SRR-754

@dataset{Bevan2017,
  title = {Radiocarbon Dataset and Analysis from Bevan, A., Colledge, S., Fuller, D., Fyfe, R., Shennan, S. and C. Stevens 2017. Holocene Fluctuations in Human Population Demonstrate Repeated Links to Food Production and Climate},
  author = {Bevan, A. H.},
  date = {2017-10-20},
  publisher = {UCL Institute of Archaeology},
  location = {London, UK},
  doi = {10.14324/000.ds.10025178},
  url = {https://discovery.ucl.ac.uk/id/eprint/10025178/},
  urldate = {2023-09-07},
  langid = {english}
}
@article{p3k14c,
  title = {P3k14c, a Synthetic Global Database of Archaeological Radiocarbon Dates},
  author = {Bird, Darcy and Miranda, Lux and Vander Linden, Marc and Robinson, Erick and Bocinsky, R. Kyle and Nicholson, Chris and Capriles, José M. and Finley, Judson Byrd and Gayo, Eugenia M. and Gil, Adolfo and d’Alpoim Guedes, Jade and Hoggarth, Julie A. and Kay, Andrea and Loftus, Emma and Lombardo, Umberto and Mackie, Madeline and Palmisano, Alessio and Solheim, Steinar and Kelly, Robert L. and Freeman, Jacob},
  year = {2022},
  month = {jan},
  journal = {Scientific Data},
  volume = {9},
  number = {1},
  pages = {27},
  publisher = {Nature Publishing Group},
  issn = {2052-4463},
  doi = {10.1038/s41597-022-01118-7},
  abstract = {Archaeologists increasingly use large radiocarbon databases to model prehistoric human demography (also termed paleo-demography). Numerous independent projects, funded over the past decade, have assembled such databases from multiple regions of the world. These data provide unprecedented potential for comparative research on human population ecology and the evolution of social-ecological systems across the Earth. However, these databases have been developed using different sample selection criteria, which has resulted in interoperability issues for global-scale, comparative paleo-demographic research and integration with paleoclimate and paleoenvironmental data. We present a synthetic, global-scale archaeological radiocarbon database composed of 180,070 radiocarbon dates that have been cleaned according to a standardized sample selection criteria. This database increases the reusability of archaeological radiocarbon data and streamlines quality control assessments for various types of paleo-demographic research. As part of an assessment of data quality, we conduct two analyses of sampling bias in the global database at multiple scales. This database is ideal for paleo-demographic research focused on dates-as-data, bayesian modeling, or summed probability distribution methodologies.},
  copyright = {2022 The Author(s)},
  langid = {english},
  keywords = {Archaeology,Chemistry},
  month_numeric = {1}
}
@misc{Cessford 2005: 85 Bronk Ramsey et al. 2009: 337,
  
}
@misc{Moore et al. 1986 Gowlett and Hedges 1987 Housley 1994 Schyle 1996,
  
}
@misc{Maggs T. 1984. The Iron Age South of the Zambezi. In: Klein R.G. (ed.) Southern African Prehistory and Palaeoenvironments. A.A.Balkema Rotterdam and Boston: 329–360,
  
}
@misc{Vogel JC and Marais M. 1971. Pretoria radiocarbon dates I. Radiocarbon 13: 378-394,
  
}
@misc{Vogel JC and Visser E. 1981. Pretoria Radiocarbon dates II. Radiocarbon 23: 43-80,
  
}
@misc{Carter P.L. Mitchell P.J. and Vinnicombe P. 1988. Sehonghong: The Middle and Later Stone Age industrial sequence at a Lesotho rockshelter. British Archaeological Reports International Series.,
  
}
@misc{Larsson 2019,
  
}
@misc{Ashmore 2004,
  
}

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---
- :bibtex_key: Bevan2017
  :bibtex_type: :dataset
  :title: "{Radiocarbon Dataset and Analysis from Bevan, A., Colledge, S., Fuller,
    D., Fyfe, R., Shennan, S. and C. Stevens 2017. Holocene Fluctuations in Human
    Population Demonstrate Repeated Links to Food Production and Climate}"
  :author: "{Bevan, A. H.}"
  :date: "{2017-10-20}"
  :publisher: "{UCL Institute of Archaeology}"
  :location: "{London, UK}"
  :doi: "{10.14324/000.ds.10025178}"
  :url: "{https://discovery.ucl.ac.uk/id/eprint/10025178/}"
  :urldate: "{2023-09-07}"
  :langid: "{english}"
---
- :bibtex_key: p3k14c
  :bibtex_type: :article
  :title: "{P3k14c, a Synthetic Global Database of Archaeological Radiocarbon Dates}"
  :author: "{Bird, Darcy and Miranda, Lux and Vander Linden, Marc and Robinson, Erick
    and Bocinsky, R. Kyle and Nicholson, Chris and Capriles, José M. and Finley, Judson
    Byrd and Gayo, Eugenia M. and Gil, Adolfo and d’Alpoim Guedes, Jade and Hoggarth,
    Julie A. and Kay, Andrea and Loftus, Emma and Lombardo, Umberto and Mackie, Madeline
    and Palmisano, Alessio and Solheim, Steinar and Kelly, Robert L. and Freeman,
    Jacob}"
  :year: "{2022}"
  :month: "{jan}"
  :journal: "{Scientific Data}"
  :volume: "{9}"
  :number: "{1}"
  :pages: "{27}"
  :publisher: "{Nature Publishing Group}"
  :issn: "{2052-4463}"
  :doi: "{10.1038/s41597-022-01118-7}"
  :abstract: "{Archaeologists increasingly use large radiocarbon databases to model
    prehistoric human demography (also termed paleo-demography). Numerous independent
    projects, funded over the past decade, have assembled such databases from multiple
    regions of the world. These data provide unprecedented potential for comparative
    research on human population ecology and the evolution of social-ecological systems
    across the Earth. However, these databases have been developed using different
    sample selection criteria, which has resulted in interoperability issues for global-scale,
    comparative paleo-demographic research and integration with paleoclimate and paleoenvironmental
    data. We present a synthetic, global-scale archaeological radiocarbon database
    composed of 180,070 radiocarbon dates that have been cleaned according to a standardized
    sample selection criteria. This database increases the reusability of archaeological
    radiocarbon data and streamlines quality control assessments for various types
    of paleo-demographic research. As part of an assessment of data quality, we conduct
    two analyses of sampling bias in the global database at multiple scales. This
    database is ideal for paleo-demographic research focused on dates-as-data, bayesian
    modeling, or summed probability distribution methodologies.}"
  :copyright: "{2022 The Author(s)}"
  :langid: "{english}"
  :keywords: "{Archaeology,Chemistry}"
  :month_numeric: "{1}"
---
:bibtex_key: 'Cessford 2005: 85 Bronk Ramsey et al. 2009: 337'
:bibtex_type: :misc
---
:bibtex_key: Moore et al. 1986 Gowlett and Hedges 1987 Housley 1994 Schyle 1996
:bibtex_type: :misc
---
:bibtex_key: 'Maggs T. 1984. The Iron Age South of the Zambezi. In: Klein R.G. (ed.)
  Southern African Prehistory and Palaeoenvironments. A.A.Balkema Rotterdam and Boston:
  329–360'
:bibtex_type: :misc
---
:bibtex_key: 'Vogel JC and Marais M. 1971. Pretoria radiocarbon dates I. Radiocarbon
  13: 378-394'
:bibtex_type: :misc
---
:bibtex_key: 'Vogel JC and Visser E. 1981. Pretoria Radiocarbon dates II. Radiocarbon
  23: 43-80'
:bibtex_type: :misc
---
:bibtex_key: 'Carter P.L. Mitchell P.J. and Vinnicombe P. 1988. Sehonghong: The Middle
  and Later Stone Age industrial sequence at a Lesotho rockshelter. British Archaeological
  Reports International Series.'
:bibtex_type: :misc
---
:bibtex_key: Larsson 2019
:bibtex_type: :misc
---
:bibtex_key: Ashmore 2004
:bibtex_type: :misc