Unpacking the polarization of workplace skills
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eaao6030.full.pdf
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1.75 MB
Format
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Checksum (MD5)
9f2cb2b6197343711e58862d25670929
Author(s)
Rahwan, Iyad
Alabdulkareem, Ahmad
Frank, Morgan Ryan
Sun, Lijun
AlShebli, Bedoor
Hidalgo Ramaciotti, Cesar A.
Date Issued
July 2018
Journal
Science Advances
Publisher
American Association for the Advancement of Science (AAAS)
Citation
Alabdulkareem, Ahmad, Morgan R. Frank, Lijun Sun, Bedoor AlShebli, César Hidalgo, and Iyad Rahwan. “Unpacking the Polarization of Workplace Skills.” Science Advances 4, no. 7 (July 2018): eaao6030.
Version
Final published version
Abstract
Economic inequality is one of the biggest challenges facing society today. Inequality has been recently exacerbated by growth in high- and low-wage occupations at the expense of middle-wage occupations, leading to a “hollowing” of the middle class. Yet, our understanding of how workplace skills drive this process is limited. Specifically, how do skill requirements distinguish high- and low-wage occupations, and does this distinction constrain the mobility of individuals and urban labor markets? Using unsupervised clustering techniques from network science, we show that skills exhibit a striking polarization into two clusters that highlight the specific social-cognitive skills and sensory-physical skills of high- and low-wage occupations, respectively. The connections between skills explain various dynamics: how workers transition between occupations, how cities acquire comparative advantage in new skills, and how individual occupations change their skill requirements. We also show that the polarized skill topology constrains the career mobility of individual workers, with low-skill workers “stuck” relying on the low-wage skill set. Together, these results provide a new explanation for the persistence of occupational polarization and inform strategies to mitigate the negative effects of automation and offshoring of employment. In addition to our analysis, we provide an online tool for the public and policy makers to explore the skill network: skillscape.mit.edu.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Massachusetts Institute of Technology. Media Laboratory
MIT Technology and Development Program
Terms of Use
Creative Commons Attribution-NonCommercial 4.0 International
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1126/sciadv.aao6030
