methodological tools, such as surveys, observations, biomarkers, ethnologies, social media, interviews, photovoice, archives, and ethnographies, to better understand the complexity of structural racism. The use of mixed methods can be done sequentially (i.e., quantitative before qualitative)
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From page 37... ...
, who created a compara tive study using the concurrent mixed methods approach of collecting sur vey data, observation data, and interview data to corroborate the impact of anti-Black racism on birthing individuals across different datasets. Adkins-Jackson cautioned researchers against becoming nonreflexive scientists, who are unaware of how much harm they create by preselecting methods -- a decision that immediately introduces bias into a study.
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. The women's specific narratives illuminated a form of structural gendered racism, pointing to the White supremacist, patriarchal, heteronormative, able-centric system as a cause of poor health for Black women: a system that impacts the larger Black communities for which "Black women are socialized to care" (see Adkins-Jackson et al., 2022; Laster Pirtle and Wright, 2021)
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. Most importantly, this decolonizing of health research helps to create a place where Indigenous peoples can survive and thrive, "guided by their ancestral knowledges and practices centered upon the lands" (see Johnson-Jennings et al., 2019, 2020)
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From page 40... ...
Third, although conventional regression estimators are a key aspect of survey re search, they can be misaligned with relational theories of race and racism. Boen remarked that the first step in improving the use of survey re search to understand the drivers of racialized health inequities is to have better data to capture the structural and institutional processes that pro duce these inequities, as well as better data infrastructure.
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From page 41... ...
Boen discussed another common approach used to measure structural racism that focuses solely on markers of disparities and discrimination in particular institutional domains, which can conceal other forms and con sequences of racial violence, racist social control, and structural racism. Thus, she encouraged researchers to also consider how overall levels of ex ploitation, violence, exclusion, and social control can reflect the structural racism that affects social inequities.
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NOVEL APPROACHES TO ADMINISTRATIVE AND CROWD-SOURCED DATA Frank Edwards (assistant professor of criminal justice at Rutgers Uni versity) described his interest in using descriptive methods and novel data to quantify the social distribution of state violence in both historical and contemporary ways.
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From page 43... ...
For instance, if the cause of death was not labeled by the medical examiner as "by law enforcement," it is not recorded as such. Edwards noted that this example demonstrates the value of un official data sources; however, he encouraged researchers to use novel data c autiously and critically, as unofficial data are not without challenges and biases.
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From page 44... ...
Edwards mentioned that administrative data, another type of novel data, are generated routinely for the administration of various state pro grams and collected to meet organizational needs and for legal compliance; they are not produced with the research community in mind. Looking at administrative data on prenatal substance exposure screening from 2010 through 2019 from the National Child Abuse and Neglect Data System, Edwards and his colleagues found that in Minnesota, for example, A merican Indian infants were 15 times more likely than White infants to be reported to child protection agencies with infant or prenatal substance exposure.
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From page 45... ...
With all of these complex challenges in mind, he encouraged researchers to reflect on a key question: how can systems of knowledge be created that develop more insight on structural racism? A participant inquired about barriers to forming interdisciplinary teams for structural racism research, as well as strategies to overcome them.
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From page 46... ...
A participant inquired about successful examples of incorporating com munity voices into research. Johnson-Jennings described her experiences working with the Choctaw Nation on land-based healing to address the historical trauma of structural racism and related health disparities.
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