Year: 2024
Type: article
Abstract: Introduction. The article is devoted to a review of the results of anthropological research of European populations based on visual art, which is conducted in the laboratory of racial studies of the Anuchin Institute and Museum of Anthropology of Moscow State University. Results and discussion. The study of morphological variability of population based on the visual arts is a relatively new interdisciplinary area of physical anthropology. Research is being carried out in two directions: 1) European portraiture of the 15th-19th centuries and Russian portraiture of the 18th - 19th centuries, 2) Mediterranean ancient sculpture and painting. Descriptions of materials and methodology are detailed in the main articles of the team cited in the bibliography. The image series were studied from a population approach to the analysis of variability. About one and a half thousand Western European and Russian portraits were studied, anthropological characteristics and estimates of homogeneity of the population were obtained by descriptive method and the composite portrait method. An anthropological description of the ancient population of the Mediterranean was obtained from samples: Fayum pictorial portraits, Roman sculptural portraits, Etruscan pictorial and sculptural portraits, Greek sculptural and pictorial portraits. Conclusion. The iconography of the physical features of the populations in various monuments of material culture and art allows us to obtain anthropological information about the variability of ancient and modern populations. The research potential of visual art resources for anthropology is evident and varied, but has not yet been sufficiently studied in terms of estimating and verifying of anthropological information that can become research applications for future researchers. © 2024. This work is licensed under a CC BY 4.0 license
Author: Larisa Yu. Shpak
Language: English
Subfield: Archeology
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4409512903