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基于复杂网络映射发展的全球排名的股权导向性再思考。

An equity-oriented rethink of global rankings with complex networks mapping development.

机构信息

Dipartimento Interateneo di Fisica "M. Merlin", Università degli Studi di Bari "A. Moro", 70126, Bari, Italy.

Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125, Bari, Italy.

出版信息

Sci Rep. 2020 Oct 22;10(1):18046. doi: 10.1038/s41598-020-74964-3.

Abstract

Nowadays, world rankings are promoted and used by international agencies, governments and corporations to evaluate country performances in a specific domain, often providing a guideline for decision makers. Although rankings allow a direct and quantitative comparison of countries, sometimes they provide a rather oversimplified representation, in which relevant aspects related to socio-economic development are either not properly considered or still analyzed in silos. In an increasingly data-driven society, a new generation of cutting-edge technologies is breaking data silos, enabling new use of public indicators to generate value for multiple stakeholders. We propose a complex network framework based on publicly available indicators to extract important insight underlying global rankings, thus adding value and significance to knowledge provided by these rankings. This approach enables the unsupervised identification of communities of countries, establishing a more targeted, fair and meaningful criterion to detect similarities. Hence, the performance of states in global rankings can be assessed based on their development level. We believe that these evaluations can be crucial in the interpretation of global rankings, making comparison between countries more significant and useful for citizens and governments and creating ecosystems for new opportunities for development.

摘要

如今,国际机构、政府和企业都在推广和使用世界排名,以评估各国在特定领域的表现,这通常为决策者提供了一个指导方针。尽管排名允许对各国进行直接和定量的比较,但有时它们提供的是一种相当简化的表示,其中与社会经济发展相关的方面要么没有得到适当考虑,要么仍然是孤立地进行分析。在一个日益数据驱动的社会中,新一代的前沿技术正在打破数据孤岛,使人们能够利用公共指标产生新的价值,为多方利益相关者服务。我们提出了一个基于公开指标的复杂网络框架,以提取全球排名背后的重要见解,从而为这些排名提供的知识增加价值和意义。这种方法可以实现对国家社区的无监督识别,建立一个更有针对性、更公平和更有意义的标准来检测相似性。因此,可以根据各国的发展水平来评估它们在全球排名中的表现。我们相信,这些评估在全球排名的解释中至关重要,使国家之间的比较更加有意义和有用,为公民和政府创造了新的发展机会生态系统。

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