Harvard Undergrad Awarded ASA/AAAS Mass Media Fellowship
Lucy Tu will spend 10 weeks as a science journalist with Scientific American this summer as the ASA’s 2023 AAAS Mass Media Fellow.
Tu is a junior studying sociology, neuroscience, and the history of science at Harvard University and the first undergraduate to be sponsored by the ASA. She has worked as a freelance health and science writer, with work appearing in The Guardian, New England Journal of Medicine, Smithsonian Magazine, and Discover Magazine.
When a Boston school district eliminated science classes from their K–5 core curriculum, Tu proposed and led a program to showcase physics, biology, and chemistry demonstrations for five schools. In 2019, using her multilingual skills, she also spent two months teaching introductory biology classes to middle-school students in central China’s Hubei Province—the epicenter of the original COVID-19 outbreak. In addition to being fluent in Mandarin, she speaks French, Spanish, and Haitian Creole.
Tu returned home to the US as the pandemic was spreading in China and affecting her host family. She said she “stumbled through jargon-laden articles about the then-novel Coronavirus” and observed that absent were “the firsthand stories that were especially precious and pertinent in the face of mass censorship.” She wrote:
Tu has been a member of the ASA since 2021. Since August 2022, she has also been a teaching fellow in the Harvard statistics department, which entails serving as a teaching assistant for an introductory statistics course with 250 undergraduate students. Upon graduating from Harvard, Tu plans to pursue joint JD and MPH degrees. You can learn more about her by visiting her portfolio.
Supporting programs like the AAAS Mass Media Fellowship helps the ASA realize its vision of a world that relies on data and statistical thinking to drive discovery and inform decisions. Beginning in 2017, the ASA’s sponsorship has allowed the program to expand its efforts to promote statistical capacity in reporting and provide statisticians with more media experience.
Previous fellows include Nick Thieme, Irineo Cabreros, Diana Cai, Jessica Craig, Aparna Nathan, and Jayati Sharma.
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