Workforce automation risks across race and gender in the United States.
Although the effects of automation on the future of work have received considerable attention, little research has been conducted on the costs of this technological transformation for different populations of workers. This article makes an important contribution as one of the first to analyze the in...
| Publicado en: | American Journal of Economics & Sociology Vol. 83; no. 2; pp. 463 - 493 |
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| Formato: | Artículo |
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Wiley-Blackwell
Mar2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=175945878&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 175945878 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00029246 AES jtl: American Journal of Economics & Sociology issn: 00029246 maglogo: Y pubinfo: dt: Mar2024 vid: 83 iid: 2 pid: 480 pub: Wiley-Blackwell artinfo: ui: 175945878 10.1111/ajes.12554 ppf: 463 ppct: 30 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P size: 1.4MB tig: atl: Workforce automation risks across race and gender in the United States. aug: au: McManus, Ian P. affil: Marlboro Institute for Liberal Arts & Interdisciplinary Studies, Emerson College, Boston Massachusetts, , USA su: United States Race Gender Labor supply Human capital Automation sug: subj: Race Gender Labor supply Human capital United States Temporary Help Services Automation ab: Although the effects of automation on the future of work have received considerable attention, little research has been conducted on the costs of this technological transformation for different populations of workers. This article makes an important contribution as one of the first to analyze the intersectional effects of workforce automation across race and gender in the United States. Multilevel survey data models are employed using two distinct measures of automation job displacement risk for over 1.4 million Americans across 385 occupations. This research demonstrates that the intersection of race and gender matters for individual automation risks. Education, age, disability, and nativity are also significant. These findings indicate that labor market outcomes of job automation will be based not only on differences in human capital but critically on socially constructed identities as well. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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