dc.contributor.advisor | Westerman, George | |
dc.contributor.advisor | O'Reilly, Una-May | |
dc.contributor.author | Clochard, Axelle | |
dc.date.accessioned | 2022-06-15T12:58:38Z | |
dc.date.available | 2022-06-15T12:58:38Z | |
dc.date.issued | 2022-02 | |
dc.date.submitted | 2022-04-13T17:59:01.323Z | |
dc.identifier.uri | https://hdl.handle.net/1721.1/143136 | |
dc.description.abstract | The importance of good career advice has become especially salient as the COVID-19 pandemic forces millions of displaced workers to look for stable employment. This research hopes to add to the career advice literature by using network analysis of U.S. job transitions data to model the universe of career paths available from a first job. By linking together the occupations that are connected by significant flows of workers and focusing on the paths that lead from precarious occupations, we can identify areas of the labor market that offer dependable channels to upward mobility and areas that do not, where workers could benefit from additional guidance. Overall, we find that, although there exist opportunities for workers of various educational attainment, upward mobility prospect are generally curtailed for workers without a Bachelor’s degree. What’s more, low-wage or shrinking occupations appear to offer limited access to stable, high-wage employment. Still, there are a number of bright spots occupations that can provide low-wage workers with dependable access to sustainable employment down the line. We hope to use this knowledge to inform the nature of advice given to workers by suggesting careers that are associated with living wages and stability in the long term. | |
dc.publisher | Massachusetts Institute of Technology | |
dc.rights | In Copyright - Educational Use Permitted | |
dc.rights | Copyright MIT | |
dc.rights.uri | http://rightsstatements.org/page/InC-EDU/1.0/ | |
dc.title | Using Network Analysis of Job Transitions to Inform Career
Advice | |
dc.type | Thesis | |
dc.description.degree | S.M. | |
dc.description.degree | S.M. | |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
dc.contributor.department | Massachusetts Institute of Technology. Institute for Data, Systems, and Society | |
mit.thesis.degree | Master | |
thesis.degree.name | Master of Science in Technology and Policy | |
thesis.degree.name | Master of Science in Electrical Engineering and Computer Science | |