Phylogenetic Typology

Jäger, Gerhard; Wahle, Johannes

doi:10.3389/fpsyg.2021.682132

Cited by 19 publications

(25 citation statements)

References 35 publications

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“…Thirdly, in quantitative diachronic typology, it is necessary to work with cross-family data. Hence, typologists have employed unified approaches using the same setup for different families, or even hierarchical models connected by shared hyperpriors [54,55]. However, for lexical data, individual language families are often studied by separate groups of researchers with different model details and there is little indication that models are re-used and compared between different language families; this article seems to be the first such study.…”

Section: Discussionmentioning

confidence: 99%

Clocks with bursts: Phylogenetic inference of schismogenesis in language evolution

Kaiping¹,

Neureiter²

2022

Preprint

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Dated language phylogenies have wide applications in historical and anthropological research. However, the quality of such applications depends on adequate models of language evolution. When a language splits into different speaker communities, the speed of language change increases such that a significant proportion of lexical disparity can be attributed to the splitting events. This could be explained by “schismogenesis”, i. e. the exaggeration of language differences to mark social boundaries. Surprisingly, this result has not found its way back into the clock models used in phylogenetic inference. Here, we develop an extension to existing phylogenetic clock models in BEAST2 to account for bursts at language splits. We validate the mode in a simulation studies and fit it to four major language families ofthe world: Austronesian, Bantu, Indo-European, and Sino-Tibetan. In each of the four families the burst clock model fits the data significantly better than a strict or relaxed clock without bursts. Astonishingly, the estimated bursts lead to changes equivalent to about 100 years of independent evolution. This makes bursts at splits a major contribution to language evolution, and our model may even be applicable to some cases of biological evolution.

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Section: Discussionmentioning

confidence: 99%

Clocks with bursts: Phylogenetic inference of schismogenesis in language evolution

Kaiping¹,

Neureiter²

2022

Preprint

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“…Since Greenberg's seminal work, a number of studies have provided empirical evidence for crosscategory harmony (e.g., Hawkins, 1983;Dryer, 1992;Jäger and Wahle, 2021). For example, Dryer (1992) investigated whether the tendency of cross-category harmony observed in Greenberg (1963) holds for a larger sample of more than 600 languages.…”

Section: Typological Evidence For Cross-category Harmonymentioning

confidence: 99%

“…However, Dryer's (1992) method for controlling relationships among languages remains potentially problematic. For example, the results might be biased by the assumptions of the genetic relations of languages in the sample (see Dunn et al, 2011, Ladd, Roberts, and Dediu, 2015, Jäger and Wahle, 2021. To mitigate the effects of data independence in language samples, Bayesian phylogenetic methods have recently been used to re-evaluate the word order correlations observed in typology.…”

Section: Typological Evidence For Cross-category Harmonymentioning

confidence: 99%

The learning bias for cross-category harmony is sensitive to semantic similarity: Evidence from artificial language learning experiments

Wang¹,

Kirby²,

Culbertson³

2023

Preprint

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Cross-category harmony is one of the most well-known typological universals. It describes the tendency for syntactic heads to be ordered consistently relative to their dependents across different phrase types. Explanations for this universal vary as to whether cognitive factors play a role, or instead the tendency is due to mechanisms of language change alone. In this paper we report a series of artificial language learning experiments that aim to test a hypothesized link between cognition and cross-category harmony. As with the typological tendency itself, we find mixed evidence for harmony across different types of phrases. Specifically, learners are biased in favor of harmony between the order of verb and object and the order of adposition and noun. However, the bias for harmony between the order of verb and object and the order of adjective and noun depends on the semantic similarity between adjectives and verbs. When adjectives are active and therefore more verb-like (e.g., ‘broken'), we find harmony; when they are stative and therefore less verb-like (e.g., ‘blue'), we do not. These results suggest that the bias for cross-category harmony is not purely based on the syntactic notions of head and dependent, but reflects the interaction between a general cognitive bias for simplicity and cross-category similarity (Culbertson and Kirby, 2016; Culbertson and Kirby, 2022).

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“…It remains an open question in which ways a similarity-based structure bias operates over time and space in the transmission and emergence of L and X unnatural patterns crosslinguistically. To probe this further, phylogenetic modelling is needed that compares the transition preferences across patterns in a wide range of language families and under different conditions of language contact (Bickel, 2015;Cathcart, 2018;Cysouw, 2011;Greenhill, Heggarty, & Gray, 2020;Jäger & Wahle, 2021).…”

Section: Diachronic Change In Unnatural Patternsmentioning

confidence: 99%

More or Less Unnatural: Semantic Similarity Shapes the Learnability and Cross-Linguistic Distribution of Unnatural Syncretism in Morphological Paradigms

Saldana¹,

Herce²,

Bickel³

2022

Preprint

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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., 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.

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Phylogenetic Typology

Cited by 19 publications

References 35 publications

Clocks with bursts: Phylogenetic inference of schismogenesis in language evolution

Clocks with bursts: Phylogenetic inference of schismogenesis in language evolution

The learning bias for cross-category harmony is sensitive to semantic similarity: Evidence from artificial language learning experiments

More or Less Unnatural: Semantic Similarity Shapes the Learnability and Cross-Linguistic Distribution of Unnatural Syncretism in Morphological Paradigms

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