Inductive evolution: cognition, culture, and regularity in language
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Date
30/06/2015Author
Ferdinand, Vanessa Anne
Metadata
Abstract
Cultural artifacts, such as language, survive and replicate by passing from mind
to mind. Cultural evolution always proceeds by an inductive process, where behaviors
are never directly copied, but reverse engineered by the cognitive mechanisms
involved in learning and production. I will refer to this type of evolutionary
change as inductive evolution and explain how this represents a broader class of
evolutionary processes that can include both neutral and selective evolution.
This thesis takes a mechanistic approach to understanding the forces of evolution
underlying change in culture over time, where the mechanisms of change
are sought within human cognition. I define culture as anything that replicates
by passing through a cognitive system and take language as a premier example of
culture, because of the wealth of knowledge about linguistic behaviors (external
language) and its cognitive processing mechanisms (internal language). Mainstream
cultural evolution theories related to social learning and social transmission
of information define culture ideationally, as the subset of socially-acquired
information in cognition that affects behaviors. Their goal is to explain behaviors
with culture and avoid circularity by defining behaviors as markedly not part of
culture. I take a reductionistic approach and argue that all there is to culture
is brain states and behaviors, and further, that a complete explanation of the
forces of cultural change can not be explained by a subset of cognition related
to social learning, but necessarily involves domain-general mechanisms, because
cognition is an integrated system. Such an approach should decompose culture
into its constituent parts and explore 1) how brains states effect behavior, 2) how
behavior effects brain states, and 3) how brain states and behaviors change over
time when they are linked up in a process of cultural transmission, where one
person's behavior is the input to another.
I conduct several psychological experiments on frequency learning with adult
learners and describe the behavioral biases that alter the frequencies of linguistic
variants over time. I also fit probabilistic models of cognition to participant data
to understand the inductive biases at play during linguistic frequency learning.
Using these inductive and behavioral biases, I infer a Markov model over my empirical
data to extrapolate participants' behavior forward in cultural evolutionary
time and determine equivalences (and divergences) between inductive evolution
and standard models from population genetics. As a key divergence point, I introduce
the concept of non-binomial cultural drift, argue that this is a rampant
form of neutral evolution in culture, and empirically demonstrate that probability
matching is one such inductive mechanism that results in non-binomial cultural
drift. I argue further that all inductive problems involving representativeness are
potential drivers of neutral evolution unique to cultural systems. I also explore
deviations from probability matching and describe non-neutral evolution due to
inductive regularization biases in a linguistic and non-linguistic domain. Here,
I offer a new take on an old debate about the domain-specificity vs -generality
of the cognitive mechanisms involved in language processing, and show that the
evolution of regularity in language cannot be predicted in isolation from the general
cognitive mechanisms involved in frequency learning. Using my empirical
data on regularization vs probability matching, I demonstrate how the use of appropriate
non-binomial null hypotheses offers us greater precision in determining
the strength of selective forces in cultural evolution.
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