Ethnoscientific expertise and knowledge specialisation in 55 traditional cultures

People everywhere acquire high levels of conceptual knowledge about their social and natural worlds, which we refer to as ethnoscientific expertise. Evolutionary explanations for expertise are still widely debated. We analysed ethnographic text records (N = 547) describing ethnoscientific expertise...

Descripción completa

Detalles Bibliográficos
Autores principales: Lightner, Aaron D., Heckelsmiller, Cynthiann, Hagen, Edward H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10427309/
https://www.ncbi.nlm.nih.gov/pubmed/37588549
http://dx.doi.org/10.1017/ehs.2021.31
Descripción
Sumario:People everywhere acquire high levels of conceptual knowledge about their social and natural worlds, which we refer to as ethnoscientific expertise. Evolutionary explanations for expertise are still widely debated. We analysed ethnographic text records (N = 547) describing ethnoscientific expertise among 55 cultures in the Human Relations Area Files to investigate the mutually compatible roles of collaboration, proprietary knowledge, cultural transmission, honest signalling, and mate provisioning. We found relatively high levels of evidence for collaboration, proprietary knowledge, and cultural transmission, and lower levels of evidence for honest signalling and mate provisioning. In our exploratory analyses, we found that whether expertise involved proprietary vs. transmitted knowledge depended on the domain of expertise. Specifically, medicinal knowledge was positively associated with secretive and specialised knowledge for resolving uncommon and serious problems, i.e. proprietary knowledge. Motor skill-related expertise, such as subsistence and technological skills, was positively associated with broadly competent and generous teachers, i.e. cultural transmission. We also found that collaborative expertise was central to both of these models, and was generally important across different knowledge and skill domains.