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New methodological approaches focused on studying the reduction and use-life of stone tools have emerged in recent years, enabling researchers to move beyond strict technical and technological characterizations and explore specific aspects of occupation dynamics and economic management of resources. Previous studies have shown the importance of reduction distributions of individual measurements rather than averaged values. In this sense, survival analysis, and more specifically Weibull distributions, are one of the main inferential tools used in reduction studies. However, the resolution of Weibull distribution obtained from different methods has not been tested experimentally. In this paper, we present an evaluation of some of the main methods used in the study of core reduction intensity, such as the Volumetric Reconstruction Method, the Scar Density Index, and the non-cortical surface percentage. Our results show 1) strong and positive correlations between these approaches and actual reduction intensity, 2) similar Weibull distributions for non-cortical surface percentage, Volumetric Reconstruction Method, and logarithmic transformation of Scar Density Index. In addition, 3) the results from each method show a similar intra-assemblage variation, with a high percentage of agreement between them. As a result, all the evaluated proposals are useful and reliable methods for estimating the degree of reduction. Finally, a workflow is proposed for approaching reduction in archaeological assemblages by integrating different methods in the same study. This work has been carried out with the financial support of the Generalitat de Catalunya, AGAUR agency (2017SGR1040 Research Group), the Universitat Rovira i Virgili (2019PFR-URV-91), and the Spanish Ministry of Science, Innovation and Universities (MICINN/FEDER project PGC2018-093925-B-C32). The Institut Català de Paleoecologia Humana i Evolució Social (IPHES-CERCA) has received financial support from the Spanish Ministry of Science and Innovation through the “María de Maeztu” program for Units of Excellence (CEX2019-000945-M). D.L. is funded by Post-Doc Xunta de Galicia Grant (ED481B_2022_048). J.R.R. is a beneficiary of a Margarita Salas postdoctoral fellowship (MARSALAS21-22) funded by the Spanish Ministry of Universities, the European Union-Next Generation EU, and the University of Alicante. A.C.-T. is grateful to the Max Planck Society for funding. The research of J.I.M. was supported by the Spanish Ministry of Science and Innovation through the “María de Maeztu” excellence accreditation (CEX2019-000945-M). |
