In the U.S., women are severely underrepresented in many academic and nonacademic career areas of science and engineering (S&E). This is a serious problem because women and minorities form a significant portion of the potential scientific workforce and maintaining a strong and vibrant scientific workforce is critical to economic and scientific progress. To understand the factors affecting participation of women and minorities in S&E careers one needs data. One also needs data in order to formulate and evaluate policies seeking to increase representation of women and minorities at all levels of S&E careers. The principal goal of this proposal is to use existing sources of information in novel ways to address key questions about the S&E workforce. The proposed study has four specific aims that are essential steps toward achieving the principal goal of using existing sources of information in novel ways to address key questions about the S&E workforce. Underlying the four aims will be a computational model of the dynamics of the scientific workforce. First, the NSF's Survey of Doctorate Recipients will be linked over time and enhanced with time varying covariate variables from several additional sources of information. Second, we will calculate longitudinal survey sampling weights for the purposes of using the database for inference concerning factors affecting key transitions in scientific careers. Third, the database will be used to estimate parameters in computational models of the dynamics of the scientific workforce in the U.S. The merged database will be unique in its composition and usefulness for assessing primary hypotheses about the experiences of women and minorities in the scientific workforce. Fourth, plans will be studied for incorporating additional data sources and for designing focused surveys related to key hypotheses.. The methods and products of this research will yield unique insights and be a key building block for future studies of polices and lifting interventions that aim to encourage the participation of women and minorities in the scientific workforce. Successful policies that lead to increased sustainability and productivity in science, engineering, and health careers are anticipated to have significant, positive impacts on science research, public health, and the economy.
We propose to create a substantial database from public sources and conduct statistical analyses to estimate a computational model of workforce dynamics. This work will lead to better understanding of scientific, engineering, and health career paths and help improve policies to increase retention and productivity, especially of women and minorities, thereby improving science, public health, and the economy.
