Identity Avoidance in Turkish Partial Reduplication: Feature Specificity and Locality

Abstract

This study investigates the Turkish partial reduplication phenomenon, in which the reduplicant is derived by prefixing C1_V_C2 syllable, where C1_V are identical to the word-initial CV of the base and the reduplicant C2 ends in one of the four consonants: -p, -m, -s, -r, known as linking consonants. This study re-examines the factors conditioning the choice of the linking consonant, by focusing the nature of the (dis)similarity (feature specificity) and the proximity (locality) between the consonants in the base and the linking consonant, using an acceptability rating task with over 200 participants. Results indicate that the identity avoidance effect extends over all consonants in the base (contra many previous studies). Crucially, the effect of all consonants is not uniform but linear, with the strength of the effect decreasing further into the base. The study also uncovers an elusive interplay between the distance-based decay effect and the syllable position effect, both of which turn out to play a role. In terms of the nature of feature specificity, results indicate that identity avoidance operates over both individual features as well as whole segments. Additionally, in line with findings in cross-linguistic typology, features do not participate equally in identity avoidance processes, with some being more influential than others. Overall, the study increases our understanding of the nature of both locality and feature specificity, and argues in favour of the view that locality-sensitive feature-specific identity avoidance constraints are part of the grammar.

Modelling L1 and the artificial language during artificial language learning

“…Linzen and Gallagher (2017) trained English speakers with the same number of artificial words containing identical and non-identical consonants. Natural language is likely to have fewer words containing identical consonants than those containing non-identical consonants (Graff & Jaeger, 2009; see references within Tang & Akkuş, 2022). Thus, the training set exhibited an overrepresentation of consonant identity nonwords relative to chance and this led speakers to be more likely to accept new items as part of the learned language if they conformed to the identity pattern.…”

“…Biases need more such experimental investigations as some of them are controversially discussed. There is a relative consensus about the complexity bias, which says that featurally simple phonological patterns are learned more easily than more complex patterns (Moreton & Pater, 2012b), while the substantive bias, a bias that favours phonetically motivated patterns (Baer-Henney et al, 2015;DeMille et al, 2018;Finley, 2012;Glewwe, 2019;Greenwood, 2016;Martin & White, 2021;Moreton & Pater, 2012a;Tang, DeMille, Frijters, & Gruen, 2020;Wilson, 2006) McMullin & Hansson, 2016;Tang & Akkuş, 2022;White et al, 2018), or the regularisation bias showing a preference for regular over irregular patterns (Fehér, Wonnacott, & Smith, 2016;Hudson Kam & Newport, 2005;Nevins, Rodrigues, & Tang, 2015;Samara, Smith, Brown, & Wonnacott, 2017;Smith et al, 2017;Smith & Wonnacott, 2010;Tang & Nevins, 2013). One essential problem to date is that most evidence for universal biases comes from investigations of only a few languages.…”