Project #4 - Life Cycle Events, Productivity, and Scientific Impact The notion that intellectual productivity is typically high at younger ages but tapers off at later (but not necessarily late) ones is pervasive. One way in which scientific productivity may be impacted by aging is through changing constraints on scientific mobility that might allow researchers to better locate in environments that are more complementary to their changing skill set. Moreover, the production of science is distinct from its enduring impact, which may also be influenced by life cycle events. In this project, we employ modern developments in the economic study of innovation alongside novel econometric methods in order to examine the impact of life cycle events for an elite set of life scientists. Preliminary analysis reveals a large dip in moves when children enter high school followed by a significant climb after the youngest has graduated. Using data on this relationship, we will examine the impacts of moving on the publishing, funding, and patenting activity of elite scientists. Publication keywords and the breadth of journal citations will be used to examine whether moves (and the resulting change in colleagues) lead to changes in the direction of the elite scientist's research. Our analysis of enduring scientific impact will focus on the relationship between scientist death and the evolution of knowledge within scientific fields, with a particular focus on individual and scientific factors that shape this relationship. Can the untimely death of a scientist alter the trajectory of nascent fields or hasten the decline of mature ones? Can trainees, coauthors, and non-coauthor idea peers keep the flame alive and build upon a scientist's legacy, or is such a legacy mostly determined by characteristics of the scientist (e.g. his/her age, gender, etc.)? In the immortal words of Max Planck, does """"""""science advance one funeral at a time"""""""" by creating space for new researchers to take the helm and drive the research agenda in yet unexplored directions? The overarching goal of this project is to deepen our understanding of knowledge production and the evolution of scientific fields within the life sciences as well as the potential policy levers that might influence this process.
This research examines the importance of spillovers generated by elite scientists for scientific progress in the biomedical area and the influence that family structure and age play in this process. Deepening our understanding of knowledge production in this sector will allow us to improve our allocation of public and private resources and thus expand the frontier of the biomedical field.
|Prosperi, Mattia; Buchan, Iain; Fanti, Iuri et al. (2016) Kin of coauthorship in five decades of health science literature. Proc Natl Acad Sci U S A 113:8957-62|
|Mishra, Shubhanshu; Torvik, Vetle I (2016) Quantifying Conceptual Novelty in the Biomedical Literature. Dlib Mag 22:|
|Buffington, Catherine; Harris, Benjamin Cerf; Jones, Christina et al. (2016) STEM Training and Early Career Outcomes of Female and Male Graduate Students: Evidence from UMETRICS Data linked to the 2010 Census. Am Econ Rev 106:333-338|
|Knepper, Richard; BÃ¶rner, Katy (2016) Comparing the Consumption of CPU Hours with Scientific Output for the Extreme Science and Engineering Discovery Environment (XSEDE). PLoS One 11:e0157628|
|Smalheiser, Neil R; Shao, Weixiang; Yu, Philip S (2015) Nuggets: findings shared in multiple clinical case reports. J Med Libr Assoc 103:171-6|
|Torvik, Vetle I (2015) MapAffil: A Bibliographic Tool for Mapping Author Affiliation Strings to Cities and Their Geocodes Worldwide. Dlib Mag 21:|
|Smalheiser, Neil R; Gomes, Octavio L A (2015) Mammalian Argonaute-DNA binding? Biol Direct 10:27|
|Zolas, Nikolas; Goldschlag, Nathan; Jarmin, Ron et al. (2015) Wrapping it up in a person: Examining employment and earnings outcomes for Ph.D. recipients. Science 350:1367-71|
|Shao, Weixiang; Adams, Clive E; Cohen, Aaron M et al. (2015) Aggregator: a machine learning approach to identifying MEDLINE articles that derive from the same underlying clinical trial. Methods 74:65-70|
|Cohen, Aaron M; Smalheiser, Neil R; McDonagh, Marian S et al. (2015) Automated confidence ranked classification of randomized controlled trial articles: an aid to evidence-based medicine. J Am Med Inform Assoc 22:707-17|
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