Language scholars speak of language contact to refer to all those situations where speakers of different languages (or different varieties of the same language) get to interact and, eventually, influence each other’s... [ view full abstract ]
Language scholars speak of language contact to refer to all those situations where speakers of different languages (or different varieties of the same language) get to interact and, eventually, influence each other’s linguistic behavior. Among the numerous social and linguistic implications of language contact, language shift is one of the most commonly observed phenomena. It can be defined as the process whereby, for a number of reasons, a community shifts to a speaking a language different from its own. As a matter of fact, close language contact and perceived lower status are often the cause of language decline and, eventually, language extinction. During the last decades governments implemented numerous policy interventions that attempted to stop or even revert language decline, with varying degrees of effectiveness. Often, the cause of failure was the presence of non-linguistic variables that were somehow related to the individual linguistic behavior but that were not tackled by the policy intervention and eventually played a major role in the decline process.
Language contact and its implication for regional and minority languages represent therefore a complex issue. The objective of this paper is to develop an agent-based model (ABM) that describes language dynamics as the result of complex interactions. ABMs allow to simulate all sorts of dynamics starting from the interactions within a system, in which new variables can be added, subtracted and modified to project different scenarios. These variables do not only represent standard information such as the number of individuals and their linguistic endowments and skills, but also situational conditions, such as social relations, people’s attitude towards difference, their propensity to pick up a new language, government intervention in the education system, and so on. Besides, ABM programming tools allow for calibrating the variables, which respond to – and with – different levels of intensity. As a consequence, ABMs can not only help sketch the current situation and its future dynamics, but also provide an idea of the scenarios to which different policy interventions can lead.
