Peopling the past: creating a site biography in the Hungarian Neolithic

  • Alex Bayliss (Author)
  • Nancy Beavan (Author)
  • Derek Hamilton (Author)
  • Kitti Köhler (Author)
  • Éva Ágnes Nyerges (Author)
  • Christopher Bronk Ramsey (Author)
  • Elaine Dunbar (Author)
  • Marc Fecher (Author)
  • Tomasz Goslar (Author)
  • Bernd Kromer (Author)
  • Paula Reimer (Author)
  • Eszter Bánffy (Author)
  • Tibor Marton (Author)
  • Krisztián Oross (Author)
  • Anett Osztás (Author)
  • István Zalai-Gaál (Author)
  • Alasdair Whittle (Author)

Abstract

Imprecise chronology has entailed a fuzzy kind of prehistory. Prehistorians should no longer be content with timeframes that employ successive units of 200 years or more duration, or with slow change over the long term as their dominant chronological and interpretative perspective. The means to get away from very generalised accounts of the past is formal chronological modelling in a Bayesian framework. The Bayesian approach in general is outlined, with emphasis on its interpretive and iterative nature. The approach combines calibrated radiocarbon dates with knowledge of the archaeological contexts from which they are derived to produce a series of formal, probabilistic date estimates. Stringent demands are made of both the radiocarbon dates and our archaeological understanding of stratigraphy, associations, sample taphonomy and context in general. The Bayesian process at Alsónyék involved assessment of existing dates, careful definition of aims and objectives, the construction of a rigorous sampling strategy, with an explicit hierarchy of suitable samples, precise understanding of the contexts from which samples are derived, and simulation to achieve cost-effective use of resources. The principal material dated at Alsónyék was human and animal bone. Potential age offsets from non-vegetarian diets are carefully considered; ‘perfect pairs’ of human and animal bone samples from the same contexts indicate that human bone samples are not subject to wide-scale freshwater reservoir effects. Dietary inputs are estimated formally using a series of Bayesian mixing models. The sequence of iterative sampling submissions between 2012 and 2015 is described, and the procedures of the five laboratories involved are detailed. Procedures for model construction, validation and comparison are discussed. Finally, we consider how we can use precise timings to reveal the web of connections and successions that made up past lives, adding plot and context to a more precise chronicle to create narratives for peopling the past.

Statistics

loading
Published
2017-04-11
Language
en