Innateness and culture in the evolution of language

By Simon Kirby, Mike Dowman, T. Griffiths. Proceedings of the National Academy of Sciences of the United States of America, 2006

420 citations recorded by the source corpus.

Subfields: Cultural Studies

View Paper: https://www.semanticscholar.org/paper/b24aa58f695e103f5630a382e55bad9c84dd466e

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In Cultural Studies

Citations in the corpus

Cumulative cultural evolution in the laboratory: An experimental approach to the origins of structure in human language (2008, background): “Models of this process (4-13) demonstrate that, over repeated episodes of transmission, behaviours transmitted by iterated learning tend to: 1.”
Iterated learning and the evolution of language. (2014, background): “[34] S.”
Universal cognitive mechanisms explain the cultural success of bloodletting (2015, background): “Modeling bypasses experimental limitations and provides a more accurate representation of the consequences of even weak biases on cultural evolution (Boyd & Richerson, 1985; Kalish et al., 2007; Kirby, Dowman, & Griffiths, 2007; Richerson & Boyd, 2005).”
Three decades of cultural evolution in Savannah sparrow songs (2013, background): “Even weak biases that favour regularity in human language can give rise to strong systematic rules favouring one grammatical form rather than two (Kirby et al. 2007; Reali & Griffiths 2010).”
Symbolic Inductive Bias for Visually Grounded Learning of Spoken Language (2018, background): “ to their innate inductive bias whereby they assume that language is symbolic. They presumably acquired such bias via the process of evolution by natural selection, or possibly by cultural evolution (Kirby et al., 2007). In the context of machine learning, inductive bias can instead be injected via ”
Dynamic Language Models for Continuously Evolving Content (2021, background): “Our world is changing, and so are our languages [1, 21].”
Cultural Evolution: A Review of Theory, Findings and Controversies (2015, methodology): “The same process has been modelled using a Bayesian framework, where cognitive (or ‘inductive’) biases form the priors that people use when making inferences about culturally acquired information (Griffiths et al. 2008; Kirby et al. 2007).”
Can Large Language Models Transform Computational Social Science? (2023, background): “Semantic change detection can serve as a proxy measure for the spread and change of culture (Kirby et al., 2007), both on the internet (Eisenstein, 2012; Eisenstein et al.”
Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift (2010, methodology): “In the context of language, Dirichlet priors have been recently used in models of iterated learning (Kirby et al. 2007) and language acquisition (Goldwater et al. 2009; Reali & Grifﬁths 2009).”
Language as shaped by the brain. (2008, background): “For example, Kirby et al. (2007) show that, if information is transmitted directly between individual learners, and learners sample grammars from the Bayes posterior distribution of grammars, given that information, then language asymptotically converges to match the priors initially encoded by the…”