  Online labor platforms, such as the Amazon Mechanical Turk, provide an
effective framework for eliciting responses to judgment tasks. Previous work
has shown that workers respond best to financial incentives, especially to
extra bonuses. However, most of the tested incentives involve describing the
bonus conditions in formulas instead of plain English. We believe that
different incentives given in English (or in qualitative framing) will result
in differences in workers' performance, especially when task difficulties vary.
In this paper, we report the preliminary results of a crowdsourcing experiment
comparing workers' performance using only qualitative framings of financial
incentives. Our results demonstrate a significant increase in workers'
performance using a specific well-formulated qualitative framing inspired by
the Peer Truth Serum. This positive effect is observed only when the difficulty
of the task is high, while when the task is easy there is no difference of
which incentives to use.
