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Biology subjects

Cathcart, C. A.

Publications and source records attributed to Cathcart, C. A..

3 recordsLinked to original sources

Evolutionary dynamics of maximal syllable complexity show no universal bias rooted in jaw biomechanics

Linguistic evolution has given rise to variation in the degree of syllable complexity that any given language permits. However, several models of language converge in predicting a universal bias towards the consonant-vowel (CV) structure (or a broader strong-weak asymmetry). This is closely tied to incremental speech processing, and in evolutionary terms has been linked to certain rhythmic orofacial displays in non-human primates. Yet, whether linguistic evolution really reflects such a universal tendency is an open question, one that we aim to address using phylogenetic comparative methods. Modeling change according to a continuous-time Markov process, we estimate transition rates for maximal onset and coda sizes (i.e. grammatical rules) across 5 language families. We demonstrate that a lineage-specific model outperforms a global model, and further explore the nature of lineage-specific long-term preferences and rates of change on multiple levels. We show that the former drive inter-family variation more than the latter. Generally, particulars turn out to impact syllable complexity more than any universal biomechanically or neurocognitively motivated biases do, implying that evolutionary continuity with our primate ancestors may have been overstated for this domain of language.

evolutionary biology↗

Linguistic evolution minimizes the amount of syntactic hierarchy in grammar

A core characteristic of language is the capacity for hierarchical syntax, but it remains debated to what extent languages favor hierarchical structure in their grammars, that is, the extent to which they favor hierarchical structures like "When driving, look ahead!" over concatenations like "You drive, you look ahead!". Through phylogenetic modeling of the grammars of clause combining in three extensive language families (Tupi-Guarani, Sino-Tibetan, and Indo-European), we find an overall bias towards minimizing hierarchy, with significant cultural variation. Our findings suggest that the computational and representational benefits of hierarchical structure tend not to be universally exploited in clause combinations, likely because they come with additional costs for learning. In consequence, the amount of hierarchy in language might differ from what is found in animal communication in a more graded way than commonly assumed.

evolutionary biology↗

Writing does not Impact the Evolution of Syntax

The acquisition of writing has a lasting effect on how languages are processed in the brain, raising the possibility that it also affects how they are used and evolve over time. A popular hypothesis is that writing specifically leads to increased use and evolution of complex hierarchical structures in language. While most case studies on individual languages have supported this, it remains unclear whether results scale to larger and more diverse sets of languages. Here we test the prediction for language use by modeling hierarchy depth and sentence length in Universal Dependencies corpora from 30 languages, and the prediction for language evolution by modeling the phylogenetic dynamics of structural asymmetry in clause combinations of 59 languages from three families. We found no effect of writing in either analysis. Hierarchy depth and sentence length do not demonstrably differ between spoken and written use of language, and the introduction of writing had no discernible effect on the evolution of clause combining in grammar. There is weak evidence for a decrease in variance after the introduction of writing in one family, possibly reflecting the impact of increased normativity. In conclusion, our findings challenge popular beliefs about hierarchy and suggest that the evolution of syntax is more driven by culturally variable ideas about style in linguistic expression than by the evolution of writing.

evolutionary biology↗