The Frequent Frames model (Mintz, 2003) attempts to assign words to word categories based on their distributional patterns of usage. This model is highly successful in categorizing words in child-directed speech in English, but has been shown by Erkelens (2008) to be less effective with Dutch material. We show that extending the amount of contextual information in a frame by making use of the full utterance context does not improve categorization performance, but that constraining the fillers of Frequent Frames to be relatively less frequently occurring words does improve categorization significantly. We connect the latter result to a basic dichotomy in some languages between function words and content words, and conclude that, at least for English and Dutch, paying attention to this dichotomy is of greater importance for distributional bootstrapping proposals than the specific distributional contexts that are used to categorize words.