{"title":"美国不同种族和性别的劳动力自动化风险","authors":"Ian P. McManus","doi":"10.1111/ajes.12554","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":47133,"journal":{"name":"American Journal of Economics and Sociology","volume":"83 2","pages":"463-492"},"PeriodicalIF":0.9000,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Workforce automation risks across race and gender in the United States\",\"authors\":\"Ian P. McManus\",\"doi\":\"10.1111/ajes.12554\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":47133,\"journal\":{\"name\":\"American Journal of Economics and Sociology\",\"volume\":\"83 2\",\"pages\":\"463-492\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2023-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Economics and Sociology\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/ajes.12554\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Economics and Sociology","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/ajes.12554","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
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 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.
期刊介绍：
The American Journal of Economics and Sociology (AJES) was founded in 1941, with support from the Robert Schalkenbach Foundation, to encourage the development of transdisciplinary solutions to social problems. In the introduction to the first issue, John Dewey observed that “the hostile state of the world and the intellectual division that has been built up in so-called ‘social science,’ are … reflections and expressions of the same fundamental causes.” Dewey commended this journal for its intention to promote “synthesis in the social field.” Dewey wrote those words almost six decades after the social science associations split off from the American Historical Association in pursuit of value-free knowledge derived from specialized disciplines. Since he wrote them, academic or disciplinary specialization has become even more pronounced. Multi-disciplinary work is superficially extolled in major universities, but practices and incentives still favor highly specialized work. The result is that academia has become a bastion of analytic excellence, breaking phenomena into components for intensive investigation, but it contributes little synthetic or holistic understanding that can aid society in finding solutions to contemporary problems. Analytic work remains important, but in response to the current lop-sided emphasis on specialization, the board of AJES has decided to return to its roots by emphasizing a more integrated and practical approach to knowledge.
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