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First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. Mallows models are a classically studied class of distributions over permutations that can be viewed as a sequential model in which items are inserted one by one into a ranking. This paper proposes an interesting hierarchical generalization of Mallows models in which groups of items are sequentially ``merged'' together (as they would be in mergesort). The model can also be viewed as a special case of a recently proposed class of ``riffle independent'' models by Huang/Guestrin, but with a more tractable number of parameters in general and better computational properties. There are several nice contributions in this paper, including a simple and elegant characterization of identifiability of the structure, as well as an interesting structure estimation algorithm based on the inside-outside parsing algorithm for stochastic context free grammars.