Damián E. Blasi’s research while affiliated with Pompeu Fabra University and other places

When speakers of different languages are in contact, they often borrow features like sounds, words, or syntactic patterns from one language to the other, but the lack of historical data has hampered estimation of this effect at a global scale. We break out of this impasse by using genetic admixture as a proxy for population contact. We find that language pairs whose speaker populations underwent genetic admixture or that are located in the same geo-historical area share more features than others, suggesting borrowing. The effect varies strongly across features, partly following expectations from differences in lifelong learnability, partly responding to differences in social imbalances during contact. Additionally, we find that for some features, admixture decreases sharing. This likely reflects signals of divergence (schismogenesis) under contact.

The evolution of music, language, and cooperation have been debated since before Darwin. The social bonding hypothesis proposes that these phenomena may be interlinked: musicality may have facilitated the evolution of group cooperation beyond the possibilities of spoken language. Although dozens of experimental studies have shown that synchronised rhythms can promote cooperation, it is unclear whether synchronous singing enhances cooperation relative to spoken language, particularly across diverse societies that differ in their musical/linguistic rhythms and social organisation. Here, we propose a Registered Report to test this hypothesis through a global experiment in diverse languages aiming to collect data from 1500 participants across 50 sites. The social bonding hypothesis predicts that cooperation will increase more after synchronous singing than after spoken (sequential) conversation or (simultaneous) recitation, while alternative hypotheses predict that song will not increase cooperation relative to speech. Regardless of outcome, these results will provide an unprecedented understanding of cross-cultural relationships between music, language, and cooperation.

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.

Grammars Across Time Analyzed (GATA) is a resource capturing two snapshots of the grammatical structure of a diverse range of languages separated in time, aimed at furthering research on historical linguistics, language evolution, and cultural change. GATA comprises grammatical information on 52 diverse languages across all continents, featuring morphological, syntactic, and phonological information based on published grammars of the same language at two different time points. Here we introduce the coding scheme and design features of GATA, and we describe some salient patterns related to language change and the coverage of grammatical descriptions over time.

Large language models (LLMs) have recently made vast advances in both generating and analyzing textual data. Technical reports often compare LLMs’ outputs with “human” performance on various tests. Here, we ask, “Which humans?” Much of the existing literature largely ignores the fact that humans are a cultural species with substantial psychological diversity around the globe that is not fully captured by the textual data on which current LLMs have been trained. We show that LLMs’ responses to psychological measures are an outlier compared with large-scale cross-cultural data, and that their performance on cognitive psychological tasks most resembles that of people from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies but declines rapidly as we move away from these populations (r = -.70). Ignoring cross-cultural diversity in both human and machine psychology raises numerous scientific and ethical issues. We close by discussing ways to mitigate the WEIRD bias in future generations of generative language models.

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.

In the field of neurodegeneration, speech and language assessments are useful for diagnosing aphasic syndromes and for characterizing other disorders. As a complement to classic tests, scalable and low-cost digital tools can capture relevant anomalies automatically, potentially supporting the quest for globally equitable markers of brain health. However, this promise remains unfulfilled due to limited linguistic diversity in scientific works and clinical instruments. Here we argue for cross-linguistic research as a core strategy to counter this problem. First, we survey the contributions of linguistic assessments in the study of primary progressive aphasia and the three most prevalent neurodegenerative disorders worldwide –Alzheimer’s disease, Parkinson’s disease, and behavioral variant frontotemporal dementia. Second, we address two forms of linguistic unfairness in the literature: the neglect of most of the world’s 7,000 languages and the preponderance of English-speaking cohorts. Third, we review studies showing that linguistic dysfunctions in a given disorder may vary depending on the patient’s language and that English speakers offer a suboptimal benchmark for other language groups. Finally, we highlight different approaches, tools, and initiatives for cross-linguistic research, identifying core challenges for their deployment. Overall, we seek to inspire timely actions to counter a looming source of inequity in behavioral neurology.