Editor-in-Chief: Newman, John
4 Issues per year
IMPACT FACTOR 2016: 2.135
CiteScore 2016: 1.29
SCImago Journal Rank (SJR) 2015: 0.592
Source Normalized Impact per Paper (SNIP) 2015: 1.277
A foundational goal of cognitive linguistics is to explain linguistic phenomena in terms of general cognitive strategies rather than postulating an autonomous language module (Langacker 1987: 12–13). Metonymy is identified among the imaginative capacities of cognition (Langacker 1993: 30, 2009: 46–47). Whereas the majority of scholarship on metonymy has focused on lexical metonymy, this study explores the systematic presence of metonymy in word-formation. I argue that in many cases, the semantic relationships between stems, affixes, and the words they form can be analyzed in terms of metonymy, and that this analysis yields a better, more insightful classification than traditional descriptions of word-formation. I present a metonymic classification of suffixal word-formation in three languages: Russian, Czech, and Norwegian. The system of classification is designed to maximize comparison between lexical and word-formational metonymy. This comparison supports another central claim of cognitive linguistics, namely that grammar (in this case word-formation) and lexicon form a continuum (Langacker 1987: 18–19), since I show that metonymic relationships in the two domains can be described in nearly identical terms. While many metonymic relationships are shared across the lexical and grammatical domains, some are specific to only one domain, and the two domains show different preferences for source and target concepts. Furthermore, I find that the range of metonymic relationships expressed in word-formation is more diverse than what has been found in lexical metonymy. There is remarkable similarity in word-formational metonymy across the three languages, despite their typological differences, though they all show some degree of language-specific behavior as well. Although this study is limited to three Indo-European languages, the goal is to create a classification system that could be implemented (perhaps with modifications) across a wider spectrum of languages.
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