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Entropology: an Information-Theoretic Approach to Understanding Archaeological Data
Journal of Archaeological Method and Theory ( IF 3.073 ) Pub Date : 2023-11-03 , DOI: 10.1007/s10816-023-09627-4
Paula Gheorghiade , Vaiva Vasiliauskaite , Aleksandr Diachenko , Henry Price , Tim Evans , Ray Rivers

The main objective of this paper is to develop quantitative measures for describing the diversity, homogeneity, and similarity of archaeological data. It presents new approaches to characterize the relationship between archaeological assemblages by utilizing entropy and its related attributes, primarily diversity, and by drawing inspiration from ecology. Our starting premise is that diachronic changes in our data provide a distorted reflection of social processes and that spatial differences in data indicate cultural distancing. To investigate this premise, we adopt a parsimonious approach for comparing assemblage profiles employing and comparing a range of (Hill) diversities, which enable us to exploit different aspects of the data. The modelling is tested on two seemingly large datasets: a Late Bronze Age Cretan dataset with circa 13,700 entries (compiled by PG); and a 4th millennium Western Tripolye dataset with circa 25,000 entries (compiled by AD). The contrast between the strongly geographically and culturally heterogeneous Bronze Age Crete and the strongly homogeneous Western Tripolye culture in the Southern Bug and Dnieper interfluve show the successes and limitations of our approach. Despite the seemingly large size of our datasets, these data highlight limitations that confine their utility to non-semantic analysis. This requires us to consider different ways of treating and aggregating assemblages, either as censuses or samples, contingent upon the degree of representativeness of the data. While our premise, that changes in data reflect societal changes, is supported, it is not definitively confirmed. Consequently, this paper also exemplifies the limitations of large archaeological datasets for such analyses.



中文翻译:

熵学:理解考古数据的信息论方法

本文的主要目的是开发定量方法来描述考古数据的多样性、同质性和相似性。它提出了利用熵及其相关属性(主要是多样性)并从生态学中汲取灵感来表征考古组合之间关系的新方法。我们的起始前提是,数据的历时变化提供了社会进程的扭曲反映,而数据的空间差异表明了文化距离。为了研究这个前提,我们采用一种简约的方法来比较组合剖面,使用和比较一系列(希尔)多样性,这使我们能够利用数据的不同方面。该模型在两个看似大型的数据集上进行了测试:青铜时代晚期克里特岛数据集,包含约 13,700 个条目(由 PG 编译);以及第四个千年的 Western Tripolye 数据集,包含约 25,000 个条目(由 AD 编译)。青铜时代克里特岛在地理和文化上具有强烈的异质性,与南布格河和第聂伯河交汇处具有强烈同质性的西方特里波耶文化之间的对比显示了我们方法的成功和局限性。尽管我们的数据集看似很大,但这些数据凸显了其实用性仅限于非语义分析的局限性。这要求我们根据数据的代表性程度,考虑以不同的方式处理和汇总组合,无论是普查还是样本。虽然我们的前提是数据的变化反映了社会的变化,这一前提得到了支持,但尚未得到明确证实。因此,本文还举例说明了大型考古数据集用于此类分析的局限性。

更新日期:2023-11-03
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