Primary Submission Category: LGBTQ+
State-Level Structural Stigma and Well-Being: A Focus on Policies Targeted at Sexual and Gender Diverse Individuals
Authors: Kara Joyner Wendy Manning
Presenting Author: Kara Joyner*
Research on the effects of structural discrimination (e.g., heterosexism, sexism, racism, and xenophobia) has proliferated in recent years, but details about the development of indices and typologies used to operationalize this concept are often missing. A core property of the minority stress framework is structural stigma. We explore the dimensions of structural stigma experienced by sexual and gender diverse individuals (also known as structural heterosexism) across states. We apply unsupervised machine learning techniques to measures that capture the level of protection that laws and policies in different states offer sexual and gender diverse populations. Specifically, we use nine measures that represent a broad array of laws and policies that were in place at the beginning of this decade. Principal Component Analysis (PCA) shows that these measures contribute equally to a dimension that explains over two-thirds of the variation in state-level policies. K-Means and hierarchical clustering alike reveal that states cluster into one of three groups that depend largely on their values for the index based on PCA scores. We compare the indices and typologies of structural stigma from our techniques to those produced by the Human Rights Campaign (HRC) and Movement Advancement Project (MAP) and find striking consistency. To validate our measures, in addition to measures constructed by the HRC and MAP, we estimate regression models of self-reported health and depressive symptoms for respondents who self-identify as gay, lesbian, or bisexual in the 2021 Behavioral Risk Factor Surveillance System. These results provide a foundation for future analyses that incorporate other routinely-used measures of structural stigma (e.g., same-sex couple concentration) and contribute more broadly to research that is capturing how structural or contextual indicators operate to further or narrow health disparities.