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Nuances of What? Burials as Relational Configurations
Norwegian Archaeological Review ( IF 0.8 ) Pub Date : 2018-07-03 , DOI: 10.1080/00293652.2018.1532965
Fredrik Fahlander

I very much welcome the opportunity to comment on Mark Haughton’s study of social relations in local burial grounds. The proposition to emphasise nuances in burial analysis is especially welcome in times flooded with large-scale studies based on isotope – and aDNA signatures. I find much to agree with in the text and will take some of the arguments as grounds for further exploration. My commentary will focus on three areas: the question of scale and scope, social complexity, and the formation of burial assemblages. Haughton expresses concerns for how largescale statistical analyses principally tend to treat different burial grounds from approximately the same period as analytically one. The problems with such approaches are well known. Grand scale analyses of the burial practices of a larger region have a tendency to underestimate the potential of local variability (as Haughton’s own case study shows). A perhaps more problematic issue is that large-scale analysis, treating all burials as more or less contemporary, is seldom able to detect subtle changes in burial ritual and/or social relations. Large-scale datasets thus run the risk of homogenising each period and generate a totality that was never really experienced nor lived by anyone. As Marilyn Strathern puts it: ‘patterns themselves may be regular without being similar, or similar without being regular’ (Strathern 1991, p. xxiii). It could, of course, be argued that the whole point of large-scale studies is to sift out the ‘major’ trends and tendencies. Be that as it may, we should always remember that the seemingly objective percentages and numbers of large-scale analyses normally build upon subjective and qualitative interpretations on the small scale. On the other side of the coin, local and small-scale analyses are no less problematic. A small grave field is not necessarily representative even for local social relations or ideologies. There can be several generations between the earliest and the latest grave, individual burial grounds for different social collectives, and a portion of the population may not have received burial at all. The fact that a burial is an event related to the death of an individual makes the representative value of each grave uncertain. Burial grounds are rarely planned compositions, but perhaps best characterised by improvisation and necessity. InHaughton’s example, children are only buried together with adults. To me, this implies that children are buried only when the death of a child coincides with the death of an adult (if not burials are subsequently added to the cist). While I agree with Haughton about the problems of generalisation, we should nonetheless be careful to maintain a dichotomy between the local and particular on the one hand and the general and large scale on the other. The same is also true for the different techniques and methods. Statistical analysis

中文翻译:

什么的细微差别?作为关系配置的墓葬

我非常欢迎有机会评论 Mark Haughton 对当地墓地社会关系的研究。在充斥着基于同位素和 aDNA 特征的大规模研究的时代,强调埋葬分析中细微差别的提议尤其受欢迎。我在文本中发现很多同意的地方,并将把一些论点作为进一步探索的基础。我的评论将集中在三个领域:规模和范围问题、社会复杂性以及墓葬组合的形成。Haughton 表达了对大规模统计分析如何主要倾向于将几乎同一时期的不同墓地视为分析地的担忧。这种方法的问题是众所周知的。对更大区域的埋葬实践进行大规模分析倾向于低估当地可变性的潜力(正如 Haughton 自己的案例研究所示)。一个可能更成问题的问题是,将所有墓葬或多或少都视为当代的大规模分析很少能够发现墓葬仪式和/或社会关系的微妙变化。因此,大规模数据集冒着将每个时期同质化的风险,并产生一个从来没有人真正体验过或生活过的总体。正如 Marilyn Strathern 所说:“模式本身可能是规则而不相似,或者相似而不是规则”(Strathern 1991,p. xxiii)。当然,可以说大规模研究的全部意义在于筛选出“主要”趋势和趋势。是因为它可能,我们应该永远记住,大规模分析的看似客观的百分比和数量通常建立在小规模的主观和定性解释之上。另一方面,本地和小规模分析同样存在问题。即使对于当地的社会关系或意识形态,一个小小的墓地也不一定具有代表性。最早和最晚的坟墓之间可能有几代人,不同社会集体的个人墓地,一部分人口可能根本没有接受过葬礼。埋葬是与个人死亡有关的事件这一事实使得每个坟墓的代表价值不确定。墓地很少是有计划的作品,但也许最好的特点是即兴创作和必要性。以霍顿为例,儿童只与成人葬在一起。对我来说,这意味着只有在儿童的死亡与成人的死亡同时发生时才埋葬儿童(如果不是,随后将埋葬添加到 cist 中)。虽然我同意 Haughton 关于泛化问题的观点,但我们还是应该小心地在一方面保持局部和特殊性,另一方面保持一般性和大规模性之间的二分法。对于不同的技术和方法也是如此。统计分析 尽管如此,我们应该小心地在一方面是局部的和特殊的,另一方面是一般的和大的范围之间保持二分法。对于不同的技术和方法也是如此。统计分析 尽管如此,我们应该小心地在一方面是局部的和特殊的,另一方面是一般的和大的范围之间保持二分法。对于不同的技术和方法也是如此。统计分析
更新日期:2018-07-03
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