From social learning to culture : mathematical and computational models of cultural evolution
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Humans are unique in the extent and complexity of their cultures. As a species, we generate extensive knowledge and innumerable norms, attitudes, traditions, skills, beliefs and technologies that we share with those around us through teaching, imitation and language. These cultural practices have their roots in our uniquely potent ability for social learning. This thesis sets out to elucidate the process of cultural evolution using a series of mathematical and computational models. These models first investigate the evolution of the capacity for social learning, the rare ability to teach, and the evolution of the smart and strategic use of social learning, in the animal lineage. They go on to investigate the implications of these strategies and mechanisms for culture and find that the form human culture takes is dependant on the amount and nature of social learning as well as on the underlying learning strategies deployed. The thesis also investigates the effect that culture has had on the human evolutionary niche. Cultural practices fundamentally change the selection pressures to which humans are subject and these in turn change both our cultures and our genes through gene-culture coevolution. Finally, a demographic cultural niche construction model is presented, which investigates the application of cultural evolution modelling, cultural niche construction theory and demographic models to the growing problem of sex-ratio imbalance in modern China and considers the implications for policy-making. The analyses presented in this thesis support the argument that the uniquely potent human ability to transmit acquired information through teaching, imitation and other forms of social learning, and through this to shape our cultural and ecological environments, has played and continues to play a central role in human evolution.
Thesis, PhD Doctor of Philosophy
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