Volume 35, Issue 1 e3379
RESEARCH ARTICLE

A Method for Detecting Bias in Human Archaeological Cemetery Samples

Bonnie R. Taylor

Corresponding Author

Bonnie R. Taylor

School of Archaeology and Anthropology, Australian National University, Canberra, Australian Capital Territory, Australia

Correspondence:

Bonnie R. Taylor ([email protected])

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Marc F. Oxenham

Marc F. Oxenham

School of Archaeology and Anthropology, Australian National University, Canberra, Australian Capital Territory, Australia

Department of Archaeology, School of Geosciences, University of Aberdeen, Aberdeen, UK

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First published: 22 December 2024
Citations: 1

Funding: This work was supported by Australian Government Research Training Program Scholarship.

ABSTRACT

This paper aims to provide a methodological approach to identify potential bias in cemetery sample age-at-death distributions and provide an alternative way to report fertility despite underenumeration. The method involves comparing total fertility rate (TFR) estimates from two empirically derived models developed on a United Nations mortality and fertility dataset. The models utilize different age cohorts in their calculations (one relies on the proportion of pre-adults aged < 15 years, whereas the other excludes all those aged < 15 years). The tested hypothesis is that similar TFR estimates using both models indicate a relatively unbiased sample, although the converse would suggest cemetery sample bias in one broad age cohort. Results comparing the respective TFR estimates from D0–14/D and D15–49/D15+ models confirm that fertility estimates are comparable for unbiased samples. From this, a method for the coordinated application of the D0–14/D and D15–49/D15+ models were found to be valid in determining if a cemetery sample was biased. Following the determination of potential underrepresentation, an approach is outlined for dealing with biased and unbiased cemetery samples in terms of reporting on demographic variables such as TFRs.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

United Nations (2024) and Roser (2024) data used in this article can be found in the Supporting Information.

The full text of this article hosted at iucr.org is unavailable due to technical difficulties.