The evolutionary dynamics of how languages signal who does what to whom.

Languages vary in how they signal "who does what to whom". Three main strategies to indicate the participant roles of "who" and "whom" are case, verbal indexing, and rigid word order. Languages that disambiguate these roles with case tend to have either verb-final or flexible word order. Most previous studies that found these patterns used limited language samples and overlooked the causal mechanisms that could jointly explain the association between all three features. Here we analyze grammatical data from a Grambank sample of 1705 languages with phylogenetic causal graph methods. Our results corroborate the claims that verb-final word order generally gives rise to case and, strikingly, establish that case tends to lead to the development of flexible word order. The combination of novel statistical methods and the Grambank database provides a model for the rigorous testing of causal claims about the factors that shape patterns of linguistic diversity.

Societies of strangers do not speak less complex languages.

Many recent proposals claim that languages adapt to their environments. The linguistic niche hypothesis claims that languages with numerous native speakers and substantial proportions of nonnative speakers (societies of strangers) tend to lose grammatical distinctions. In contrast, languages in small, isolated communities should maintain or expand their grammatical markers. Here, we test these claims using a global dataset of grammatical structures, Grambank. We model the impact of the number of native speakers, the proportion of nonnative speakers, the number of linguistic neighbors, and the status of a language on grammatical complexity while controlling for spatial and phylogenetic autocorrelation. We deconstruct "grammatical complexity" into two separate dimensions: how much morphology a language has ("fusion") and the amount of information obligatorily encoded in the grammar ("informativity"). We find several instances of weak positive associations but no inverse correlations between grammatical complexity and sociodemographic factors. Our findings cast doubt on the widespread claim that grammatical complexity is shaped by the sociolinguistic environment.

Grambank reveals the importance of genealogical constraints on linguistic diversity and highlights the impact of language loss.

While global patterns of human genetic diversity are increasingly well characterized, the diversity of human languages remains less systematically described. Here, we outline the Grambank database. With over 400,000 data points and 2400 languages, Grambank is the largest comparative grammatical database available. The comprehensiveness of Grambank allows us to quantify the relative effects of genealogical inheritance and geographic proximity on the structural diversity of the world's languages, evaluate constraints on linguistic diversity, and identify the world's most unusual languages. An analysis of the consequences of language loss reveals that the reduction in diversity will be strikingly uneven across the major linguistic regions of the world. Without sustained efforts to document and revitalize endangered languages, our linguistic window into human history, cognition, and culture will be seriously fragmented.

Global predictors of language endangerment and the future of linguistic diversity.

Language diversity is under threat. While each language is subject to specific social, demographic and political pressures, there may also be common threatening processes. We use an analysis of 6,511 spoken languages with 51 predictor variables spanning aspects of population, documentation, legal recognition, education policy, socioeconomic indicators and environmental features to show that, counter to common perception, contact with other languages per se is not a driver of language loss. However, greater road density, which may encourage population movement, is associated with increased endangerment. Higher average years of schooling is also associated with greater endangerment, evidence that formal education can contribute to loss of language diversity. Without intervention, language loss could triple within 40 years, with at least one language lost per month. To avoid the loss of over 1,500 languages by the end of the century, urgent investment is needed in language documentation, bilingual education programmes and other community-based programmes.

Why are some languages confused for others? Investigating data from the Great Language Game.

In this paper we explore the results of a large-scale online game called 'the Great Language Game', in which people listen to an audio speech sample and make a forced-choice guess about the identity of the language from 2 or more alternatives. The data include 15 million guesses from 400 audio recordings of 78 languages. We investigate which languages are confused for which in the game, and if this correlates with the similarities that linguists identify between languages. This includes shared lexical items, similar sound inventories and established historical relationships. Our findings are, as expected, that players are more likely to confuse two languages that are objectively more similar. We also investigate factors that may affect players' ability to accurately select the target language, such as how many people speak the language, how often the language is mentioned in written materials and the economic power of the target language community. We see that non-linguistic factors affect players' ability to accurately identify the target. For example, languages with wider 'global reach' are more often identified correctly. This suggests that both linguistic and cultural knowledge influence the perception and recognition of languages and their similarity.