Systematic bias in humanities datasets: ancient and medieval coin finds in the FLAME project

FLAME is an online digital humanities project providing economic data for investigations of the transition from Late Antiquity to the Early Middle Ages (CE 325-750) in Western Eurasia and North Africa. While accumulating, entering, and displaying the data, the project’s leadership has become increasingly aware of the inherent distortions in these data. These deviations operate on various levels, from the disparate events that provide the coin finds that serve as the basis of its data to previously unexamined scholarly biases that underpin such a quantitative approach to historical analysis. By systematically examining these phenomena, we hope to frame a discussion of such inherent biases in other digital humanities undertakings.

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Publication Details

Journal
Digital humanities quarterly
Published
2025-02-14
DOI
https://doi.org/10.63744/6xsv95vxqxd4
Primary Topic
Art History and Market Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Systematic bias in humanities datasets: ancient and medieval coin finds in the FLAME project

Mark Pyzyk, Ilia Curto Pelle, Lee Mordechai, Alan Stahl
Digital humanities quarterly
Art History and Market Analysis
article

Systematic bias in humanities datasets: ancient and medieval coin finds in the FLAME project

Mark Pyzyk, Ilia Curto Pelle, Lee Mordechai, Alan Stahl
article en

Abstract

FLAME is an online digital humanities project providing economic data for investigations of the transition from Late Antiquity to the Early Middle Ages (CE 325-750) in Western Eurasia and North Africa. While accumulating, entering, and displaying the data, the project’s leadership has become increasingly aware of the inherent distortions in these data. These deviations operate on various levels, from the disparate events that provide the coin finds that serve as the basis of its data to previously unexamined scholarly biases that underpin such a quantitative approach to historical analysis. By systematically examining these phenomena, we hope to frame a discussion of such inherent biases in other digital humanities undertakings.

Digital humanities quarterlyVol. 19(1)
Quality Education
Openalex Percentile: Top 3%
Art History and Market Analysis
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