Inside the Turk

By Gabriele Paolacci, Jesse J. Chandler. 2014

1,658 citations recorded by the source corpus.

Subfields: Computer Science Applications, Human-Computer Interaction

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In Human-Computer Interaction

Citations in the corpus

Manipulating and Measuring Model Interpretability (2018, background): “tudies show that data from high reputation Mechanical Turk workers are comparable to data from commercial panels and university pools when assessing factors such as attentiveness, honesty, and effort [11, 13, 16, 53, 59]. (a) Clear, two-feature condition (CLEAR-2). (b) Black-box, two-feature conditi”
The shape of and solutions to the MTurk quality crisis (2020, background): “For these reasons, the use of MTurk for survey research has grown dramatically across a variety of disciplines, including psychology (Paolacci and Chandler, 2014; Zhou and Fishbach, 2016), economics (Horton et al ., 2011), public administration (Stritch et al ., 2017), and sociology (Shank, 2016).”
Do Investors Value Sustainability? A Natural Experiment Examining Ranking and Fund Flows (2019, background): “…recruited through MTurk tend to perform similarly on tasks (Casler et al., 2013) and better in attention checks (Hauser and Schwarz, 2016) than traditional participant pools traditionally recruited through labs, while representing a more diverse set of participants (Paolacci and Chandler, 2014).”
Contraction as a Response to Group Threat: Demographic Decline and Whites’ Classification of People Who Are Ambiguously White (2020, background): “MTurk workers are not representative of the U.S. population (Huff and Tingley 2015; Paolacci and Chandler 2014).”
The quality of data collected online: An investigation of careless responding in a crowdsourced sample (2020, background): “…platforms offer a more diverse population compared to typically homogenous samples from psychological studies (Kan and Drummey, 2018): In the case of MTurk, these workers are composed of a demographic containing more than 5000000 individuals from 190 countries (Paolacci and Chandler, 2014).”
Use of AI-based tools for healthcare purposes: a survey study from consumers’ perspectives (2020, methodology): “MTurk is a survey tool that has been used in several studies as an acceptable means to collect individual-level data from the general population of interest [57].”
Are Attention Check Questions a Threat to Scale Validity? (2018, background): “This outcome can be disastrous because it means that the recommended practice of using attention checks for screening (Buhrmester, Kwang, & Gosling, 2011; Paolacci & Chandler, 2014) may create a more serious problem than it solves.”
Intellectual humility and openness to the opposing view (2018, methodology): “We recruited 188 American adults (Mage = 32.84, SD = 11.65, range = 18–69; 109 women and 78 men, 1 unspecified) from the online panel Amazon Mechanical Turk (Buhrmester, Kwang, & Gosling, 2011; Paolacci & Chandler, 2014).”
The Future of Work in the ‘Sharing Economy’. Market Efficiency and Equitable Opportunities or Unfair Precarisation? (2016, neutral): “…experiments, and user studies; as a result there is a growing body of research discussing the reliability and validity of this platform for research purposes (Grysman, 2015; Kittur et al., 2008; Layman & Sigurdsson, 2013; Paolacci & Chandler, 2014; Rand, 2012; Rouse, 2015; Schmidt, 2015) xl .”