Data-Informed Tools for Archaeological Reflexivity: Examining the substance of bone through a meta-analysis of academic texts

Abstract

Our study uses computational archaeology tools to investigate how researchers in our field present interpretations of the past in patterned ways. We do so in order to illuminate assumptions, naturalised categories, and patterned interpretative moves that may direct or impact the ways we interact with our evidence and write about our research. We approach this topic through a meta-analysis, using large-scale textual data from archaeological publications, focusing on the case study of bone. Are there patterned ways that archaeologists write about artefacts like bone that are visible when analysing larger datasets? If so, what underlying ideas shape these shared discursive moves? We present the results of three analyses: textual groundwork, conducted manually by field experts, and two machine-based interactive topic modelling visualisations (pyLDAvis and a hierarchical tree based on a Model of Models). Our results indicate that there are, indeed, patterns in our writing around how artefactual and archaeological materials are discussed, many of which are overt and sensical. However, our analyses also identify patterned discourses that are less obvious, but still part of regularised discourses in written narratives surrounding bone. These include: the use of multiple conceptual positions within, rather than simply between, articles, and a lack of patterned centrality of indigenous ontologies in how our field writes about bone. This pilot approach identifies data-informed, applied tools that will aid reflexive practices in our field. These operate at a scale that impacts future scholarly interactions with both evidence and published interpretations by shifting observation and reflection from an individual or small group exercise to a larger and more systematic process.