Charles Crabtree

Professor Crabtree’s research focuses on intergroup relations and discrimination, using experimental methods to understand why people treat poorly those who differ from them and to identify interventions that might reduce discrimination.

He has extensive experience conducting field and survey experiments across multiple contexts, including the United States, Eastern Europe, and Japan. His work has been published in over 40 journals and volumes, including the American Journal of Political Science, American Political Science Review, British Journal of Political Science, Journal of Politics, Nature, Nature Human Behaviour, Political Analysis, and the Proceedings of the National Academy of Sciences. His research has been featured in media outlets such as NPR, CBS News, The Atlantic, and The Economist.

As an innovator in experimental methods, Crabtree has been at the forefront in using AI tools to enhance experimental research workflows. He has taught courses on AI and research design and experimentation at Essex and National University of Singapore, among other institutions. He’s developed approaches for using large language models to design experimental materials, validate treatments, conduct automated text analysis, and improve research efficiency while maintaining scientific rigor. He regularly integrates these tools into his research and teaches others how to leverage AI for better experimental design.

Crabtree received his Ph.D. in Political Science from the University of Michigan. He has taught courses on experimental methods, research design, and statistical analysis at both the graduate and undergraduate levels. He currently serves as co-director of Dartmouth’s Government Department Honors Program. He is passionate about making cutting-edge methodological tools accessible to researchers across disciplines.