Breaking monotony with meaning: Motivation in crowdsourcing markets
Dana Chandler,Adam Kapelner +1 more
TLDR
It is found that when a task was framed more meaningfully, workers were more likely to participate and the meaningful treatment increased the quantity of output while the shredded treatment decreased the quality of output.Abstract:
We conduct the first natural field experiment to explore the relationship between the “meaningfulness” of a task and worker effort. We employed about 2500 workers from Amazon's Mechanical Turk (MTurk), an online labor market, to label medical images. Although given an identical task, we experimentally manipulated how the task was framed. Subjects in the meaningful treatment were told that they were labeling tumor cells in order to assist medical researchers, subjects in the zero-context condition (the control group) were not told the purpose of the task, and, in stark contrast, subjects in the shredded treatment were not given context and were additionally told that their work would be discarded. We found that when a task was framed more meaningfully, workers were more likely to participate. We also found that the meaningful treatment increased the quantity of output (with an insignificant change in quality) while the shredded treatment decreased the quality of output (with no change in quantity). We believe these results will generalize to other short-term labor markets. Our study also discusses MTurk as an exciting platform for running natural field experiments in economics.read more
Citations
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Journal ArticleDOI
Gender Differences in Preferences
Rachel Croson,Uri Gneezy +1 more
TL;DR: This paper reviewed the literature on gender differences in economic experiments and identified robust differences in risk preferences, social (other-regarding) preferences, and competitive preferences, speculating on the source of these differences and their implications.
Running experiments on Amazon Mechanical Turk
TL;DR: The authors presented new demographic data about the Mechanical Turk subject population, reviewed the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and compared the magnitude of effects obtained using Mechanical Turk and traditional subject pools.
Journal ArticleDOI
Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk
TL;DR: It is shown that respondents recruited in this manner are often more representative of the U.S. population than in-person convenience samples but less representative than subjects in Internet-based panels or national probability samples.
Posted Content
Running experiments on Amazon Mechanical Turk
TL;DR: The authors presented new demographic data about the Mechanical Turk subject population, reviewed the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and compared the magnitude of effects obtained using Mechanical Turk and traditional subject pools.
Journal ArticleDOI
Inside the Turk Understanding Mechanical Turk as a Participant Pool
Gabriele Paolacci,Jesse Chandler +1 more
TL;DR: The characteristics of Mechanical Turk as a participant pool for psychology and other social sciences, highlighting the traits of the MTurk samples, why people become Mechanical Turk workers and research participants, and how data quality on Mechanical Turk compares to that from other pools and depends on controllable and uncontrollable factors as mentioned in this paper.
References
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Book
The WEIRDest People in the World
TL;DR: A review of the comparative database from across the behavioral sciences suggests both that there is substantial variability in experimental results across populations and that WEIRD subjects are particularly unusual compared with the rest of the species – frequent outliers.
Journal ArticleDOI
Gender Differences in Preferences
Rachel Croson,Uri Gneezy +1 more
TL;DR: This paper reviewed the literature on gender differences in economic experiments and identified robust differences in risk preferences, social (other-regarding) preferences, and competitive preferences, speculating on the source of these differences and their implications.
Journal ArticleDOI
WEIRD languages have misled us, too [Comment on Henrich et al.]
Asifa Majid,Stephen C. Levinson +1 more
Running experiments on Amazon Mechanical Turk
TL;DR: The authors presented new demographic data about the Mechanical Turk subject population, reviewed the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and compared the magnitude of effects obtained using Mechanical Turk and traditional subject pools.