Dataset Information

The two types of society: Computationally revealing recurrent social formations and their evolutionary trajectories.

ABSTRACT: Comparative social science has a long history of attempts to classify societies and cultures in terms of shared characteristics. However, only recently has it become feasible to conduct quantitative analysis of large historical datasets to mathematically approach the study of social complexity and classify shared societal characteristics. Such methods have the potential to identify recurrent social formations in human societies and contribute to social evolutionary theory. However, in order to achieve this potential, repeated studies are needed to assess the robustness of results to changing methods and data sets. Using an improved derivative of the Seshat: Global History Databank, we perform a clustering analysis of 271 past societies from sampling points across the globe to study plausible categorizations inherent in the data. Analysis indicates that the best fit to Seshat data is five subclusters existing as part of two clearly delineated superclusters (that is, two broad "types" of society in terms of social-ecological configuration). Our results add weight to the idea that human societies form recurrent social formations by replicating previous studies with different methods and data. Our results also contribute nuance to previously established measures of social complexity, illustrate diverse trajectories of change, and shed further light on the finite bounds of human social diversity.

SUBMITTER: Miranda L

PROVIDER: S-EPMC7219743 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The two types of society: Computationally revealing recurrent social formations and their evolutionary trajectories.

Miranda Lux L Freeman Jacob J

PloS one 20200513 5

Comparative social science has a long history of attempts to classify societies and cultures in terms of shared characteristics. However, only recently has it become feasible to conduct quantitative analysis of large historical datasets to mathematically approach the study of social complexity and classify shared societal characteristics. Such methods have the potential to identify recurrent social formations in human societies and contribute to social evolutionary theory. However, in order to a ...[more]

PMID: 32401771

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Project description:Due to their worldwide distribution and occupancy of different types of environments, bottlenose dolphins display considerable morphological variation. Despite limited understanding about the taxonomic identity of such forms and connectivity among them at global scale, coastal (or inshore) and offshore (or oceanic) ecotypes have been widely recognized in several ocean regions. In the Southwest Atlantic Ocean (SWA), however, there are scarce records of bottlenose dolphins differing in external morphology according to habitat preferences that resemble the coastal-offshore pattern observed elsewhere. The main aim of this study was to analyze the genetic variability, and test for population structure between coastal (n = 127) and offshore (n = 45) bottlenose dolphins sampled in the SWA to assess whether their external morphological distinction is consistent with genetic differentiation. We used a combination of mtDNA control region sequences and microsatellite genotypes to infer population structure and levels of genetic diversity. Our results from both molecular marker types were congruent and revealed strong levels of structuring (microsatellites FST = 0.385, p < .001; mtDNA FST = 0.183, p < .001; ?ST = 0.385, p < .001) and much lower genetic diversity in the coastal than the offshore ecotype, supporting patterns found in previous studies elsewhere. Despite the opportunity for gene flow in potential "contact zones", we found minimal current and historical connectivity between ecotypes, suggesting they are following discrete evolutionary trajectories. Based on our molecular findings, which seem to be consistent with morphological differentiations recently described for bottlenose dolphins in our study area, we recommend recognizing the offshore bottlenose dolphin ecotype as an additional Evolutionarily Significant Unit (ESU) in the SWA. Implications of these results for the conservation of bottlenose dolphins in SWA are also discussed.

Dataset Information

The two types of society: Computationally revealing recurrent social formations and their evolutionary trajectories.

Publications

The two types of society: Computationally revealing recurrent social formations and their evolutionary trajectories.

Similar Datasets

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