Geographical Discrimination in Digital Labor Platforms
Geographical Discrimination in Digital Labor Platforms
复制标题
数字劳动力平台中的地域歧视
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
H. Galperin
中科院分区：
文献类型：
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作者：
H. Galperin
本研究旨在实证检验无摩擦的全球数字劳动力市场的叙述。实证策略是基于对Nubelo内部数据的检查，Nubelo是最大的西班牙语在线劳动力平台之一。结果表明，在传统劳动力市场长期观察到的与信息有关的摩擦在在线平台上加剧，导致基于原籍国的歧视。我们发现，在控制了可观察到的工人特征和他们的工作出价后，外国求职者赢得西班牙雇主合同的可能性降低了42%，西班牙雇主约占平台上所有雇主的三分之二。我们将这一结果归因于社会刻板印象的激活，这些刻板印象在缺乏关于个别工人素质的可核实信息的情况下指导雇主的雇用决定。我们得出了平台设计和在线劳动合同的治理的影响。
This study seeks to empirically test the narrative of a frictionless global market for digital labor. The empirical strategy is based on the examination of internal data from Nubelo, one of the largest Spanish-language online labor platforms. The results suggest that informationrelated frictions long observed in traditional labor markets are exacerbated in online platforms, resulting in discrimination based on country of origin. We show that, after controlling for observable workers’ characteristics and their job bids, foreign job-seekers are 42 percent less likely to win contracts from Spanish employers, which represent about twothirds of all employers in the platform. We attribute this result to the activation of social stereotypes that orient employers’ hiring decisions, in the absence of verifiable information about the quality of individual workers. We draw implications for platform design and the governance of online labor contracts.