Modeling the Relationship between Input Distributions and Learning Trajectories with the Tolerance Principle

Abstract

Child language learners develop with remarkable uniformity, both in their learning trajectories and ultimate outcomes, despite major differences in their learning environments. In this paper, we explore the role that the frequencies and distributions of irregular lexical items in the input plays in driving learning trajectories. We conclude that while the Tolerance Principle, a type-based model of productivity learning, accounts for inter-learner uniformity, it also interacts with input distributions to drive cross-linguistic variation in learning trajectories.