Narrow Results

It is well established in previous research that female and minority entrepreneurs are less successful with business ventures in comparison to whites and males. In that same literature, motivation and growth expectations have been shown to be positively associated with business success. This paper examines how motivations and business goals differ by gender and race and how they affect disparity in business outcomes. Using data from the Second Panel Study of Entrepreneurial Dynamics (PSED II), we find that stronger motivations for financial gain have a negative effect on business survival rate for black women and Hispanic men. In contrast, the effect is positive for black men and Hispanic women. When considering interactions between financial motivations, race and gender, various significant effects were found and are detailed in the paper. It is important for researchers and practitioners who want to promote entrepreneurship to understand the differences and adapt advisory and training curricula accordingly.

The incompleteness of race and ethnicity information in real-world data (RWD) hampers its utility in promoting healthcare equity. This study introduces two methods—one heuristic and the other machine learning-based—to impute race and ethnicity from genetic ancestry using tumor profiling data. Analyzing de-identified data from over 100,000 cancer patients sequenced with the Tempus xT panel, we demonstrate that both methods outperform existing geolocation and surname-based methods, with the machine learning approach achieving high recall (range: 0.859-0.993) and precision (range: 0.932-0.981) across four mutually exclusive race and ethnicity categories. This work presents a novel pathway to enhance RWD utility in studying racial disparities in healthcare.