Mary Feeney
$565,087
University of Pittsburgh
Pennsylvania
Social Behavioral and Economic Sciences (SBE)
Science of Science
Science in the past century has been characterized by a dramatic increase in the scale and complexity of research, growing specialization, and a transition from individual innovation to collaborative discovery. This shift has been driven by a high expectation for “team science,” that scientists in teams will achieve breakthroughs otherwise difficult to attain through individual or additive efforts. Yet, two problems at the foundation of team science call for a thorough investigation lest this high expectation devolves into underdelivered promise. First, the advance of basic, core scientific knowledge on fundamental questions can be stifled or slowed despite the increased use of this knowledge in responding to urgent questions raised by societal needs. For example, the fast and successful development of the COVID-19 vaccine is conditional on decades of basic research on mRNA mechanisms, but it is unclear how a flood of pandemic funding has helped mRNA studies or other research of fundamental importance in biology. The slow development of the knowledge core may restrain the expansion of the research frontier that builds upon it and affect downstream educational initiatives in the long run. Second, the roles and careers of young scientists in the era of team science have become an overlooked topic against the rise of large teams and a temporary scientific workforce. Indeed, while previous studies emphasized the benefits of teams, recent studies have revealed the cost of teams in constraining creative thinking, curtailing due credit, and undermining career progression. Taken together, the increasing dominance of teams in knowledge production presents an urgent need to understand how individual scientists can learn, progress, and effectively innovate in teams. This project has three primary objectives. First, I propose understanding the evolution of core scientific knowledge over the past century by analyzing the displacement between highly cited papers on the same topic, using newly available datasets of 46 million papers and 7 million syllabi. Second, I will investigate the psychological, communication, and financial conditions of team innovation at the knowledge core, by analyzing the impact of age composition, collaboration distance, and funding support on the innovative performance of 2 million name-disambiguated scientists collaborating across 3,500 cities around the globe. Finally, I will investigate the career outcomes of team members who contributed to core knowledge innovation, focusing on early-career women and researchers from minoritized groups. Using machine learning models, I will identify the distinct roles of authors across 16 million papers and associate these roles with job outcomes revealed by millions of CVs. This research program will contribute to several fields, including the science of science, science communication, and public policy. The produced literature, metrics, databases, and code will benefit practicing scientists, research and funding managers, and policymakers on how to design, support, and evaluate research teams for innovation at the foundations of sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.