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Description: An important feature of language production is the flexibility of lexical selection; producers could refer to an animal as chimpanzee, chimp, ape, she, and so on. Thus, a key question for psycholinguistic research is how and why producers make the lexical selections that they do. Information theoretic approaches have argued that producers regulate the uncertainty of the utterance for comprehenders, for example using longer words like chimpanzee if their messages are likely to be misunderstood, and shorter ones like chimp when the message is easy to understand. In this work, we test for the relative contributions of the information theoretic approach and an approach more aligned with psycholinguistic models of language production. We examine the effect on lexical selection of whole utterance-level factors that we take as a proxy for register or style in message-driven production accounts. Using a modern machine learning-oriented approach, we show that for both naturalistic stimuli and real-world corpora, producers prefer words to be longer in systematically different contexts, independent of the specific message they are trying to convey. We do not find evidence for regulation of uncertainty, as in information theoretic approaches. We offer suggestions for modification of the standard psycholinguistic production approach that emphasizes the need for the field to specify how message formulation influences lexical choice in multiword utterances.