Turking in the time of COVID

[1]  Aaron J. Moss,et al.  Demographic Stability on Mechanical Turk Despite COVID-19 , 2020, Trends in Cognitive Sciences.

[2]  Stella F. Lourenco,et al.  No Participant Left Behind: Conducting Science During COVID-19 , 2020, Trends in Cognitive Sciences.

[3]  David G. Rand,et al.  Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention , 2020, Psychological science.

[4]  Jesse J. Chandler,et al.  Participant carelessness and fraud: Consequences for clinical research and potential solutions. , 2020, Journal of abnormal psychology.

[5]  Cheskie Rosenzweig,et al.  The persistence of pay inequality: The gender pay gap in an anonymous online labor market , 2019, PloS one.

[6]  Aaron J. Moss,et al.  Tapped out or barely tapped? Recommendations for how to harness the vast and largely unused potential of the Mechanical Turk participant pool , 2019, PloS one.

[7]  A. Acquisti,et al.  Reputation as a sufficient condition for data quality on Amazon Mechanical Turk , 2014, Behavior research methods.

[8]  Adam J. Berinsky,et al.  Separating the Shirkers from the Workers? Making Sure Respondents Pay Attention on Self‐Administered Surveys , 2014 .

[9]  David G. Rand,et al.  Social heuristics shape intuitive cooperation , 2014, Nature Communications.

[10]  Jesse Chandler,et al.  Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers , 2013, Behavior Research Methods.

[11]  David G. Rand,et al.  The online laboratory: conducting experiments in a real labor market , 2010, ArXiv.

[12]  S. Frederick.  Journal of Economic Perspectives—Volume 19, Number 4—Fall 2005—Pages 25–42 Cognitive Reflection and Decision Making , 2022 .