Embodied labors during the state formation of Egypt and Nubia (ca. 4800–1750 BCE): Elucidating transformations in behavioral patterns with entheseal changes.

  • Published In: International Journal of Osteoarchaeology, 2023, v. 33, n. 3. P. 444 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Carballo‐Pérez, Jared; Schrader, Sarah A. 3 of 3

Abstract

Throughout Egypt and Nubia's state formation periods (4400–1750 BCE), broad transformations impacted Nile Valley communities, which experienced agricultural consolidation, sedentarization, and more complex social organization. The current study examines the various patterns and levels of physical activity in the skeletal remains of 259 predynastic and early dynastic individuals from Nubia (Northern Dongola Reach) and Egypt (el‐Badari, Naqada, el‐Ballas, and Hu). Using entheseal changes in the upper and lower limbs and non‐parametric tests, we have observed changes in behavior patterns between the fifth and second millennia BCE in the Nile Valley. These transformations include an increased impact on the evolution of physical activity and possibly specialized occupations in the Old Kingdom. In this regard, we discovered differences in activity based on the type of burial and the tasks performed by females compared with males. Furthermore, we found additional evidence to support the hypothesis that the Nubian state of Kerma was based on a highly mobile pastoral way of life. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Osteoarchaeology. 2023/05, Vol. 33, Issue 3, p444
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2023
  • ISSN:1047-482X
  • DOI:10.1002/oa.3198
  • Accession Number:164136609
  • Copyright Statement:Copyright of International Journal of Osteoarchaeology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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