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Primary Submission Category: Structural factors
Structural Racism, Ballot Measures, and Health
Authors: Anna Hing,
Presenting Author: Anna Hing*
Voter suppression is a clear example of how structural racism functions to unequally distribute both power and resources. If people cannot vote, they cannot shape the policies directly impacting the conditions in which they live – their SDOH.
One understudied factor linking voting to health are the policies that are enacted by voters or elected officials. State-level ballot measures voted on directly by the people without intermediary representatives, can be used to determine if structural racism, via voter suppression, is linked to more equitable (antiracist) or harmful (racist) measures being passed that shape the racialized patterning of SDOH.
Aim. To understand how structural racism contributes to the racialized patterning of social determinants of health by examining if voter suppression contributes to more racist ballot measures being passed.
Hypothesis: States with a higher cost of voting (voter suppression) will be associated with a higher number of racist ballot measures.
Data. All ballot measures will be identified via Ballotpedia. Ballot measures will be coded as “racist” if the anticipated impact is harmful to racial equity or “antiracist” if the if impact is likely to ameliorate racial inequities. The Cost of Voting Index (COVI) 2024 provides state-level data on barriers to voting (i.e. voter suppression). The COVI examines election laws and calculates a single score and subsequent rank for difficulty of voting in each state. The American Community Survey, freely available by the US Census Bureau, will provide state-level covariates.
Methods. For Aim 1, I will employ Public Health Critical Race Praxis (PHCRP) to code ballot measures. The COVI score 2024 will serve as the main predictor variable in a Poisson or Negative Binomial regression model in StataMP. The outcome variables will be a count of racist ballot measures and antiracist ballot measures, proposed and passed. State-level covariates will be included.
Analyses have not yet been completed.