Earlier this month, the Yale Pama-Nyungan Lab’s Dr. Claire Bowern and Kevin Zhou published a paper titled “Quantifying uncertainty in the phylogenetics of Australian numeral systems” in the journal Proceedings of the Royal Society B. You can read the paper here.
Using Bayesian phylogenetic methods, Dr. Bowern and Zhou study and analyze the numeral systems of Pama-Nyungan languages in order to reconstruct how those systems may have looked thousands of years ago. What they discover is that the finite numeral systems of Pama-Nyungan languages change over time, losing and gaining numbers as they go. According to the authors, this demonstrates a potential for adaptability and flexibility in languages commonly stereotyped as simple, limited, and incapable of expressing new concepts. They also find that there is tremendous variation over time between the behavior of numeral systems limited at the number five and those with higher limits.
Here is the paper’s abstract:
Researchers have long been interested in the evolution of culture and the ways in which change in cultural systems can be reconstructed and tracked. Within the realm of language, these questions are increasingly investigated with Bayesian phylogenetic methods. However, such work in cultural phylogenetics could be improved by more explicit quantification of reconstruction and transition probabilities. We apply such methods to numerals in the languages of Australia. As a large phylogeny with almost universal ‘low-limit’ systems, Australian languages are ideal for investigating numeral change over time. We reconstruct the most likely extent of the system at the root and use that information to explore the ways numerals evolve. We show that these systems do not increment serially, but most commonly vary their upper limits between 3 and 5. While there is evidence for rapid system elaboration beyond the lower limits, languages lose numerals as well as gain them. We investigate the ways larger numerals build on smaller bases, and show that there is a general tendency to both gain and replace 4 by combining 2 + 2 (rather than inventing a new unanalysable word ‘four’). We develop a series of methods for quantifying and visualizing the results.