From the field into the lab: causal approaches to the evolution of spatial language

Abstract

Striking variation exists in preferences for specific spatial linguistic strategies among different speech communities. Increasing evidence now suggests that this might not simply be a result of neutral drift, but rather a form of linguistic adaptation to the local social, cultural, or physical environment. Recent studies indicate that different factors like topography, subsistence style, and bilingualism successfully predict the choice of spatial frames of reference (FoR) on linguistic and non-linguistic tasks. However, the exact causal relationships between these variables and the cultural evolutionary mechanisms behind the selection of one FoR strategy over another are still not fully understood. In this paper, we argue that to arrive at a more mechanistic and causal understanding of the cultural evolution of spatial language, observations from descriptive fieldwork should be combined with experimental and computational methods. In the framework we present, causal relationships between linguistic and non-linguistic variables (such as FoR choice and topography) can be isolated and systematically tested in order to shed light on how sociotopographic factors motivate the variation in spatial language we observe cross-linguistically. We discuss experimental results from behavioral studies and computer simulations that illustrate how this approach can deliver empirical findings that go beyond simple correlations.

Virtual Reality: A tool to study language evolution

“…However, such cross-sectional studies often face criticism for their primarily correlational nature and lack of control for cultural evolution, which can confound data points (Roberts & Winters, 2013). More recently, scholars have argued that robust, causal models of how external variables shape language require an integration of findings with methods that can directly test hypotheses, such as fieldwork, experiments, and computational models (Roberts, 2018;Raviv et al, 2019;Nölle & Spranger, 2022). For instance, Roberts (2018) suggests that a causal model of the relationship between humidity and tone necessitates converging evidence from laboratory phonetics, iterated learning experiments, corpus studies, and historical case studies.…”

“…Majid et al, 2004). However, one challenge is that these sociotopographic factors often intertwine and are difficult to disentangle (Nölle & Spranger, 2022). For instance, in Marshallese and Dhivehi, topography's influence appears to be modulated by other factors.…”

Temperature shapes language sonority: Revalidation from a large dataset

“…In recent decades, linguistics research has witnessed a shift towards the use of large-scale datasets. Studies have emerged that explore methods to investigate language adaptation employing big data and computer simulations ( 31 , 32 ). In this study, we utilized vocabulary lists of basic words of 9,179 language varieties from the Automated Similarity Judgment Program (ASJP) database ( 33 ) as our source for exploring the effect of temperature on sonority.…”