Towards a Multivariate Model for Accurately Identifying Cutmarks

Summary

The identification of cutmarks has been integral to expanding the understanding of hominin behavior ranging from the origins of meat eating to megafaunal extinctions and the peopling of Australia and the Americas. However, paleoanthropological and archaeological research has demonstrated that while cutmark placement may be indicative of activity, cutmark morphology is more complex and influenced by multiple variables such as raw material, tool shape, and bone density. Further, significant overlap in the classic features of cutmarks, such as the standard V-shaped cross-section, has also been recognized in numerous processes including carnivore gnawing and trampling. This presentation establishes an empirical, probabilistic, and multivariate approach through logistic regression for differentiating raw materials (lithics, steel, and teeth) as well as actors which produce modifications commonly identified as evidence for butchering in the archaeological record. The results demonstrate that no diagnostic attribute of cutmarks produced by lithics was identified. Therefore, single attributes are insufficient for accurate cutmark identification. However, an approach which includes excavation history, stratigraphic context, location, orientation, and color of mark improve the likelihood with which cutmarks are identified accurately.

SAA 2015 abstracts made available in tDAR courtesy of the Society for American Archaeology and Center for Digital Antiquity Collaborative Program to improve digital data in archaeology. If you are the author of this presentation you may upload your paper, poster, presentation, or associated data (up to 3 files/30MB) for free. Please visit http://www.tdar.org/SAA2015 for instructions and more information.

This Resource is Part of the Following Collections

• From Taphonomy to Human Ecology: Papers in Honor of Gary Haynes   •
• Society for American Archaeology 80th Annual Meeting, San Francisco, CA (2015)

Keywords

Spatial Coverage