1 Introduction

Language allows us to communicate about the world. This is possible because parts of language (e.g., words) refer to parts of the world (e.g., objects). However, this relationship is rarely one‐to‐one. For example, the word “cat” refers to a range of objects that share features on certain dimensions, such as shape, but differ on others, such as color. This abstraction over features is a ubiquitous property of natural language called underspecification (Geeraerts, 2009, p. 196).

Different areas of the lexicon have different characteristic patterns of underspecification. For example, words for artifacts tend to specify shape or function, and underspecify color; words for substances tend to specify material, and underspecify shape (Smith & Samuelson, 2006). These regularities in the lexicon enable learners to acquire higher order generalizations about which dimensions are relevant to the meaning of words learned in particular contexts, for example, the shape bias that labels for objects generalize by shape (Smith, Jones, Landau, Gershkoff‐Stowe, & Samuelson, 2002).

However, this account does not explain how the lexicon comes to have these helpful regularities in the first place. One possibility is that learners have strong constraints on the kind of word meanings they will entertain (Markman, 1994; Waxman & Kosowski, 1990), which map straightforwardly to strong constraints on the kinds of underspecification lexicons can exhibit. Instead, we show that the same processes that enable learners to form higher order generalizations on the basis of regularities in the lexicon can also shape the lexicon to exhibit those regularities in the first place, leading it to reflect the systematic salience of particular dimensions in contexts of learning and use. This happens not over the course of an individual's learning, but via the cumulative language change that occurs when a lexicon is transmitted.

The attentional learning account states that “context cues that co‐occur with (and define) specific tasks will come with repeated experience to shift attention to the task‐relevant information” (Smith, Colunga, & Yoshida, 2010, p. 1295). Modeling the learning of (part of) the lexicon as this kind of “specific task,” we train and test learners on an artificial language in contexts where one dimension of meaning is systematically made less salient (backgrounded). We manipulate salience by casting word learning and use as a series of discrimination games where one dimension is never helpful. The general format of the discrimination game has a precedent in the “guessing game” of Steels (2003), while manipulating one dimension to be unhelpful builds on the well‐established results in the concepts and categories literature showing that dimensions that are unhelpful for discrimination are attended to less than helpful dimensions (e.g., Kruschke, 1992; Medin & Schaffer, 1978). In real word learning, this backgrounding effect is more likely the outcome of factors such as domain‐specific knowledge (Kelemen & Bloom, 1994; Lin & Murphy, 1997), increased salience of functional features (Booth & Waxman, 2002; Keil, 1994; Kemler Nelson, 1995), attentional cues from speakers (Tomasello, 2000), inference of the speaker's intention (Bloom, 2000; Xu & Tenenbaum, 2007), or other “non‐linguistic evidence of the speaker's locus of attention” (Clark, 1997).1 This systematic backgrounding has only a small effect at the individual level. However, over cultural transmission, a lexicon that initially specifies equally across all dimensions changes to reflect the differing salience of dimensions in learning and use, leading to an emerging system which preferentially underspecifies the backgrounded dimension. This serves as a demonstration of how cultural transmission amplifies the effects of individual learning processes to create an adaptively specified lexicon.