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Paid crowd work offers remarkable opportunities for improving productivity, social mobility, and the global economy by engaging a geographically distributed workforce to complete complex tasks on demand and at scale. But it is also possible that crowd work will fail to achieve its potential, focusing on assembly-line piecework. Can we foresee a future crowd(More)
The goal of the Crowdsourcing at Scale workshop was to identify the biggest challenges in very large-scale crowd-sourcing and to reduce the chasm between industrial and academic crowdsourcing research. The aim of the Disco: Human and Machine Learning in Games workshop was to extend upon the focus of two past workshops and explore the intersection of(More)
Internal HITs on Mechanical Turk can be programmatically restrictive, and as a result, many requesters turn to using external HITs as a more flexible alternative. However, creating such HITs can be redundant and time-consuming. We present MmmTurkey, a framework that enables researchers to not only quickly create and manage external HITs, but more(More)
  • David Mcclosky, B S, Sc M, Mark Johnson, Dan Date, Klein +62 others
  • 2010
Current efforts in syntactic parsing are largely data-driven. These methods require labeled examples of syntactic structures to learn statistical patterns governing these structures. Labeled data typically requires expert annotators which makes it both time consuming and costly to produce. Furthermore, once training data has been created for one textual(More)
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