The Science of Change: How do we measure cultural transmission at large scales?

Evolutionary modeling of cultural transmission and cultural change has grown over the past 25 years from a handful of biologist and social scientists, to a major interdisciplinary program that involves research in every social science, cognitive and computer science, biologists, and even physicists.  Formal models of cultural transmission and evolution have proliferated, but major challenges exist in testing transmission models against real world data.  Difficulties exist even when we have individual-level observations.

The challenge is even more profound when the only data we have on a cultural or economic phenomenon come in aggregate form:  where our observations refer to groups of people, blocks of time, or both.  After examining how aggregated data foil our efforts at inferring the parameters of evolutionary models or accurately choosing between models, I advocate for matching aggregate data with higher level models and research questions.  I demonstrate how aggregate data from cultural transmission simulations can accurately discriminate between macroevolutionary transmission models, giving us the ability to understand large scale transmission phenomena even while micro scale causation remains obscure.