The Devil's in the Detail: A review of Group I and III Petrographic Thin-Sections

Markham, M. Virginia

doi:10.11141/ia.26.23

Cited by 1 publication

(1 citation statement)

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“…It also assigns axeheads to coarser macrogroups for those stones that come from the same broad region of Britain. While there have been attempts to identify even more precise sources within existing source areas using geochemical fingerprinting, and these have met with some success (Markham and Floyd 1998;Markham 2009;Davis et al 2009), such techniques have not as yet been applied consistently across the sample, and for the purposes of the present analysis, a more approximate source location within ca. 50 km is more than sufficient.…”

Section: Methodsmentioning

confidence: 99%

British Neolithic Axehead Distributions and Their Implications

Schauer

Bevan

Shennan

et al. 2019

J Archaeol Method Theory

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Neolithic stone axeheads from Britain provide an unusually rich, well-provenanced set of evidence with which to consider patterns of prehistoric production and exchange. It is no surprise then that these objects have often been subject to spatial analysis in terms of the relationship between particular stone source areas and the distribution of axeheads made from those stones. At stake in such analysis are important interpretative issues to do with how we view the role of material value, supply, exchange, and demand in prehistoric societies. This paper returns to some of these well-established debates in the light of accumulating British Neolithic evidence and via the greater analytical power and flexibility afforded by recent computational methods. Our analyses make a case that spatial distributions of prehistoric axeheads cannot be explained merely as the result of uneven resource availability in the landscape, but instead reflect the active favouring of particular sources over known alternatives. Above and beyond these patterns, we also demonstrate that more populated parts of Early Neolithic Britain were an increased pull factor affecting the longer-range distribution of these objects.

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Section: Methodsmentioning

confidence: 99%