Identifying the accumulator: Making the most of bone surface modification data
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Identifying the accumulator: Making the most of bone surface modification data

机译:识别累加器:使大部分骨表面修改数据

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Abstract Taphonomic analysis is an essential component of zooarchaeology, but is employed in different ways within different research traditions. Within the Africanist Palaeolithic literature, there is a strong emphasis on quantitative comparison of proportions of different bone surface modifications to one another and to proportions observed on modern experimental collections. This work has been driven by debates about the taphonomic histories of Oldowan sites that document the subsistence strategies of early Homo, but this specific approach can be usefully applied to a range of contexts across many different time periods and geographic locations. One obstacle to the cross-fertilization of this taphonomic tradition with other zooarchaeological work is the restrictive manner in which data are selected from an assemblage for analysis. To ensure comparability between fossil and modern assemblages, analysts typically exclude specimens with evidence for post-depositional modification not modeled in the experimental data. Although this adds interpretive robustness, it can diminish sample size significantly, sometimes to the point of affecting statistical analyses, and results in much time invested in collecting data that ultimately are not used. Here, we describe a new method for maximizing the number of specimens that can be incorporated into analysis, thus resolving the persistent problem of poor sample sizes to make more statistically robust comparisons to actualistic datasets. Highlights ? Bone surface modifications (BSM) are critical for identifying taphonomic processes. ? BSM analysis varies between research traditions and standardization is needed. ? Quantitative comparisons to experimental collections can identify accumulators. ? Quantitative comparisons to experimental collections do not maximize available data. ? A revised approach maximizes analytical power by including all available data. ]]>
机译:摘要埋藏组学分析是动物考古学的一个重要组成部分,但在不同的研究传统中以不同的方式使用。在非洲旧石器时代文献中,非常强调不同骨表面修饰的比例之间的定量比较,以及与现代实验收藏中观察到的比例之间的定量比较。这项工作通过对记录早期人类生存策略的Oldowan遗址埋藏史的辩论,但这种特定的方法可以有效地应用于跨越许多不同时间段和地理位置的一系列背景。这种隐音学传统与其他动物考古学工作交叉融合的一个障碍是从集合中选择数据进行分析的限制性方式。为了确保化石和现代组合之间的可比性,分析人员通常会排除有实验数据中未建模的沉积后改造证据的样本。虽然这增加了解释的稳健性,但它可以显著减少样本量,有时甚至会影响统计分析,并导致在收集最终未使用的数据时投入大量时间。在这里,我们描述了一种新的方法,用于最大限度地增加可纳入分析的样本数量,从而解决了长期存在的样本量不足的问题,以便与现实数据集进行更具统计稳健性的比较突出显示骨表面修饰(BSM)对于识别埋藏过程至关重要。BSM分析因研究传统而异,需要标准化。与实验收集的定量比较可以识别累加器。与实验收集的定量比较不能最大化可用数据。修订后的方法通过包含所有可用数据来最大限度地提高分析能力。]>

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