Race, Segregation, and Discrimination
Session E in Room 1.302 D
Moderator: Becky Pettit, Barbara Pierce Bush Regents Professor of Liberal Arts, Department of Sociology, UT Austin
Brielle Bryan, Assistant Professor, Department of Sociology, Rice University
Locked out of Place: How Felony Conviction History Shapes Residential Opportunity
This study uses a correspondence test approach, sending email inquiries about rental housing ads posted on Craigslist for the 40 largest U.S. cities. with the goal of determining (1) the amount of discrimination individuals with felony convictions face in the private rental housing market; (2) how the extent of discrimination varies by characteristics like race, gender, age, and parent status; and (3) whether discrimination patterns vary by neighborhood context. This study marks the first attempt to conduct a nationwide analysis of how much discrimination the 19 million Americans with felony records face and, crucially, what types of neighborhoods they are channeled into as a result.
Mary Campbell, Director, Texas Federal Statistical Research Data Center (TXRDC), Professor, Department of Sociology, Texas A&M University
Race Moves: Linking Administrative Data to Explore Social Change
We use powerful, newly-linked federal administrative data spanning 80 years to understand ethnic and racial self-identification, with a special emphasis on understanding the identification patterns of immigrants, children of immigrants, and people with more than one ethnic or racial background. We have linked restricted-access American Community Surveys (2005-2020 ACS), the 1940, 2000 and 2010 Decennial Censuses, and the complete set of Social Security Administration records (the Numident). Using this sample, we test patterns of ethnoracial identification change across the life course.
Denisa Gandara, Assistant Professor, Department of Educational Leadership and Policy, UT Austin
Inside the Black Box: Detecting and Mitigating Algorithmic Bias across Racialized Groups in College Student-Success Prediction
Colleges are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions and student-success interventions. Because predictive algorithms rely on historical data, they capture societal injustices, including racism. A model that includes racial categories may predict that racially minoritized students will have less favorable outcomes. We explore bias in education data by modeling bachelor’s degree attainment using various machine-learning modeling approaches. We also evaluate the utility of leading bias-mitigating techniques in addressing unfairness. Using nationally representative data, we demonstrate how models incorporating commonly used features to predict college-student success produce racially biased results.
Aprile Benner, Professor, Department of Human Development and Family Sciences, UT Austin
PRC Faculty Co-Author: Bridget Goosby, Professor, Department of Sociology, PRC Graduate Training Director, Department of Sociology, UT Austin
Historical Trends and Demographic Variation in Adolescents’ Views on U.S. Race Relations
Perceptions of race relations, encompassing larger internalized models of racial attitudes and prejudice, inform social and political views and interpersonal interactions. How these sentiments shift historically provides a bellwether for the concerns and direction of U.S. society. Modeling survey responses from American adolescent cohorts across 43 years (1976-2018), inflection points were observed in perceptions of worsening Black-White relations and race relations worries centering on 1993/94 and 2018. We link these inflections to the key historical zeitgeists of the moment and note marked divergence in historical trajectories most notably across political affiliation, race/ethnicity, and school-based interracial contact. Adolescent attitudes are consequential, as they are the next generation of constituents shaping the future of race relations in the U.S
LGBTQ+ Populations and Health
Session F in Room 1.302 E
Moderator: Phillip Schnarrs, Associate Professor, Department of Population Health, Director, The Texas PRIDE Health Collaborative, Dell Medical School, UT Austin
Andrew R. Yockey, Assistant Professor, Biostatistics & Epidemiology, School of Public Health, University of North Texas Health Science Center
Barriers to Cancer Screening Among Older LGBT Adults: A Scoping Review
The present proposal will assess the current state of the literature regarding barriers to cancer screening among older LGBT adults using the NIMHD SGM framework. Findings from the present study will inform health care decisions and future interventions aimed at reducing cancer disparities among LGBT+ populations.
Debarun Majumdar, Professor, Sociology, Texas State University
Who Are the Queer Desi (South Asian) Folks? An Analysis of Data from a Purposive US Sample
Very little is known about South Asian LGBTQ+ population in the US. With the increase in the population of South Asians in the US, this marginalized community has also grown in recent decades. In this paper, I will present data (n=120) on the following characteristics of this community: demographics, outness, social connections, well-being among others. As this population can have various intersectional identities based on gender, sexual orientation, race/ethnicity, and immigration status, findings from the general US queer population cannot be always generalized to this population. This research seeks to fill this gap.
Kara Joyner, Professor, Sociology and Demography, UT at San Antonio
State-Level Structural Stigma and Well-Being
We explore the dimensions of structural stigma (or structural heterosexism) across states by applying 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. 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, 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.
Phillip Schnarrs, Associate Professor, Department of Population Health, Director, The Texas PRIDE Health Collaborative, Dell Medical School, UT Austin
Sexual and Gender Minority Adverse Childhood Experiences (SGM-ACEs): Measuring Exposure to Cisheterosexism in Early Life and Its Role in Adult Health
Adverse Childhood Experiences (ACEs) are conceptualized as stressful/traumatic events in early life. ACEs are associated with poor adult health. Sexual and gender minority (SGM) adults report great ACEs exposure, likely related to cisheteronormativity, leading to calls for intersectional ACEs frameworks that account for the unique ACEs to which SGM youth are exposed. Schnarrs and colleagues developed and tested the first ever SGM-ACEs measure and found it have good to excellent psychometric proprieties. In this talk, Schnarrs will: 1. Discuss the development of SGM-ACEs, 2. Describe findings from psychometric assessments across two studies, and 3. Identify next steps in for development.
Hye Won Chai, Postdoctoral Scholar, PRC and CAPS, UT Austin Daily Stress Reactivity and Marital Relationship Among Middle-Aged Same-Sex and Different-Sex Couples A vast literature shows the importance of daily stressors for social support with marriages, but we know little about how spouses’ affective reactivity to daily stressors shapes perceptions of support and how this may differ for men and women in same-sex and different-sex marriages. This study used dyadic diary data from 752 individuals in 376 gay, lesbian, and heterosexual marriages to examine the associations between an individual’s and their spouse’s affective reactivity to daily stressors and perceived marital support and tested whether these associations differed by marital satisfaction and gendered relationship contexts. Results showed that individuals’ heightened affective reactivity was associated with lower levels of perceived support only among gay men who were dissatisfied with their marriage. Spouses’ reactivity was associated with lower support only among lesbian women who were dissatisfied with their marriage. These findings highlighting potential different stress reactivity dynamics for different-sex and same-sex couples.