  We conduct the first natural field experiment to explore the relationship
between the "meaningfulness" of a task and worker effort. We employed about
2,500 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.
