Transparent population estimations using Bayesian models

Hinz, Martin; Roe, Joe (2 February 2023). Transparent population estimations using Bayesian models (Unpublished). In: DAB 2023: Digital Archaeology Bern “advancing open research into the next decade”. Bern. 1.-3.3.2023.

Demographic estimates in archaeology are currently a dark art. Either they are based entirely on an intuitive assessment by experts, and this is inevitably subjective and often not particularly data-based. Or they are based on mathematical models, but often the underlying data and calculations are not sufficiently open. This has improved to some extent in recent years, with the focus on 14C data as the dominant proxy for such estimates. However, the use of radiocarbon-based SPD has its own pitfalls: The transfer functions between the number of datings to the desired population sizes are unknown, so that at best a relative statement can be made. Interpretation is thus again necessary, and we have to rely on subjective estimates and eyeballing.

We have developed an approach to estimating population sizes that is able to incorporate various proxies in addition to 14C data, and which aspires to provide absolute numbers. In this talk I would like to present this approach and its results so far and give an outlook on further development and application. In addition, I will present our experiences with the full reproducible analytical chain and the challenges as well as our strategies how to deal with them in order to bring archaeological demography to the same methodological level as contemporary studies currently have.

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