评估不同时期经济不平等的宏大叙事

IF 9.1 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Gary M. Feinman, Gabriela Cervantes Quequezana, Adam Green, Dan Lawrence, Jessica Munson, Scott Ortman, Cameron Petrie, Amy Thompson, Linda M. Nicholas
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引用次数: 0

摘要

长期根深蒂固的宏大叙事将大规模人类群体中的不平等与一般的线性趋势联系在一起,这是驯化的直接结果,然后由人口增长和/或人类制度等级复杂性的阶梯式标量转变所促进。人们认为,这种普遍模式只有在灾难性灾难或社会崩溃的情况下才会短路或逆转。然而,在很大程度上,这些普遍确定性框架是根据历史或人种学的快照构建的,对人类机构或机构的系统关注很少。在这里,我们利用定量的、暂时定义的考古和人种学数据,这些数据来自一系列全球地区,其中大部分地区都经历了城市化和复杂的等级形成过程,来研究不平等程度随时间的变化。虽然广泛的时间模式得到了证明,但不平等的区域趋势既不是线性的,均匀的,也不是由马尔萨斯动力学或标量增长立即或机械地触发的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing grand narratives of economic inequality across time
Long-entrenched grand narratives have tied inequality in large human aggregations to generally linear trends, a direct outcome of domestication, then fostered by population growth and/or stepped scalar transitions in the hierarchical complexity of human institutions. This general pattern has been argued to short-circuit or reverse only in the context of cataclysmic disasters or societal breakdowns. Yet, for the most part, these universal deterministic frameworks have been constructed from historical or ethnographic snapshots in time and afford little systematic attention to human institutions or agency. Here, we leverage quantitative, temporally defined archaeological, and ethnographic data from a suite of global regions, most of which transitioned through the process of urbanism and complex hierarchy formation, to examine shifts in degrees of inequality over time. Although broad temporal patterns are evidenced, the regional trends in inequality are neither linear, uniform, nor triggered immediately or mechanically by Malthusian dynamics or scalar increases.
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来源期刊
CiteScore
19.00
自引率
0.90%
发文量
3575
审稿时长
2.5 months
期刊介绍: The Proceedings of the National Academy of Sciences (PNAS), a peer-reviewed journal of the National Academy of Sciences (NAS), serves as an authoritative source for high-impact, original research across the biological, physical, and social sciences. With a global scope, the journal welcomes submissions from researchers worldwide, making it an inclusive platform for advancing scientific knowledge.
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