In this project, we are studying the nondegree credentials needed for a job in the Skilled Technical Workforce (STW). This work is important because the skilled technical workforce is a fast growing and crucial sector of the US economy, and these STW jobs can offer a path to the middle class for millions of Americans. Despite the importance of the skilled technical workforce, there are massive data gaps between the skilled technical workforce players, namely federal and state governments, employers, and the educational institutions that provide the nondegree credential training. We spent this summer bridging some of these data gaps. First, we used R’s web scraping capabilities to collect the certifications associated with the 133 skilled technical workforce occupations listed in the Department of Labor’s Occupational Information Network (ONET). Then, we collected the certifications demanded by employers for these occupations in job-ads from Burning Glass Technologies. We used Natural Language Processing techniques to standardize the job-ad certifications using the ONET certification names. Finally, we used network analysis to visualize the connections between occupations and certifications, thus highlighting paths workers could potentially take in the STW. If you’d like to learn more, please attend our virtual poster session!
University of Minnesota, College of Liberal Arts
Washington and Lee University, Department of Sociology
University of Colorado Boulder, College of Arts and Sciences
Principal Scientist, Biocomplexity Institute, University of Virginia
Postdoctoral Research Associate, Biocomplexity Institute, University of Virginia
National Center for Science and Engineering Statistics