Abstract: A crowdsourcing environment is described herein which uses a single-stage or multi-stage approach to evaluate the quality of work performed by a worker, with respect to an identified task. In the multi-stage case, an evaluation system, in the first stage, determines whether the worker corresponds to a spam agent. In a second stage, for a non-spam worker, the evaluation system determines the propensity of the worker to perform desirable (e.g., accurate) work in the future. The evaluation system operates based on a set of features, including worker-focused features (which describe work performed by the particular worker), task-focused features (which describe tasks performed in the crowdsourcing environment), and system-focused features (which describe aspects of the configuration of the crowdsourcing environment). According to one illustrative aspect, the evaluation system performs its analysis using at least one model, produced using any type of supervised machine learning technique.