当前位置: X-MOL 学术Journal of Anthropological Archaeology › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Social networks and community features: Identifying neighborhoods in a WWII Japanese American incarceration center
Journal of Anthropological Archaeology ( IF 2.312 ) Pub Date : 2023-04-20 , DOI: 10.1016/j.jaa.2023.101507
April Kamp-Whittaker

Socially defined neighborhoods develop through frequent face to face interactions among residents and their self-identification as neighbors. While archaeological evidence of neighborhoods is usually dependent on artifact frequencies, boundaries, or shared features, this paper explores how effectively communal features act as proxies for social interactions. Network data drawn from historic newspapers published by incarcerees at Amache, a WWII Japanese American Incarceration Center, is used to recreate networks of interaction between residents of a block – a spatial unit generally viewed as a neighborhood, that housed between 200 and 350 individuals. Within a sample of surveyed residential areas, these interpersonal networks of published social events are compared to the frequency of community landscape features to see how well archaeological remains correspond to historic network data in identifying socially defined neighborhoods archaeologically. All blocks exhibit neighborhood-like social interaction within one or the other dataset, but not always in both suggesting that archaeological research should test multiple datasets to make more robust interpretations about neighborhoods in the past.



中文翻译:

社交网络和社区特征:识别二战日裔美国人监禁中心的社区

社会定义的社区通过居民之间频繁的面对面互动和他们作为邻居的自我认同而发展。虽然社区的考古证据通常取决于人工制品频率、边界或共享特征,但本文探讨了公共特征如何有效地充当社会互动的代理。从二战日裔美国人监禁中心 Amache 的监禁者出版的历史报纸中提取的网络数据被用来重建街区居民之间的互动网络——一个空间单元通常被视为一个社区,容纳 200 至 350 人。在调查的住宅区样本中,将这些已发布的社会事件的人际网络与社区景观特征的频率进行比较,以了解考古遗迹与历史网络数据在考古学上识别社会定义的社区方面的对应程度。所有街区在一个或另一个数据集中都表现出类似邻里的社会互动,但并不总是在这两个数据集内,这表明考古研究应该测试多个数据集,以便对过去的邻里做出更可靠的解释。

更新日期:2023-04-20
down
wechat
bug