Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization

Proceedings of the National Academy of Sciences Vol/Iss. 115(2) National Academy of Sciences Washington, D.C Published In Pages: 144-151
By Turchin, Peter, Currie, Thomas E., Whitehouse, Harvey, François, Pieter, Feeney, Kevin, Mullins, Daniel, Hoyer, Daniel, Collins, Christina, Grohmann, Stephanie, Savage, Patrick E., Mendel-Gleason, Gavin, Turner, Edward, Dupeyron, Agathe, Cioni, Enrico, Reddish, Jenny, Levine, Jill, Jordan, Greine, Brandl, Eva, Williams, Alice, Cesaretti, Rudolf, Krueger, Marta, Ceccarelli, Alessandro, Figliulo-Rosswurm, Joe, Tuan, Po-Ju, Peregrine, Peter N., Marciniak, Arkadiusz, Preiser-Kapeller, Johannes, Kradin, Nikolay, Korotayev, Andrey V., Palmisano, Alessio, Baker, David, Bidmead, Julye, Bol, Peter, Christian, David, Cook, Connie, Covey, Alan, Feinman, Gary M., Júlíusson, Árni Daníel, Kristinsson, Axel, Miksic, John, Mostern, Ruth, Petrie, Cameron, Rudiak-Gould, Peter, ter Haar, Barend, Wallace, Vesna, Mair, Victor, Xie, Liye, Baines, John, Bridges, Elizabeth, Manning, Joseph, Lockhart, Bruce, Bogaard, Amy, Spencer, Charles


Social complexity variables will cluster into two categories (scale and nonscale), resulting in two significant principal components of variation.


Post Hoc: Alternative hypothesis is that the variables are all correlated with each other, and will result in one principal component.


Test NameSupportSignificanceCoefficientTail
Principal Component AnalysisNot SupportedNAMultipleUNKNOWN