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      Democratizing the Economy or Introducing Economic Risk? Gig Work During the COVID-19 Pandemic

      1 , 2 , 2 , 3
      Work and Occupations
      SAGE Publications

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          Abstract

          Though the growth of the gig economy has coincided with increased economic precarity in the new economy, we know less about the extent to which gig work (compared with other self-employment arrangements and non-gig work) may fuel economic insecurity among American households. We fill this gap in the literature by drawing on a sample of 4,756 workers from a unique national survey capturing economic hardships among non-standard workers like app- and platform-based gig and other self-employed workers during the COVID-19 pandemic. Results from generalized boosted regression modeling, utilizing machine learning to account for potential endogeneity, demonstrated that gig workers experienced significantly greater economic hardship than non-gig and other self-employed workers during the pandemic. For example, gig workers were more likely to experience food insecurity, miss bill payments, and suffer income loss compared with non-gig and other self-employed workers during the pandemic. While household liquid assets endowment prior to the pandemic reduced the effect of gig work on experiencing economic hardships, having dependent children in the household increased this effect. Thus, contrary to democratizing entrepreneurship opportunities, these findings suggest that the expansion of the gig economy may exacerbate labor market inequality, where wealth-endowed families are protected against adverse economic consequences of the gig economy. We discuss the implications of these findings for inequality-reducing labor market policies, including policies that account for the interconnectedness of family and the labor market.

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          Most cited references52

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            Propensity score estimation with boosted regression for evaluating causal effects in observational studies.

            Causal effect modeling with naturalistic rather than experimental data is challenging. In observational studies participants in different treatment conditions may also differ on pretreatment characteristics that influence outcomes. Propensity score methods can theoretically eliminate these confounds for all observed covariates, but accurate estimation of propensity scores is impeded by large numbers of covariates, uncertain functional forms for their associations with treatment selection, and other problems. This article demonstrates that boosting, a modern statistical technique, can overcome many of these obstacles. The authors illustrate this approach with a study of adolescent probationers in substance abuse treatment programs. Propensity score weights estimated using boosting eliminate most pretreatment group differences and substantially alter the apparent relative effects of adolescent substance abuse treatment. ((c) 2004 APA, all rights reserved).
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              What Do Platforms Do? Understanding the Gig Economy

              The rapid growth of the platform economy has provoked scholarly discussion of its consequences for the nature of work and employment. We identify four major themes in the literature on platform work and the underlying metaphors associated with each. Platforms are seen as entrepreneurial incubators, digital cages, accelerants of precarity, and chameleons adapting to their environments. Each of these devices has limitations, which leads us to introduce an alternative image of platforms: as permissive potentates that externalize responsibility and control over economic transactions while still exercising concentrated power. As a consequence, platforms represent a distinct type of governance mechanism, different from markets, hierarchies, or networks, and therefore pose a unique set of problems for regulators, workers, and their competitors in the conventional economy. Reflecting the instability of the platform structure, struggles over regulatory regimes are dynamic and difficult to predict, but they are sure to gain in prominence as the platform economy grows.
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                Author and article information

                Contributors
                Journal
                Work and Occupations
                Work and Occupations
                SAGE Publications
                0730-8884
                1552-8464
                September 20 2023
                Affiliations
                [1 ]Department of Sociology, Florida Atlantic University, Boca Raton, FL, USA
                [2 ]Center for Social Development, George Warren Brown School of Social Work, Washington University in St. Louis, St. Louis, MO, USA
                [3 ]Department of Social Work, University of North Carolina at Greensboro, Greensboro, NC, USA
                Article
                10.1177/07308884231202032
                1a9b14e7-c68d-41c9-8db1-2c9c22f4163c
                © 2023

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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