Challenges in sample processing within radiocarbon dating and their impact in C-14-dates-as-data studies
| dc.contributor.author | Becerra-Valdivia, Lorena | |
| dc.contributor.author | Leal-Cervantes, Rodrigo | |
| dc.contributor.author | Higham, Tom | |
| dc.contributor.author | Wood, Rachel | |
| dc.date.accessioned | 2023-07-21T04:34:24Z | |
| dc.date.issued | 2020 | |
| dc.date.updated | 2022-05-29T08:16:26Z | |
| dc.description.abstract | For decades, researchers have employed sets of radiocarbon dates to reconstruct trends in ancient human populations. The overarching assumption in this analysis is that the frequency of dates is proportional to the magnitude of past human activity. Thus, the distribution of summed or otherwise summarized dates is used to extrapolate population density and mobility patterns. There are, however, a number of underlying assumptions associated with this analysis that workers address to varying degrees and which, if false and not critically accounted for, will introduce bias, misrepresent the magnitude of activity, and ultimately prove misleading in archaeological interpretations. In this regard, research has so far mainly focused on correcting for the effects of time-dependent degradation of archaeological sites and constituent materials, calibration irregularities, and the efficacy of the statistical methods used. Assumptions directly related to sample processing in radiocarbon dating, however, are less discussed in ‘ 14C-dates-as-data’ analyses. It is, for example, assumed that all carbonaceous materials will yield sufficient, endogenous carbon for radiocarbon measurement. Yet sample failure in radiocarbon dating is common and contingent on, largely, deterministic factors such as post-depositional environment. Sets of radiocarbon dates analyzed, therefore, represent successful measurements independent of reliability. In this work, we discuss the biases introduced by challenges in radiocarbon processing and their impact on 14C-dates-as-data studies | en_AU |
| dc.description.sponsorship | Funding was provided by the Clarendon Fund Scholarship, University of Oxford; the Natural Environment Research Council (NERC; NE/D014077/1); and the EPSRC Centre for Doctoral Training in Industrially Focused Mathematical Modelling (EP/ L015803/1), University of Oxford. | en_AU |
| dc.format.mimetype | application/pdf | en_AU |
| dc.identifier.issn | 0305-4403 | en_AU |
| dc.identifier.uri | http://hdl.handle.net/1885/294488 | |
| dc.language.iso | en_AU | en_AU |
| dc.publisher | Elsevier | en_AU |
| dc.rights | © 2019 Elsevier Ltd | en_AU |
| dc.source | Journal of Archaeological Science | en_AU |
| dc.subject | Radiocarbon dating | en_AU |
| dc.subject | Summarized probability distributions | en_AU |
| dc.subject | Data analysis | en_AU |
| dc.subject | Archaeological science | en_AU |
| dc.subject | Archaeology | en_AU |
| dc.title | Challenges in sample processing within radiocarbon dating and their impact in C-14-dates-as-data studies | en_AU |
| dc.type | Journal article | en_AU |
| local.bibliographicCitation.lastpage | 105043-9 | en_AU |
| local.bibliographicCitation.startpage | 105043-1 | en_AU |
| local.contributor.affiliation | Becerra-Valdivia, Lorena, University of Oxford | en_AU |
| local.contributor.affiliation | Leal-Cervantes, Rodrigo, University of Oxford | en_AU |
| local.contributor.affiliation | Higham, Tom, Research Laboratory for Archaeology | en_AU |
| local.contributor.affiliation | Wood, Rachel, College of Arts and Social Sciences, ANU | en_AU |
| local.contributor.authoruid | Wood, Rachel, u5042027 | en_AU |
| local.description.embargo | 2099-12-31 | |
| local.description.notes | Imported from ARIES | en_AU |
| local.identifier.absfor | 430101 - Archaeological science | en_AU |
| local.identifier.ariespublication | a383154xPUB10888 | en_AU |
| local.identifier.citationvolume | 113 | en_AU |
| local.identifier.doi | 10.1016/j.jas.2019.105043 | en_AU |
| local.identifier.thomsonID | WOS:000509622200001 | |
| local.publisher.url | https://www.elsevier.com/en-au | en_AU |
| local.type.status | Published Version | en_AU |
Downloads
Original bundle
1 - 1 of 1
Loading...
- Name:
- 1-s2.0-S030544031930130X-main.pdf
- Size:
- 1.06 MB
- Format:
- Adobe Portable Document Format
- Description: