Abstract
Categorical variables identifying microscopic features of cut marks produce high accuracy in discrimination of bone surface modifications, but are vulnerable to variable degrees of inter-analyst subjectivity. Metric analyses of cut mark width and depth are presented by Merritt et al. (2018) as a more objective method of identifying cut marks. However, this uni(bi)variate method has shown very high rates of mark classification error when structurally similar marks are compared. Furthermore, within-sample comparison carried out via subsampling shows that different datasets of metric values, obtained with the same type of tool and raw material, are subject to such a high degree of variability that significant differences of homogeneous subsamples are repeatedly obtained, thus preventing any useful analogs to be made. Additionally, this much higher stochastic variability depends on limited knowledge of the contextual processes that intervene in cut mark metric properties, as well as on a mismatch between theoretical premises on the immanent-configurational process-trace dynamics and their confusion during experimental praxis. The selection of specific contextual variables and disregard of others, in addition to the combination of different tool types and raw materials, distorts the resulting cut mark properties. This indicates that even when attempting to use exclusively metric numeric variables, subjectivity is a conditioning factor in analyzing and interpreting cut marks.
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