Kevin S
- Research Program Mentor
PhD candidate at University of Denver
Expertise
social psychology, intergroup relations, stereotyping, prejudice, discrimination, social justice, bias
Bio
Hi! I'm Kevin and I'm currently a fifth year graduate student in the Affective Social and Cognitive area at University of Denver. I earned a BA at Miami University in Oxford, Ohio majoring in Psychology and Premedical Studies. I spent one year as a lab manager at the University of Denver before pursuing my PhD there. In my research, I investigate how group-based biases in person perception influence how we treat others in a variety of contexts. For example, I investigate how physicians' biases may influence disparities in treatment recommendations across race, class, and gender. Outside of research, I like to hike, ski and snowskate, go to concerts, and see live music.Project ideas
Factors underlying disparities in healthcare
We could explore the structural (e.g., access to resources), individual (e.g., patient behaviors), and/or perceiver level (e.g., provider bias) factors that may underlie disparities in the medical system across race, gender, or socioeconomic status. For example, you may be interested in why lower-class individuals receive less intensive pain treatment than higher-class individuals. You could then explore several factors that may contribute to this under treatment of lower-class individuals such as lack of access to insurance or quality food as well as stereotypes of lower-class individuals as tougher. You could then write up a media brief (e.g., Op ed) discussing the factors underlying the under treatment of lower-class individuals.
Using Statistical Reasoning to Combat Misinformation in the Media
In this project, we could examine statistical claims made in the media and understand why different media sources use the same statistics to make contradicting claims. In this project, you would learn the basics of statistical reasoning, how to critically evaluate information provided in media sources, and later how to use your new-found statistical reasoning skills to combat misinformation in the media. For example, you could look into media reports on police shooting. Here, you may find that some sources claim that Black individuals are disproportionately targeted by police violence whereas other sources claim that White individuals are more likely to be targeted by police violence. You would then learn how to responsibly interpret the statistics these media sources are drawing from and highlight the errors in reasoning that these sources may or may not have made. You could then present this information in a blog or even create a small podcast discussing how these claims can simultaneously exist and how others can critically evaluate statistical claims.