A recent article in Perspectives on Psychological Science (Webb & Tangney, 2022) reported a study in which just 2.6% of participants recruited on Amazon’s Mechanical Turk (MTurk) were deemed “valid.” The authors highlighted some well-established limitations of MTurk, but their central claims—that MTurk is “too good to be true” and that it captured “only 14 human beings . . . [out of] N = 529”—are radically misleading, yet have been repeated widely. This commentary aims to (a) correct the record (i.e., by showing that Webb and Tangney’s approach to data collection led to unusually low data quality) and (b) offer a shift in perspective for running high-quality studies online. Negative attitudes toward MTurk sometimes reflect a fundamental misunderstanding of what the platform offers and how it should be used in research. Beyond pointing to research that details strategies for effective design and recruitment on MTurk, we stress that MTurk is not suitable for every study. Effective use requires specific expertise and design considerations. Like all tools used in research—from advanced hardware to specialist software—the tool itself places constraints on what one should use it for. Ultimately, high-quality data is the responsibility of the researcher, not the crowdsourcing platform.

中文翻译：

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高质量在线数据收集的负担在于研究人员，而不是招聘平台


《心理科学展望》（Webb & Tangney，2022）最近发表的一篇文章报道了一项研究，其中只有 2.6% 在亚马逊 Mechanical Turk (MTurk) 上招募的参与者被视为“有效”。作者强调了 MTurk 的一些既定局限性，但他们的核心主张是 MTurk“好得令人难以置信”，并且它“只捕获了 14 个人……”。 。 。 [out of] N = 529”——极具误导性，但却被广泛重复。本评论旨在 (a) 纠正记录（即表明 Webb 和 Tangney 的数据收集方法导致数据质量异常低下）和 (b) 为在线进行高质量研究提供视角转变。对 MTurk 的负面态度有时反映出对该平台提供的功能以及如何在研究中使用该平台的根本误解。除了详细介绍 MTurk 有效设计和招募策略的研究之外，我们强调 MTurk 并不适合所有研究。有效的使用需要特定的专业知识和设计考虑。与研究中使用的所有工具一样（从先进的硬件到专业软件），工具本身对人们应该使用它的用途施加了限制。最终，高质量数据是研究人员的责任，而不是众包平台的责任。