1. Introduction

This article outlines the approaches of the research project, 'Engendering Roman Spaces', which commenced in 2001. In this project GIS visualisation assists the detailed, small-scale analyses of inter- and intra-site distribution patterns of artefacts that have been assigned social significance, or more specifically task and gender values. This particular project investigates small-scale, intra-site patterning within structurally defined areas using 'legacy data' and pseudo-GIS environments. In addition, it uses the spatial analyses of socially classified data to investigate social, and particularly gendered, behaviour (for full publication: Allison forthcoming).

In discussing the mapping of gendered behaviour, Silvia Tomášková recently questioned (2006, 25) 'whether [GIS] is the best tool for all the questions we may wish to ask'. She cited feminist geographers (e.g. Kwan 2002a, 2002b) as questioning the usefulness of GIS techniques for such interpretative and qualitative investigations. However, contra Tomášková, Kwan (2002a, esp. 272-4) advocated that GIS techniques are indeed useful for both 'quantitative/empiricist' and critical/qualitative analyses. She called for 'more diverse and nuanced reading of complex relationships among GIS technology, data, social and political institutions, application contexts, and the agency of the actors involved'.

As mentioned in the introduction to this volume, I am concerned with processes for dealing with data of uncertain meaning or significance and this is particularly pertinent to processes for the social and gender classification of archaeological data and to Tomášková's 'multiple plausible scenarios' in investigations of the data (Tomášková 2006, 25). Using Hans-Jürgen Zimmermann's language concerning Fuzzy Set Theory and its application to Fuzzy Logic and Fuzzy Data analysis, I am interested in uncertainty and imprecision resulting from an 'absence of sharply defined criteria of class-membership rather than the presence of random variables' (Zimmermann 2001, 6). The imprecision in the 'Engendering Roman Spaces' project involves a 'vagueness' in the meaning of the data and not simply 'a lack of knowledge' about it.

Two of our main problems in archaeology are, firstly, the randomness of our sample and, secondly, our lack of precise knowledge about past human social behaviour. We tend to believe that we can compensate for the former by choosing a large sample. I believe that the imposition of a condition of 'vagueness ... about the value of a parameter' (Zimmermann 2001, 6) can serve to compensate for our lack of knowledge about meaning and significance in the past, knowledge that may only ever be partially achievable (see also Hermon et al. 2004).

In this project I am concerned with imprecision and uncertainty on two levels: uncertainty about the identification of the activities with which particular artefacts would have been associated; and uncertainty about the social and gender identities of the people associated with such activities. For example, particular types of bone, ceramic and stone discs may have been used as spindle whorls and spinning seems to have been a female activity in the Roman world. The concepts of uncertainty in Fuzzy Set Theory as deriving from a continuum of related values; as involving the intersections and unions of a number of sets; and as being related to degrees of membership of a set or a union of sets, seem to fit well with my own data and objectives, and to validate the use of GIS techniques to present and analyse socially classified data.

In his definition of fuzzy data analysis, Zimmermann (2001, 279) presents four possibilities for data classification: crisp objects and crisp classes; crisp objects and fuzzy classes; fuzzy objects and crisp classes; and fuzzy objects and fuzzy classes. My data, and indeed most archaeological data, fall into Zimmermann's first, second and fourth possibilities. Without a precise identification of the actual artefacts it is difficult, if not impossible, to assign them to a specific type or class. But my two levels of uncertainty also constitute two levels of more or less 'fuzzy' classes. Given both the quantity and quality of these data and their respective classes, any attempts to model them mathematically, and then relate that modelling to their GIS presentation, is likely to ascribe an unjustifiable level of precision. However, Zimmermann's distinction between 'mathematical pattern recognition' and more context-dependent 'non-mathematical pattern recognition', and his comment that the most effective search procedure is the 'eyeball' technique (Zimmermann 2001, 277-8), suggests that a more straightforward GIS environment is probably an ideal environment in which to analyse such data.

In the 'Engendering Roman Spaces' project, a GIS-type environment is used to visualise and analyse artefact distribution patterns in 1st- and 2nd-century Roman military bases to investigate for the presence and roles of women and children within these, traditionally viewed, male-dominated domains.


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