Structural Racism and Rigorous Models of Social Inequity Proceedings of a Workshop (2022) / Chapter Skim
Currently Skimming:
Pages 43-51
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
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.
|
From page 44... ...
Administrative data on state violence in particular have several challenges: agency administrative data can be of high quality but are often limited in scope geographically, and agency involvement in approval processes limits the scope of critical research when researchers are not granted access to datasets. He asserted that new processes for managing data access and linking administrative datasets that would be independent of state agencies and administered more impartially could enable critical research on structural racism.
|
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.
|
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.
|
From page 47... ...
• A sustainable infrastructure for research on structural racism, health, and aging includes funding for longitudinal design and core support for multiple types of data, multidisciplinary research teams with proven competence and expertise in health equity research, and incentives to focus research frameworks on structural and policy change. (Jennifer Manly)
|
From page 48... ...
The researchers document the power maintained by those who determine what can be measured, how to invest in data infra structure, and who can access the data; they note that seemingly objective choices about methodology have important implications both for the re search and for future policy. Reflecting on how existing data could be leveraged to strengthen struc tural racism research, Givens explained that theory-based methodologi cal approaches offer historical and geographical context and engage both qualitative and quantitative methods that portray the systemic features of structural racism (Hardeman et al., 2022)
|
From page 49... ...
Givens asserted that addressing this structural racism requires both data and political will. She accentuated that data have been and will continue to be "politi cized and weaponized"; for instance, the U.S.
|
From page 50... ...
Givens outlined next steps for the population health community to better harness data for structural racism research: (1) use collective power and political will to mobilize the full range of data and research tools; (2)
|
From page 51... ...
For example, the NLSY effectively links contextual data spatially but lacks the ability to link data in other dimensions -- without school, firm, health care provider, and law enforcement agency IDs, important institutions where structural racism could vary are not considered. Inter generational data are also limited in the NLSY.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.