We discussed the challenges and successes in inferring religious belief and practice from the archeological and historical record and new theoretical models and tools for exploring religious history, including the Database of Religious History (DRH).
Conformist transmission is a type of frequency dependent social learning
strategy in which individuals are disproportionately inclined to copy the most common trait in their sample of the population (e.g. individuals have a 90% probability of copying a trait that 60% of people possess). The bias is particularly important, because it tends to homogenize behavior within groups increasing between group differences relative to within group differences.
Our three key findings across two experiments were:
Substantial amounts of conformist transmission. We found substantial reliance on conformist biased social learning, with only 3% and 9% (or 15%) showing no bias in Experiments 1 and 2, respectively.
Increased social learning and stronger conformist bias as the number of options increased. Both the amount of social learning and the strength of conformist biases increased as the number of options increased (i.e. 60% of people wearing black shirts is more persuasive in a world of black, red, blue, yellow, and white shirt colors than in a world of only black shirts and white shirts). These results mean that all prior experiments have underestimated reliance on social learning and the strength of conformist transmission, since all use only 2 options.
IQ predicts both social learning and the strength of the conformist bias. IQ predicts less social learning, but has a U-shaped relationship to the strength of the conformist bias. These results suggest that higher IQ individuals are strategically using social learning (using it less, but with a stronger conformist bias when they choose to use other information).
The paper (in prep), co-authored with Maciek Chudek and Joe Henrich, describes an evolutionary model of the evolution of brains and parsimoniously explains several empirical relationships between brain size, group size, social learning, mating structures, culture, and the juvenile period. The model also describes the selection pressures that may have led humans into the realm of cumulative cultural evolution, further driving up the human brain size.
This week I visited the University of St Andrews, Scotland. Kevin Laland invited me to present my paper (in prep) on the Cultural Brain Hypothesis and the Cumulative Cultural Brain Hypothesis. The paper, co-authored with Maciek Chudek and Joe Henrich, describes an evolutionary model of the evolution of brains and parsimoniously explains several empirical relationships between brain size, group size, social learning, mating structures, culture, and the juvenile period. The model also describes the selection pressures that may have led humans into the realm of cumulative cultural evolution, further driving up the human brain size. I presented the research to Kevin’s lab and to Andy Whiten’s lab. I will also be presenting the paper early next month at the 26th Annual Meeting of Human Behavior and Evolution Society (HBES) in Natal, Brazil.
Proceedings of the Royal Society B: Biological Sciences published my paper with Ben W. Shulman, Vlad Vasilescu, and Joe Henrich showing that sociality influences cultural complexity. Across two experiments, we show that access to more people (1) increases cultural complexity, allowing for cumulative cultural evolution and (2) reduces the loss of cultural knowledge and skill. We found that students paid most attention to the most capable of their mentors, but also drew inspiration from the others, suggesting that the benefit of greater interconnectivity is twofold: you have access to the best people and information, but are also able to recombine knowledge from a greater variety of people.