Measurement accuracy is something all quantitative researchers strive for, as you want to make sure you're measuring what you want to be measuring. When it comes to gathering gender and sex data, though measurements are complicated, beyond simply teasing apart sex and gender, there's also the imperative to ensure the language and measurement tools researchers use are inclusive of all experiences. That's the focus of this episode of stats and stories with guests Dooti Roy and Suzanne Thornton. Dr. Dooti Roy is a people leader, global product owner and a methodology statistician at Boehringer Ingelheim (she didn’t give me where she worked in her bio so she might not want this) who enjoys developing/deploying innovative clinical research and statistical visualization tools with expertise in creating and leading dynamic cross-functional collaborations to efficiently solve complex problems. She is currently focused on research and methodological applications of Bayesian statistics, artificial intelligence and machine learning on clinical efficacy analyses, patient adherence, and dose-finding. She is passionate about promoting diversity and inclusion, mentoring, cross-cultural collaborations, and competent leadership development. She unwinds with painting, reading, traveling and heavy metal. Suzanne Thornton professor of Statistics at Swarthmore College, a liberal arts undergraduate-only institution. As an educator, she strives to teach students to understand statistics as the language of science and prepare them to become stewards of the discipline. In 2020 she chaired an ASA presidential working group on LGBTQ+ representation and inclusion in the discipline and earlier this year, she was appointed to a three year term to serve on the National Advisory Committee for the US Census.