Inferring the age and sex of ancient potters from fingerprint ridge densities: A data-driven, Bayesian mixture modelling approach

The density of epidermal ridges in a fingerprint varies predictably by age and sex. Archaeologists are therefore interested in using recovered fingerprints to learn about the ancient people who produced them. Recent studies focus on estimating the age and sex of individuals by measuring their finger...

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Main Authors: Andrew T. Burchill, Akiva Sanders, Thomas J.H. Morgan
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:MethodsX
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2215016123002893
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author Andrew T. Burchill
Akiva Sanders
Thomas J.H. Morgan
author_facet Andrew T. Burchill
Akiva Sanders
Thomas J.H. Morgan
author_sort Andrew T. Burchill
collection DOAJ
description The density of epidermal ridges in a fingerprint varies predictably by age and sex. Archaeologists are therefore interested in using recovered fingerprints to learn about the ancient people who produced them. Recent studies focus on estimating the age and sex of individuals by measuring their fingerprints with one of two similar metrics: mean ridge breadth (MRB) or ridge density (RD). Yet these attempts face several critical problems: expected values for adult females and adolescent males are inherently indistinguishable, and inter-assemblage variation caused by biological and technological differences cannot be easily estimated. Each of these factors greatly decreases the accuracy of predictions based on individual prints, and together they condemn this strategy to relative uselessness. However, information in fingerprints from across an assemblage can be pooled to generate a more accurate depiction of potter demographics. We present a new approach to epidermal ridge density analysis using Bayesian mixture models with the following key benefits: • Age and sex are estimated more accurately than existing methods by incorporating a data-driven understanding of how demographics and ridge density covary. • Uncertainty in demographic estimates is automatically quantified and included in output. • The Bayesian framework can be easily adapted to fit the unique needs of different researchers.
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spelling doaj.art-610f626705b140cdb6749349f3e97c832023-12-04T05:22:12ZengElsevierMethodsX2215-01612023-12-0111102292Inferring the age and sex of ancient potters from fingerprint ridge densities: A data-driven, Bayesian mixture modelling approachAndrew T. Burchill0Akiva Sanders1Thomas J.H. Morgan2School of Life Sciences, Arizona State University; Corresponding author.Department of Near Eastern Languages and Civilizations, University of Chicago; American Research Institute in TurkeySchool of Human Evolution and Social Change, Arizona State University; Institute of Human Origins, Arizona State UniversityThe density of epidermal ridges in a fingerprint varies predictably by age and sex. Archaeologists are therefore interested in using recovered fingerprints to learn about the ancient people who produced them. Recent studies focus on estimating the age and sex of individuals by measuring their fingerprints with one of two similar metrics: mean ridge breadth (MRB) or ridge density (RD). Yet these attempts face several critical problems: expected values for adult females and adolescent males are inherently indistinguishable, and inter-assemblage variation caused by biological and technological differences cannot be easily estimated. Each of these factors greatly decreases the accuracy of predictions based on individual prints, and together they condemn this strategy to relative uselessness. However, information in fingerprints from across an assemblage can be pooled to generate a more accurate depiction of potter demographics. We present a new approach to epidermal ridge density analysis using Bayesian mixture models with the following key benefits: • Age and sex are estimated more accurately than existing methods by incorporating a data-driven understanding of how demographics and ridge density covary. • Uncertainty in demographic estimates is automatically quantified and included in output. • The Bayesian framework can be easily adapted to fit the unique needs of different researchers.http://www.sciencedirect.com/science/article/pii/S2215016123002893Bayesian dermatoglyphic evaluation
spellingShingle Andrew T. Burchill
Akiva Sanders
Thomas J.H. Morgan
Inferring the age and sex of ancient potters from fingerprint ridge densities: A data-driven, Bayesian mixture modelling approach
MethodsX
Bayesian dermatoglyphic evaluation
title Inferring the age and sex of ancient potters from fingerprint ridge densities: A data-driven, Bayesian mixture modelling approach
title_full Inferring the age and sex of ancient potters from fingerprint ridge densities: A data-driven, Bayesian mixture modelling approach
title_fullStr Inferring the age and sex of ancient potters from fingerprint ridge densities: A data-driven, Bayesian mixture modelling approach
title_full_unstemmed Inferring the age and sex of ancient potters from fingerprint ridge densities: A data-driven, Bayesian mixture modelling approach
title_short Inferring the age and sex of ancient potters from fingerprint ridge densities: A data-driven, Bayesian mixture modelling approach
title_sort inferring the age and sex of ancient potters from fingerprint ridge densities a data driven bayesian mixture modelling approach
topic Bayesian dermatoglyphic evaluation
url http://www.sciencedirect.com/science/article/pii/S2215016123002893
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