摘要
本文介绍了"Seshat全球史数据库"项目及其所基于的方法论,以及它作为历史学者与其他人文学者一种研究工具的潜力。Seshat是一个综合性数据集,涵盖了自新石器时代以来人类文化演进的数据。本文详细描述了如何运用Seshat方法和平台来研究长时段尺度下的重要问题,同时让用户能够深入钻研细节、将每个数据点置于历史与史学编纂的情景之中。因此,Seshat为长时段历史研究提供了一个以严格方法论为基础的平台,本文也提倡人文与社科学者参与到基于数据驱动的长时段历史研究中来。本文认为,Seshat提供了一个急需的基础设施,在此之上,不同技能和学科背景的学者能够协同从长时段尺度分析过往历史。除了论及理论与方法论的支撑,本文还通过三个研究案例证明了Seshat的潜力。每一个案例都围绕着一系列长期存在的研究议题与史学争议,而Seshat的引入被认为有望彻底改变我们对这些议题的理解。
This article introduces the"Seshat:Global History"project,the methodology it is based upon and its potential as a tool for historians and other humanists.Seshat is a comprehensive dataset covering human cultural evolution since the Neolithic.The article describes in detail how the Seshat methodology and platform can be used to tackle big questions that play out over long time scales whilst allowing users to drill down to the detail and place every single data point both in its historic and historiographical context.Seshat thus offers a platform underpinned by a rigorous methodology to actually do longue duree history and the article argues for the need for humanists and social scientists to engage with data driven longue duree history.The article argues that Seshat offers a much-needed infrastructure in which different skill sets and disciplines can come together to analyze the past using long timescales.In addition to highlighting the theoretical and methodological underpinnings,Seshat’s potential is demonstrated using three case studies.Each of these case studies is centred around a set of longstanding questions and historiographical debates and it is argued that the introduction of a Seshat approach has the potential to radically alter our understanding of these questions.
作者
闵超(译)
Pieter François;J.G.Manning;Harvey Whitehouse;Thomas Currie;Kevin Feeney;Peter Turchin
出处
《全球史评论》
2020年第2期-,共22页
Global History Review
基金
约翰·邓普顿基金会项目“人类平等主义的轴心时代宗教与Z曲线”
三兴基金会授予演化研究所的项目“现代世界的深层根基:经济增长与政治稳定的文化演进”、英国经济和社会研究理事会授予牛津大学的项目“宗教仪式、社群与冲突”(编号RES-060-25-0085)
欧盟地平线2020研究与创新计划项目(编号644055[ALIGNED,www.aligned-projecteu])的资助
关键词
数据采集方法论
数据提取
全球史
Data Harvesting Methodology
Data Extraction
Global History
