从科学到政策的跨领域知识扩散特征研究:来自Overton数据的证据

Q3 Social Sciences
Chao Ren, Menghui Yang
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引用次数: 0

摘要

从科学到政策的跨领域知识扩散是一个普遍存在的现象,需要引起学术界的关注。为了研究科学到政策的跨领域知识扩散的特征,本研究建议使用政策到科学文章的引用作为量化传播强度、广度和速度的基础。研究表明,从科学论文到政策的跨领域知识扩散的强度和广度服从幂律分布,而速度服从对数正态分布。传播强度、广度和传播速度最高的论文主要来自世界知名大学、学者和顶级期刊。扩散强度和广度最高的论文多来自社会科学,尤其是经济学,扩散速度最快的论文主要来自医学和生命科学,其次是社会科学。研究结果表明,从科学到政策的跨领域知识扩散遵循马太效应,即学术成就高的个人或机构更有可能实现成功的跨领域知识扩散。此外,经济学领域的论文具有更高的跨领域知识扩散强度和广度,而医学和生命科学领域的论文具有更快的跨领域知识扩散速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on the Characteristics of Cross‐Domain Knowledge Diffusion from Science to Policy: Evidence from Overton Data
ABSTRACT The cross‐domain knowledge diffusion from science to policy is a prevalent phenomenon that demands academic attention. To investigate the characteristics of cross‐domain knowledge diffusion from science to policy, this study suggests using the citation of policies to scientific articles as a basis for quantifying the diffusion strength, breadth, and speed. The study reveals that the strength and breadth of cross‐domain knowledge diffusion from scientific papers to policies conform to a power‐law distribution, while the speed follows a logarithmic normal distribution. Moreover, the papers with the highest diffusion strength, breadth, and fastest diffusion speed are predominantly from world‐renowned universities, scholars, and top journals. The papers with the highest diffusion strength and breadth are mostly from social sciences, especially economics, those with the fastest diffusion speed are mainly from medical and life sciences, followed by social sciences. The findings indicate that cross‐domain knowledge diffusion from science to policy follows the Matthew effect, whereby individuals or institutions with high academic achievements are more likely to achieve successful cross‐domain knowledge diffusion. Furthermore, papers in the field of economics tend to have the higher cross‐domain knowledge diffusion strength and breadth, while those in medical and life sciences have the faster cross‐domain knowledge diffusion speed.
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来源期刊
Proceedings of the Association for Information Science and Technology
Proceedings of the Association for Information Science and Technology Social Sciences-Library and Information Sciences
CiteScore
1.30
自引率
0.00%
发文量
164
期刊介绍: Information not localized
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