Contact-tracing in cultural evolution: a Bayesian mixture model to detect geographic areas of language contact

Euclide, the crow, the wolf and the pedestrian: distance metrics for linguistic typology

It is common for people working on linguistic geography, language contact and typology to make use of some type of distance metric between lects. However, most work so far has either used Euclidean distances, or geodesic distance, both of which do not represent the real separation between communities very accurately. This paper presents two datasets: one on walking distances and one on topographic distances between over 8700 lects across all macro-areas. We calculated walking distances using Open Street Maps data, and topographic distances using digital elevation data. We evaluate these distance metrics on three case studies and show that from the four distances, the topographic and geodesic distances showed the most consistent performance across datasets, and would be likely to be reasonable first choices. At the same time, in most cases, the Euclidean distances were not much worse than the other distances, and might be a good enough approximation in cases for which performance is critical, or the dataset cover very large areas, and the point-location information is not very precise.

Gaussian process models for geographic controls in phylogenetic trees

Geographical confounding in phylogenetic inference models has long been an issue. Often models have great difficulty detecting whether congruences or similarities between languages in phylogenetic datasets stem from common genetic descent or geographical proximity effects such as language contact. In this study, we introduce a distance-based Gaussian process approach with latent phylogenetic distances that can detect potential geographic contact zones and subsequently account for geospatial biases in the resulting tree topologies. We find that this approach is able to determine potential high-contact areas, making it possible to calculate the strength of this influence on both the tree-level (clade support) and the language-level (pairwise distances).

The social lives of isolates (and small language families): the case of the Northwest Amazon

The Americas are home to patches of extraordinary linguistic (genealogical) diversity. These high-diversity areas are particularly unexpected given the recent population of the Americas. In this paper, we zoom in on one such area, the Northwest Amazon, and address the question of how the diversity in this area has persisted to the present. We contrast two hypotheses that claim opposite mechanisms for the maintenance of diversity: the isolation hypothesis suggests that isolation facilitates the preservation of diversity, while the integration hypothesis proposes that conscious identity preservation in combination with contact drives diversity maintenance. We test predictions for both hypotheses across four disciplines: biogeography, cultural anthropology, population genetics and linguistics. Our results show signs of both isolation and integration, but they mainly suggest considerable diversity in how groups of speakers have interacted with their surroundings.

Spatial evolution of human cultures inferred through Bayesian phylogenetic analysis

Spatial distribution of human culture reflects both descent from the common ancestor and horizontal transmission among neighbouring populations. To analyse empirically documented geographical variations in cultural repertoire, we will describe a framework for Bayesian statistics in a spatially explicit model. To consider both horizontal transmission and mutation of the cultural trait in question, our method employs a network model in which populations are represented by nodes. Using algorithms borrowed from Bayesian phylogenetic analysis, we will perform a Markov chain Monte Carlo (MCMC) method to compute the posterior distributions of parameters, such as the rate of horizontal transmission and the mutation rates among trait variants, as well as the identity of trait variants in unobserved populations. Besides the inference of model parameters, our method enables the reconstruction of the genealogical tree of the focal trait, provided that the mutation rate is sufficiently small. We will also describe a heuristic algorithm to reduce the dimension of the parameter space explored in the MCMC method, where we simulate the coalescent process in the network of populations. Numerical examples show that our algorithms compute the posterior distribution of model parameters within a practical computation time, although the posterior distribution tends to be broad if we use uninformative priors.

Claude Lévi-Strauss as a humanist forerunner of cultural macroevolution studies

Cross-cultural studies of humans using methods developed in evolutionary biology and comparative linguistics are flourishing. 'Cultural macroevolution' has great potential to address fundamental questions of cultural transformation and human history. However, this field is poorly integrated with core cultural anthropology, although both aim in part at addressing similar issues. Claude Lévi-Strauss established a comparative approach searching for universals and documentation of diversity to bring understanding to cultural phenomena. Recognizing the nomothetic nature of Lévi-Strauss' work, his abstraction and modelling, provides an example within anthropology of the search for universals and the study of big data, akin to cultural macroevolution studies. The latter could benefit, beyond the sophisticated analyses of big data mined from ethnographic work, from the integration with the intellectual legacy and practice of core anthropology and thus propitiate the synergistic interaction of disciplines. Attempts at rapprochement of disciplines from the natural sciences that lack pluralism and present a narrow view are deemed examples of 'Wilson's effect'.

Lexibank, a public repository of standardized wordlists with computed phonological and lexical features

The past decades have seen substantial growth in digital data on the world’s languages. At the same time, the demand for cross-linguistic datasets has been increasing, as witnessed by numerous studies devoted to diverse questions on human prehistory, cultural evolution, and human cognition. Unfortunately, most published datasets lack standardization which makes their comparison difficult. Here, we present a new approach to increase the comparability of cross-linguistic lexical data. We have designed workflows for the computer-assisted lifting of datasets to Cross-Linguistic Data Formats, a collection of standards that make these datasets more Findable, Accessible, Interoperable, and Reusable (FAIR). We test the Lexibank workflow on 100 lexical datasets from which we derive an aggregated database of wordlists in unified phonetic transcriptions covering more than 2000 language varieties. We illustrate the benefits of our approach by showing how phonological and lexical features can be automatically inferred, complementing and expanding existing cross-linguistic datasets.

Measurement(s)	expressions
Technology Type(s)	data aggregation
Factor Type(s)	none
Sample Characteristic - Organism	human language
Sample Characteristic - Location	global scale