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There is disclosed a method and system for determining a productivity rate of a user in a computer-implemented crowd-sourced environment. The method comprises, in a training phase: acquiring a training project; determining, set of project-specific features indicative of one or more characteristics of the training project; acquiring, a plurality of training results; determining a set of user-task specific features; determining, a user activity history associated with the user; generating a set of training data including the set of project-specific features, the set of user-task specific features, and the user activity history; training a machine learning algorithm (MLA), the training including: determining, a set of features representative of a property of the set of training data; and generating an inferred function based on the set of features, the inferred function being configured to determine the productivity rate of the user for a given project.