Exploring the role of ecology and social organisation in agropastoral societies: A Bayesian network approach

Olga Palacios Martínez, J.A. Barceló*, Rosario Delgado de la Torre

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

Abstract

The present contribution focuses on investigating the interaction of people and environment in small-scale farming societies. Our study is centred on the particular way settlement location constraints economic strategy when technology is limited, and social division of work is not fully developed. Our intention is to investigate prehistoric socioeconomic organisation when farming began in the Old World along the Levant shores of Iberian Peninsula, the Neolithic phenomenon. We approach this subject extracting relevant information from a big set of ethnographic and ethnoarchaeological cases using Machine Learning methods. This paper explores the use of Bayesian networks as explanatory models of the independent variables-the environment- and dependent variables-social decisions-, and also as predictive models. The study highlights how subsistence strategies are modified by ecological and topographical variables of the settlement location and their relationship with social organisation. It also establishes the role of Bayesian networks as a suitable supervised Machine Learning methodology for investigating socio-ecological systems, introducing their use to build useful data-driven models to address relevant archaeological and anthropological questions.

Original languageEnglish
Article numbere0276088
Number of pages29
JournalPLoS ONE
Volume17
Issue number10 October
DOIs
Publication statusPublished - 26 Oct 2022

Keywords

  • Agriculture
  • Archaeology
  • Bayes Theorem
  • Humans
  • Population Groups
  • Technology

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