Semantic types of morphological compounds occur with quantifiable cross-linguistic frequency distributions

More or Less Unnatural: Semantic Similarity Shapes the Learnability and Cross-Linguistic Distribution of Unnatural Syncretism in Morphological Paradigms. 2022. https://doi.org/10.1162/opmi_a_00062

Abstract Morphological systems often reuse the same forms in different functions, creating what is known as syncretism. While syncretism varies greatly, certain cross-linguistic tendencies are apparent. Patterns where all syncretic forms share a morphological feature value (e.g., first person, or plural number) are most common cross-linguistically, and this preference is mirrored in results from learning experiments. While this suggests a general bias towards natural (featurally homogeneous) over unnatural (featurally heterogeneous) patterns, little is yet known about gradients in learnability and distributions of different kinds of unnatural patterns. In this paper we assess apparent cross-linguistic asymmetries between different types of unnatural patterns in person-number verbal agreement paradigms and test their learnability in an artificial language learning experiment. We find that the cross-linguistic recurrence of unnatural patterns of syncretism in person-number paradigms is proportional to the amount of shared feature values (i.e., semantic similarity) amongst the syncretic forms. Our experimental results further suggest that the learnability of syncretic patterns also mirrors the paradigm’s degree of feature-value similarity. We propose that this gradient in learnability reflects a general bias towards similarity-based structure in morphological learning, which previous literature has shown to play a crucial role in word learning as well as in category and concept learning more generally. Rather than a dichotomous natural/unnatural distinction, our results thus support a more nuanced view of (un)naturalness in morphological paradigms and suggest that a preference for similarity-based structure during language learning might shape the worldwide transmission and typological distribution of patterns of syncretism. 4077 opmi Open Mind : Discoveries in Cognitive Science Open Mind (Camb) MIT Press PMC9692061 9692061 9692061 36439066 10.1162/opmi_a_00062 More or Less Unnatural: Semantic Similarity Shapes the Learnability and Cross-Linguistic Distribution of Unnatural Syncretism in Morphological Paradigms Saldana Carmen 1 2 * † Herce Borja 1 2 † Bickel Balthasar 1 2 1 Department of Comparative Linguistics, University of Zurich, Zurich, Switzerland 2 Center for the Interdisciplinary Study of Language Evolution, University of Zurich, Zurich, Switzerland Competing Interests: The authors declare no conflict of interest. While syncretism varies greatly, certain cross-linguistic tendencies are apparent. Patterns where all syncretic forms share a morphological feature value (e.g., first person, or plural number) are most common cross-linguistically, and this preference is mirrored in results from learning experiments. While this suggests a general bias towards natural (featurally homogeneous) over unnatural (featurally heterogeneous) patterns, little is yet known about gradients in learnability and distributions of different kinds of unnatural patterns. In this paper we assess apparent cross-linguistic asymmetries between different types of unnatural patterns in person-number verbal agreement paradigms and test their learnability in an artificial language learning experiment. We find that the Keywords: artificial language learning, typology, syncretism, natural class, morphological paradigm, semantic similarity status released display-pdf yes is-olf no is-manuscript no is-preprint no is-journal-matter no is-scanned no is-retracted no Received 2021 Aug 17; Accepted 2022 Aug 28; Collection date 2022. INTRODUCTION Morphological paradigms display astonishing variation cross-linguistically. Languages vary in the type and number of morphosyntactic categories they express, as well as in the way and regularity in which these categories are marked within and across paradigms. These results add to the growing body of work using experimental methods to investigate how a bias during learning replicates biases in the transmission of morphological patterns, which in turn shape their cross-linguistic distributions over time (e.g., Fedzechkina et al., 2012 ; Hupp et al., 2009 ; Johnson et al., 2021 ; Maldonado & Culbertson, 2022 ; Maldonado et al., 2020 ; Martin & Culbertson, 2020 ; Saldana et al., 2021b ). However, before we present the experimental study, in the following section we survey the cross-linguistic evidence for the predicted asymmetry (L-type > X-type) in the recurrence of unnatural patterns of whole-word syncretism as well as unnatural patterns of shared morphology more broadly (i.e., including both whole-word and partial syncretisms). THE TYPOLOGY OF UNNATURAL PATTERNS OF SYNCRETISM There is a long tradition in theoretical morphology to disregard or “analyse away” unnatural morphological patterns (Harbour, 2008 ). Grouping these recurrent unnatural patterns with other rarer or unnatested unnatural ones might be therefore problematic; a more nuanced account of the natural-unnatural distinction than often assumed in morphological theory might instead be required (Bickel, 1995 ; Herce, 2020b ). Evidence in favour of reconsidering the spectrum of (un)naturalness should thus come from the prevalence of different types of natural and unnatural morphological patterns. In the next section we survey the available cross-linguistic data for a more in-depth exploration of the recurrence of unnatural patterns. We found cross-linguistic evidence consistent with the frequency hierarchy natural ≫ L-type unnatural > X-type unnatural. Further, our experimental results provide evidence for a learnability gradient consistent with the typology: Natural patterns are the easiest to learn, and L-type unnatural patterns are easier to learn than X-type unnatural patterns. We propose that this gradient in learnability reflects a general bias towards similarity-based structure in morphological learning, which can also be found in word learning as well as in category and concept learning more generally.