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https://www.philsoc.org.uk///media/2021/01/TPhS-TALK-Abstract.pdf

This paper examines the division of labour between phonology and morphology in the stem allomorphy of two typologically different languages, Amuzgo (Oto-Manguean) and Finnish (Uralic). Both exhibit complex systems of stem-consonant alternations that, depending on the specific consonant and/or lexical item involved, run the gamut from phonologically transparent to apparently arbitrary in identical morphological contexts. By factoring out productive phonological processes, we can establish a lexical continuum from single underlying stems, to stem allomorphs connected by unproductive phonological rules, to stem-allomorph sets whose relationships cannot be mapped by conventional formal operations of phonology. For Amuzgo noun plurals, the identification of purely phonological processes reduces the patterns to a core of n- prefixation plus the alternations ? ~ k and ts/t?/w ~ Ø. I discuss the extent to which these quasi-phonological alternations can be understood theoretically in terms of abstract scales (Mortensen 2006). In Finnish verbs, there are many classes of exceptions (some surface, some deeper) to the basic phonological conditions on consonant gradation, along with parallels to other stem alternations that fall outside the gradation system. For these cases, I adopt the stratal framework of Bermúdez-Otero (2012, 2013), in particular the twin mechanisms of stem storage and lexical redundancy rules, to capture generalizations without placing disproportionate burden on either the phonology or the lexicon.

What predicts productivity? Theory meets individuals 

Because they involve individual-level cognitive processes, psychological explanations of linguistic phenomena are in principle testable against individual behaviour. The present study draws on patterns of individual variation in corpus data to test explanations of productivity. Linguistic patterns are predicted to become more productive with higher type frequencies and lower token frequencies. This is because the formation of abstract mental representations is encouraged by varied types but counteracted by automation of high-frequency types. The predictions are tested for English -ly and -ness-derivation, as used by 698 individual journalists in the New York Times Annotated Corpus and 171 members of Parliament in the Hansard Corpus. Linear regression is used to model individual variation in productivity, in relation to type and token frequency, as well as several other predictor variables. While the expected effects are observed, there is also robust evidence of an interaction effect between type and token frequency, indicating that productivity is highest for patterns with many types and not-too-infrequent tokens. This fits best with a view of entrenchment as both a conservative and creative force in language. Further, some variation remains irreducibly individual and is not explained by currently known predictors of productivity.