Vanessa Ferdinand

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Language learners tend to regularize unpredictable variation and some claim that is due to a language-specific regularization bias. We investigate the role of task difficulty on regularization behavior in a non-linguistic frequency learning task and show that adults regularize variable input when tracking multiple frequencies concurrently, but reliably(More)
Regularization occurs when the output a learner produces is less variable than the linguistic data they observed. In an artificial language learning experiment, we show that there exist at least two independent sources of regularization bias in cognition: a domain-general source based on cognitive load and a domain-specific source triggered by linguistic(More)
What is the mechanism that translates the individual properties of learners into the properties of the language they speak? This paper will investigate cultural transmission as this mechanism and will take up the Iterated Learning Model as a formal framework in which to address this claim. This model describes language as a special learning problem, where(More)
Pathogens can spread epidemically through populations. Beneficial contagions, such as viruses that enhance host survival or technological innovations that improve quality of life, also have the potential to spread epidemically. How do the dynamics of beneficial biological and social epidemics differ from those of detrimental epidemics? We investigate this(More)
Through the use of an iterated learning experiment, we investigate the emergence of self-organised structure in a random initial alien language, as it is replicated through successive `generations' of language learners in three distinct iteration chains. Experiments in the iterated learning paradigm have frequently shown that languages evolve to become more(More)
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