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The Monongahela tradition in “real time”: Bayesian analysis of radiocarbon dates

Despite advances in techniques, methods, and theory, northeastern North American archaeologists continue to use early to mid-twentieth century culture historical taxa as units of analysis and narrative. There is a distinct need to move away from this archaeological practice to enable fuller understa...

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Detalles Bibliográficos
Autores principales: Hart, John P., Means, Bernard K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605291/
https://www.ncbi.nlm.nih.gov/pubmed/36288354
http://dx.doi.org/10.1371/journal.pone.0276014
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author Hart, John P.
Means, Bernard K.
author_facet Hart, John P.
Means, Bernard K.
author_sort Hart, John P.
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description Despite advances in techniques, methods, and theory, northeastern North American archaeologists continue to use early to mid-twentieth century culture historical taxa as units of analysis and narrative. There is a distinct need to move away from this archaeological practice to enable fuller understandings of past human lives. One tool that enables such a move is Bayesian analysis of radiocarbon dates, which provides a means of constructing continuous chronologies. A large dataset of radiocarbon dates for late prehistoric (ca AD 900/1000–1650) sites in the lower upper Ohio River basin in southwestern Pennsylvania and adjacent portions of Maryland, Ohio, and West Virginia is used here as an example. The results allow a preliminary assessment of how the settlement plans of contemporaneous villages varied considerably, reflecting decisions of the village occupants how to structure built environments to meet their needs.
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spelling pubmed-96052912022-10-27 The Monongahela tradition in “real time”: Bayesian analysis of radiocarbon dates Hart, John P. Means, Bernard K. PLoS One Research Article Despite advances in techniques, methods, and theory, northeastern North American archaeologists continue to use early to mid-twentieth century culture historical taxa as units of analysis and narrative. There is a distinct need to move away from this archaeological practice to enable fuller understandings of past human lives. One tool that enables such a move is Bayesian analysis of radiocarbon dates, which provides a means of constructing continuous chronologies. A large dataset of radiocarbon dates for late prehistoric (ca AD 900/1000–1650) sites in the lower upper Ohio River basin in southwestern Pennsylvania and adjacent portions of Maryland, Ohio, and West Virginia is used here as an example. The results allow a preliminary assessment of how the settlement plans of contemporaneous villages varied considerably, reflecting decisions of the village occupants how to structure built environments to meet their needs. Public Library of Science 2022-10-26 /pmc/articles/PMC9605291/ /pubmed/36288354 http://dx.doi.org/10.1371/journal.pone.0276014 Text en © 2022 Hart, Means https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hart, John P.
Means, Bernard K.
The Monongahela tradition in “real time”: Bayesian analysis of radiocarbon dates
title The Monongahela tradition in “real time”: Bayesian analysis of radiocarbon dates
title_full The Monongahela tradition in “real time”: Bayesian analysis of radiocarbon dates
title_fullStr The Monongahela tradition in “real time”: Bayesian analysis of radiocarbon dates
title_full_unstemmed The Monongahela tradition in “real time”: Bayesian analysis of radiocarbon dates
title_short The Monongahela tradition in “real time”: Bayesian analysis of radiocarbon dates
title_sort monongahela tradition in “real time”: bayesian analysis of radiocarbon dates
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605291/
https://www.ncbi.nlm.nih.gov/pubmed/36288354
http://dx.doi.org/10.1371/journal.pone.0276014
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