The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Lousy and Lovely Jobs: The Rising Polarization of Work in Britain
Open accessAbstract
This paper shows that the United Kingdom since 1975 has exhibited a pattern of job polarization with rises in employment shares in the highest- and lowest-wage occupations. This is not entirely consistent with the idea of skill-biased technical change as a hypothesis about the impact of technology on the labor market. We argue that the “routinization” hypothesis recently proposed by Autor, Levy, and Murnane (2003) is a better explanation of job polarization, though other factors may also be important. We show that job polarization can explain one-third of the rise in the log(50/10) wage differential and one-half of the rise in the log(90/50).
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Citations
Cites
The Skill Content of Recent Technological Change: An Empirical Exploration
Autor, D. H., Levy, F., & Murnane, R. J. (2003) · The Quarterly Journal of Economics · doi:10.1162/003355303322552801 · Cited by 6,205
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Hellerstein, J. K., Neumark, D., & Troske, K. R. (1999) · Journal of Labor Economics · doi:10.1086/209926 · Cited by 411
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Self-citationThe Growing Importance of Social Skills in the Labor Market*
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Polanyi's Paradox and the Shape of Employment Growth
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Job Polarization and Jobless Recoveries
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(2007) · University of Huddersfield Repository (University of Huddersfield) · Cited by 63
Erebak, S., & Turgut, T. (2021) · The Journal of High Technology Management Research · doi:10.1016/j.hitech.2021.100419 · Cited by 45
Robots are not always bad for employment and wages
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No automation please, we’re British: technology and the prospects for work
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Job Polarization and Rising Inequality in the Nation and the New York-Northern New Jersey Region
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Generative AI and Organizational Structure in the Knowledge Economy
Xu, F., Hou, J., Chen, W., & Xie, K. (2025) · arXiv · doi:10.48550/arxiv.2506.00532 · Cited by 22
Metadata
- Authors
- Goos, M., & Manning, A.
- Venue
- Review of Economics and Statistics
- Publisher
- MIT Press - Journals
- Published
- 2007-02
- Volume
- 89
- Issue
- 1
- Pages
- 118-133
- ISSN
- 0034-6535 (ISSN-L)
- 1530-9142
- OpenAlex
- W1601261096
- Cited by
- 2,285
- References
- 3
- FWCI
- 144.04
- Type
- journal article
- Language
- en
- Open access
- green
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.