Volume 29, Issue 3

Replication and replicability are fundamental tools to ensure that research results can be verified by an independent third party, reproducing the original study and ideally finding similar results. Yet, replication has not played a very important role in language typology so far, with most of the discussion around replication concerned with different types of language samples and sampling methods. This study addresses the issue of replication in typology in a different way. We use the original datasets of four previous typological studies (Berg 2020; Dryer 2018; Seržant 2021; Shcherbakova et al. 2023) to show how statistical modeling can be used to test methodological robustness in typology. We do so employing advanced statistical bias controls, namely phylogenetic regression for genetic effects and a Gaussian Process for contact effects. While we could replicate some of the original results, parts of our findings differed from the original ones, revealing important methodological insights. Our comparisons show that more advanced statistical techniques that can model the phylogenetic and contact relations between languages pick up more complex patterns in the data than traditional sampling methods, and they capture more of the real relations between languages and their effects on linguistic structure.

Linguistic complexity has generally been seen as influenced by ecological, demographic, and sociolinguistic factors and has been approached by seeking correlations of increased complexity along one linguistic dimension with one or another extralinguistic factor. Here we use a multidimensional definition of phonological complexity and analyze its global patterning quantitatively across predefined continents or sets of continents. We use linear and nonlinear regression models to estimate the gradient of geographical distributions of various complexity measures. We found significantly lower phonological complexity levels in South America and Australasia, suggesting isolation by distance (from centers of demographic and economic influence in the Old World). An unexpected finding is that our models show a broad transitional zone between the different levels of complexity in Africa and Europe. This Euro-African Transition Zone (ETZ) has its core between the Equator and the African coastline of the Mediterranean Sea. It has not been regarded as a language area before and is not a convergence area, but it has a robust geospatial complexity profile and we propose it as an area. We also find reasons to regard phonological complexity as a coherent property in itself, with its several dimensions behaving as a whole, and not as adaptive but as geospatially patterned. This paper is an exercise in using synchronic analysis of geolinguistic patterns of complexity to draw inferences about long-term change and evolutionary trends in language. On a higher level, the paper employs methods of geospatial analysis novel to this particular problem with the goal of raising new questions and laying groundwork for wider research into the distribution of linguistic complexity.