Homepage for 17-803 "Empirical Methods" at Carnegie Mellon University
In this lecture we reflect on how the (empirical) methods, regardless of how rigorously the studies are done, are ultimately applied and interpreted by human researchers. And how interpretation of even hard numbers is inherently subjective, subject to the beliefs, values, politics, social norms, culture, etc of the researchers.
Breznau, N., Rinke, E. M., Wuttke, A., Adem, M., Adriaans, J., Alvarez-Benjumea, A., … & van der Linden, M. (2021). Observing Many Researchers using the Same Data and Hypothesis Reveals a Hidden Universe of Data Analysis.
Shepperd, M., Bowes, D., & Hall, T. (2014). Researcher bias: The use of machine learning in software defect prediction. IEEE Transactions on Software Engineering, 40(6), 603-616.
AlShebli, B., Makovi, K., & Rahwan, T. (2020). RETRACTED ARTICLE: The association between early career informal mentorship in academic collaborations and junior author performance.). Nature Communications, 11(1), 1-8.