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Several studies have reported that visual word recognition is influenced by the frequency of the stem within a morphologically complex word (e.g., Taft, 1979). Typically, participants in these experiments are asked to make lexical decisions for sets of words matched on whole‐word frequency but varied on the frequency of stems (e.g., unreal versus refuel; Taft & Ardasinski, 2006). Results show faster lexical decision times for words with high‐frequency stems. This result has been demonstrated for both inflectional and derivational morphology, and across a number of different languages, including Italian (Burani, Salmaso, & Carramazza, 1984), Dutch (Baayen, Dijkstra, & Schreuder, 1997), and French (Colé, Beauvillain, & Segui, 1989). The fact that recognition time of morphologically complex words is based at least in part on the frequency of the stem (e.g., the real in unreal) indicates that the word recognition system is sensitive to morphological structure.

More recent research has begun to indicate that these morpheme frequency effects might be modulated by other factors. Baayen, Wurm, and Aycock (2007) used lexical decision data from the English Lexicon Project (Balota et al., 2004) to suggest that the effect of morpheme frequency might be restricted to words with low whole‐word frequency. This finding is unsurprising given that the recognition of low frequency words is slower and less accurate than for high frequency words; thus, there is less pressure in the system to represent morphemic constituents when words are high in frequency. Likewise, there is some evidence to suggest that stem frequency effects are larger when derived target words contain highly productive affixes (Bertram, Schreuder, & Baayen, 2000; Ford, Davis, & Marslen‐Wilson, 2010). Productive affixes tend to occur frequently, in combination with many different stems and in semantically consistent ways (e.g., ‐ness as in kindness is productive; ‐th as in warmth is not).

The morpheme frequency effects that I have described seem straightforward, but there is an important methodological point to consider. Typically, these experiments compare the recognition of words matched on whole‐word frequency while varying stem frequency. However, the way that we count stem frequency entails theoretical commitments. Is stem frequency simply the number of times that a particular stem occurs in a corpus of a certain size? Or, should stem frequency also include the frequency of the morphologically complex words in which it occurs? If readers analyse morphologically complex words in terms of their constituents, then the latter approach would seem to be the more valid, since each encounter with a morphologically complex word reinforces knowledge of its stem. Taking this argument further, if decomposition arises in some morphologically complex words more than others (e.g., those with highly productive affixes), then that may also influence how we should quantify stem frequency. Researchers do not always think about how their decisions to match stimuli on psycholinguistic properties reflect underlying theoretical commitments. In this instance, theoretical uncertainties make it difficult to design and interpret experiments of this nature.