Over two million Americans watched each NASCAR race in 2025, yet this popular sport remains understudied in sociology. NASCAR’s fans are known for their enthusiasm and loyalty but are also stereotyped as uneducated, white, conservative Southerners. Such stereotypes and symbolic boundaries can produce feelings of belonging for those who conform and exclusion for those who don’t, with implications for social connections and fandom. What are the consequences of stereotypes on NASCAR fandom and belonging? To start to address this question, we created an online survey and distributed it to NASCAR fans on various social media platforms. In total, we collected 591 responses on their identities, attitudes, behaviors, and their sense of belonging with other NASCAR fans during the last two weeks of the 2025 NASCAR season. Our results indicate a connection between how much a person feels they belong with other NASCAR fans and fan intensity: fans who say they fit in with other fans are more likely to identify as die-hard fans. Based on our findings, we conclude that feelings of belonging and stereotypes exert influences on fans, thus making NASCAR fandom and belonging more challenging for people who do not fall within existing stereotypes or group boundaries.
As generative AI is becoming more integrated into our society, students are uneasy about the future, and professors have been at the forefront of making policy decisions about generative AI’s place in academics. The goal of this project is to explore student opinion about AI to ensure that students have a voice in policy discussions. Data are from the 2025 Eau Claire Longitudinal Student Survey, in which a random sample of 215 UWEC undergraduates were asked about generative AI, its place in academics, policies, social acceptance, and benefits. Results show that positive and negative views of AI are made up of clusters of interrelated beliefs, attitudes, and experiences with AI, including social acceptance and how useful and important they view it. Opinion appears to be shaped by major and political ideology, with liberals and arts and humanities majors on one end of the continuum and conservatives and business majors on the other, with moderates and other majors in the middle. We conclude that policies should differ between faculty to reflect the needs of students’ futures in their fields and that professors need to prioritize communication with students about student preferences and ethical AI use.
As artificial intelligence becomes increasingly integrated into professional and academic environments, questions about fairness, accountability, transparency, and regulation have become more urgent. While existing research explores AI literacy, trust, professional implementation, and theoretical ethical concerns, fewer studies directly examine how the general public evaluates specific ethical issues such as disclosure requirements, bias, data privacy, job security, productivity impacts, and responsibility for harm.
In 1857 the U.S. Supreme Court ruled in Dred Scott v Sandford, that Dred and Harriet Scott were not eligible to sue for their freedom because they were not citizens. In our modern retelling of this case the focus is overwhelmingly on the role that the Supreme Court had in spurring on the Civil War and/or the overreach of the federal government in attempting to regulate state property rights. This narrative obfuscates the way that Dred Scott v Sandford reinforced the idea that Black folks were not human and subject to dehumanization in the United States. By conducting an institutional ethnography of the physical locations that discuss the impact of Dred and Harriet Scott in the past and present in the Twin Cities this research argues that these locations are haunted with the memory of slavery and allow people in the present day to contend with the ghosts of the past and their role in the present.
