An agent-based model of sign language persistence informed by real-world data

What is it about?

In this article we aim to further our understanding of how sign languages persist. We study this by building an agent-based model (a type of modeling where individual people, or agents, of a community are represented and interact). Using this model, we investigate how sign language persistence is affected by a) the genetic transmission of deafness (modeled as a recessive trait), b) how the sign language is passed on from generation to generation, and c) marital patterns, in which deaf people may prefer marrying a deaf partner (or not). To inform the model, we use data from the sign language Kata Kolok to create a data-driven model of sign language persistence. We conclude that sign language persistence is affected by various factors: how the language is passed on from generation to generation, the proportion and spread of deafness in the community, the size of the population and marital patterns with regards to deafness.

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