Becoming the Super Turker:Increasing Wages via a Strategy from High Earning Workers

Becoming the Super Turker:Increasing Wages via a Strategy from High Earning Workers
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成为超级土耳其人:通过高收入工人的策略增加工资

DOI:
10.1145/3366423.3380200
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发表时间:
2020
期刊:
The Web Conference
影响因子:
--
通讯作者:
Bigham, Jeffrey
Bigham, Jeffrey
中科院分区:
--
文献类型:
--
作者:
Savage, Saiph;Chiang, Chun Wei;Saito, Susumu;Toxtli, Carlos;Bigham, Jeffrey

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传统上,群体市场通过不提供关于哪些任务支付公平或哪些请求者不可靠的透明信息来限制工人。研究人员认为,人群工作者工资低的一个关键原因是缺乏透明度。因此,开发了一些工具,在人群市场中提供更多的透明度,以帮助工人。然而,尽管大多数工人使用这些工具,他们的收入仍然低于最低工资。我们认为,缺少的要素是如何使用透明度信息的指导。在本文中,我们探讨了新手如何通过遵循超级Turkers的透明度标准来提高收入,即,在亚马逊土耳其机器人(MTurk)上赚取更高工资的人群。我们相信,Super Turkers已经开发出了使用透明度信息的有效流程。因此,通过让新手遵循超级Turker标准(一个简单且在超级Turker中流行的标准),我们可以帮助新手增加工资。为此,我们:(i)进行了一项调查和数据分析,以通过计算确定超级Turker使用的简单而通用的标准,用于处理透明度工具;(ii)部署了一个为期两周的实地实验,让遵循超级Turker标准的新手在MTurk上找到更好的工作。在我们的研究中,新手查看了1,394个请求者的25,000多个任务。我们发现,使用超级特克标准的新手比其他新手获得更好的工资。我们的研究结果强调,支持人群工作者的工具开发应该与教育机会相结合,教育工作者如何有效地使用工具及其相关指标(例如,透明度值)。最后,我们提出了一些设计建议,以使人群工作者能够获得更高的薪水。
Crowd markets have traditionally limited workers by not providing transparency information concerning which tasks pay fairly or which requesters are unreliable. Researchers believe that a key reason why crowd workers earn low wages is due to this lack of transparency. As a result, tools have been developed to provide more transparency within crowd markets to help workers. However, while most workers use these tools, they still earn less than minimum wage. We argue that the missing element is guidance on how to use transparency information. In this paper, we explore how novice workers can improve their earnings by following the transparency criteria of Super Turkers, i.e., crowd workers who earn higher salaries on Amazon Mechanical Turk (MTurk). We believe that Super Turkers have developed effective processes for using transparency information. Therefore, by having novices follow a Super Turker criteria (one that is simple and popular among Super Turkers), we can help novices increase their wages. For this purpose, we: (i) conducted a survey and data analysis to computationally identify a simple yet common criteria that Super Turkers use for handling transparency tools; (ii) deployed a two-week field experiment with novices who followed this Super Turker criteria to find better work on MTurk. Novices in our study viewed over 25,000 tasks by 1,394 requesters. We found that novices who utilized this Super Turkers’ criteria earned better wages than other novices. Our results highlight that tool development to support crowd workers should be paired with educational opportunities that teach workers how to effectively use the tools and their related metrics (e.g., transparency values). We finish with design recommendations for empowering crowd workers to earn higher salaries.
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