The conundrum of castration in the archaeological record: An interpretation of Roman cattle horn-cores from Chelmsford,Essex

Current methods of sexing archaeological cattle bones, in particular the metapodials, are based upon past research into contemporary breeds and this work embraces a limited sample size, spread across a vast geographical area. Although the separation of cows and bulls is not in question, there appears a great deal of subjectivity in the literature concerning the identification of castrated beasts. Living bone is in a dynamic state of equilibrium with the rest of the body and responds to increased loading, that is, an increase in weight of the beast or stress/strain through strenuous movement, by remodelling. If cows and oxen are performing the same work, as for example in ploughing, then loading on the bones will be similar. These bones will thus respond by remodelling in corresponding fashion, and hence any morphological and metrical distinctions will be clouded. Horn-cores are less subject to these constraints, although in some cultures there may be loading on these bones, for example through attaching the harness to the horns for ploughing. The Chelmsford cattle horn-cores constitute waste from some industrial activity and it is argued in the text that horn-working is the most likely candidate, together with possibly tanning. Sexing of the bones strongly indicated male animals, with few females being present. A procedure for detecting castrated cattle (oxen) is presented, the results of which suggest an equivalent ratio of oxen to bulls.     

THE KNIGHTS OF LABOR DATA-BANK

Several countries have made large investments in building historical Geographical Information Systems (GIS) databases containing census and other quantitative statistics over long periods of time. Making good use of these databases requires approaches that explore spatial and temporal change. The authors use a variety of visualization and spatial analysis techniques to explore population change in Ireland during and after the Great Famine of the late 1840s. Importantly, the techniques allow differences over space and time to be explored, thus stressing the diversity between places, rather than making all places appear the same, a common criticism of many statistical approaches. The authors demonstrate the potential of these techniques to explore geographical and temporal variations in large quantitative GIS datasets.