The U.S. scientific workforce is aging - the average age of both US academics and medical school faculty increased to the late 40s, from the early 40s in 1970. This aging is troubling because people are seen to make important scientific contributions early in their careers. Moreover, the U.S. is turning to innovation as an economic driver, and the aging of the population will both increase and shift the demand for biomedical innovation. This Program Project will develop and disseminate an interrelated body of research on the production and impact of research in an aging society along with the data infrastructure necessary to catalyze the development of a dynamic research community studying innovation at the individual-level and aging and innovation. Our research will be organized around 2 broad, interrelated issues: (1) We will project how the aging scientific workforce will affect the quantit and quality of innovation and policy responses. We will study how innovation varies over the lifecycle, and how a) the age-structure of research teams and communities; b) life-cycle events from training to retirement; and c) researcher characteristics (gender, race, and ethnicity) mediate the age-innovation relationship. (2) We will study the health impacts of and local economic spillovers from research and how the aging biomedical research workforce will affect health and the economy. We will also study how the aging of our population will affect the demand for biomedical research and how researchers will respond. Supported by 3 cores providing (A) Administration, (B) Data Acquisition and Construction, and (C) Program Development, our multi-disciplinary team will produce a comprehensive analysis and catalyze research on innovation in an aging society. Complementing this work, we will produce a wide range of data and tools, including a large-scale, disambiguated, longitudinal dataset on biomedical researchers that will not only support the projects, but provide infrastructure for the research community.

Public Health Relevance

Our scientific workforce is aging, which is expected to reduce innovation at the same time we are emphasizing innovation. We will project how our aging biomedical research workforce will affect innovation, quantify the associated health and economic consequences, and explore a range of policy responses. We will also develop infrastructure for and catalyze the development of a new research community. DESCRIPTION (provided by applicant): The U.S. scientific workforce is aging - the average age of both US academics and medical school faculty increased to the late 40s, from the early 40s in 1970. This aging is troubling because people are seen to make important scientific contributions early in their careers. Moreover, the U.S. is turning to innovation as an economic driver, and the aging of the population will both increase and shift the demand for biomedical innovation. This Program Project will develop and disseminate an interrelated body of research on the production and impact of research in an aging society along with the data infrastructure necessary to catalyze the development of a dynamic research community studying innovation at the individual-level and aging and innovation. Our research will be organized around 2 broad, interrelated issues: (1) We will project how the aging scientific workforce will affect the quantit and quality of innovation and policy responses. We will study how innovation varies over the lifecycle, and how a) the age-structure of research teams and communities; b) life-cycle events from training to retirement; and c) researcher characteristics (gender, race, and ethnicity) mediate the age-innovation relationship. (2) We will study the health impacts of and local economic spillovers from research and how the aging biomedical research workforce will affect health and the economy. We will also study how the aging of our population will affect the demand for biomedical research and how researchers will respond. Supported by 3 cores providing (A) Administration, (B) Data Acquisition and Construction, and (C) Program Development, our multi-disciplinary team will produce a comprehensive analysis and catalyze research on innovation in an aging society. Complementing this work, we will produce a wide range of data and tools, including a large-scale, disambiguated, longitudinal dataset on biomedical researchers that will not only support the projects, but provide infrastructure for the research community.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Program Projects (P01)
Project #
4P01AG039347-04
Application #
9116058
Study Section
Special Emphasis Panel (ZAG1)
Program Officer
Bhattacharyya, Partha
Project Start
2013-09-30
Project End
2018-06-30
Budget Start
2016-08-01
Budget End
2017-06-30
Support Year
4
Fiscal Year
2016
Total Cost
Indirect Cost
Name
National Bureau of Economic Research
Department
Type
DUNS #
054552435
City
Cambridge
State
MA
Country
United States
Zip Code
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
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
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:

Showing the most recent 10 out of 31 publications