Project #2: Aging and the Production of High-Impact and Transformative Research Researchers, research institutions, and policy makers are all promoting high impact and transformative research. Of particular concern is the aging of the US scientific workforce, as researchers are typically viewed as most likely to produce their most important and transformative work when young. This project will document trends in the age distribution of the scientific workforce in order to address questions such as: Are the young primary contributors to high impact and transformative science? Do older practitioners stifle transformative research or do they facilitate radical change either directly or indirectly through their interaction with younger workers (e.g., collaboration)? Building on our existing research identifying radical scientific change, we will mine data on (i) citations to scholarly articles, (ii) scientific vocabulary, and (iii) the field / network / market structure of science to (1) develop metrics and visualization tools to identify high-impact and transformative research, the periods in which it is produced, and how the production of high-impact and transformative work relates to the underlying features of fields, including researcher age and collaboration networks; (2) document the nature of high-impact and transformative work relative to other work and the inter-relationships between these types of work; and (3) estimate how the age-structure of innovative fields affects the quantity and quality of output in those fields. To estimate how the age-structure of fields affects output, we will generate instruments for the age-structure of fields using lagged values as well as major events (e.g. the elimination of mandatory retirement and abrupt changes in support, such as stimulus spending). The analysis will contribute to our understanding of how age is related to the production of high-impact research and quantify the research consequences of our aging scientific workforce. The metrics we develop will also be of interest in their own right and our visualization tools help the broader science policy community identify where high impact and transformative work is being done and how their production relates to the characteristics of fields, including their age, network, and market structure.
t Research institutions are increasingly focusing on generating high-impact and transformative research. This project will develop tools that can be used by policy analysts and researchers to identify and visualize where high impact and transformative research is produced and assess the effect of our aging scientific workforce on the production of such research.
| Marschke, Gerald; Nunez, Allison; Weinberg, Bruce A et al. (2018) Last Place? The Intersection of Ethnicity, Gender, and Race in Biomedical. AEA Pap Proc 108:222-227 |
| Shiffrin, Richard M; Börner, Katy; Stigler, Stephen M (2018) Scientific progress despite irreproducibility: A seeming paradox. Proc Natl Acad Sci U S A 115:2632-2639 |
| Fortunato, Santo; Bergstrom, Carl T; Börner, Katy et al. (2018) Science of science. Science 359: |
| Börner, Katy; Simpson, Adam H; Bueckle, Andreas et al. (2018) Science map metaphors: a comparison of network versus hexmap-based visualizations. Scientometrics 114:409-426 |
| Staudt, Joseph; Yu, Huifeng; Light, Robert P et al. (2018) High-impact and transformative science (HITS) metrics: Definition, exemplification, and comparison. PLoS One 13:e0200597 |
| Azoulay, Pierre; Graff-Zivin, Joshua; Uzzi, Brian et al. (2018) Toward a more scientific science. Science 361:1194-1197 |
| Carpenter, Janet S; Laine, Tei; Harrison, Blake et al. (2017) Topical, geospatial, and temporal diffusion of the 2015 North American Menopause Society position statement on nonhormonal management of vasomotor symptoms. Menopause 24:1154-1159 |
| Smalheiser, Neil R (2017) Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery. J Data Inf Sci 2:43-64 |
| Kehoe, Adam K; Torvik, Vetle I; Ross, Matthew B et al. (2017) Predicting MeSH Beyond MEDLINE. Proc 1st Workshop Sch Web Min (2017) 2017:49-56 |
| Peng, Yufang; Bonifield, Gary; Smalheiser, Neil R (2017) Gaps within the Biomedical Literature: Initial Characterization and Assessment of Strategies for Discovery. Front Res Metr Anal 2: |
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