JOURNAL ARTICLE
Occupational patterns in Anglo‐Saxon and Medieval East Midlands, England: Insights from activity‐related skeletal changes.
Published In: International Journal of Osteoarchaeology, 2023, v. 33, n. 3. P. 419 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Nikita, Efthymia; Radini, Anita 3 of 3
Abstract
This paper examines five assemblages from the East Midlands, England, assessing activity‐related skeletal changes with the aim of exploring differences in labor‐linked social divisions between the Anglo‐Saxon (5th–11th century) and medieval periods (11th–15th century). The Anglo‐Saxon assemblages come from Empingham and Southwell, while all three medieval assemblages originate from Leicester (St Michael's cemetery, St Peter's cemetery, Austin Friars). The analysis of activity‐related skeletal changes encompassed entheseal changes (EC) and cross‐sectional geometric properties (CSG) of the upper limb long bones. The results supported a lack of sexual dimorphism, with the exception of St Peter's for CSG. This pattern suggests the absence of systematic sex‐based division of labor in both the Anglo‐Saxon period and in the medieval period for part of the population, such as the poorer St Michael's individuals. Inter‐assemblage patterns, although restricted by small sample sizes, agree with historical and archaeological evidence for a more complex and diversified urban life in the later medieval period compared to the earlier Anglo‐Saxon period. However, at the same time they highlight the similarities that overall characterized these assemblages. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Osteoarchaeology. 2023/05, Vol. 33, Issue 3, p419
- Document Type:Article
- Subject Area:Military History and Science
- Publication Date:2023
- ISSN:1047-482X
- DOI:10.1002/oa.3186
- Accession Number:164136605
- 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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