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University of Cambridge > Talks.cam > Computational and Digital Archaeology Lab (CDAL) > Simulation modelling as a method to explain cultural transmission processes using sparse data: a case study from the Aegean Bronze Age looking at the transmission of pottery-making technologies.
Simulation modelling as a method to explain cultural transmission processes using sparse data: a case study from the Aegean Bronze Age looking at the transmission of pottery-making technologies.Add to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact akm73. Simulation modelling is a powerful method for understanding the causal factors behind dynamic transmission processes in the past and has seen widespread application in archaeology, particularly in subfields with an established theoretical framework (e.g., evolutionary archaeology) and a tradition of systematic quantification. Typically, the assumptions of the simulation are informed by theory, and quantitative data are used to inform the selection of parameter ranges/values and to compare the empirical record to the outcomes of the simulated process. While these characteristics are necessary to develop simulation models producing detailed explanations of a phenomenon, they do not hold in all academic traditions. In Aegean archaeology, explanations are often produced by verbal models that are not quantitatively compared to the material record, and quantitative data are often published in a non-standardised manner which impedes large-scale comparisons across sites and regions. In this talk, I will discuss ways to overcome these challenges and show that, even with sparse data, it is still possible to build simulation models which produce insights that are hard to achieve with other methods using examples from a simulation-based study on the cultural transmission of pottery-making technologies in the Bronze Age Aegean. This talk is part of the Computational and Digital Archaeology Lab (CDAL) series. This talk is included in these lists:
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