Quality Research Follows the Power Law

IF 0.6 Q3 INFORMATION SCIENCE & LIBRARY SCIENCE Journal of Scientometric Research Pub Date : 2023-11-30 DOI:10.5530/jscires.12.3.054
Hanbin Mao, Jixin Chen
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Abstract

Research output can be evaluated with productivity and impact, which are quantified by the numbers of publications ( N ) and citations N c , respectively. The h -index ( H ) unifies both factors. However, as an extensive variable, it grows with quantity of research output and favors senior researchers over juniors. In this report, by analyzing the data of the world top 2% scientists ( n = 179,597) from an online database, we found that h -index follows power laws and proposes a different model from what Hirsch has originally proposed. We propose intensive indices ( Q N and Q C ) to measure quality research by comparing the actual h -index of a researcher with the power-law fitted h -indices from the top 2% scientists with the same numbers of publications and citations respectively. We further calculated a dynamic research quality ( Q 1 = Q N / Q C ) and a reduced index ( Q 2 =( Q N Q C ) 0.5 ) to evaluate research quality over time. We rationalized that the power law dependency of quality research is due to its heterogeneous production pathways that require extra effort with respect to “regular” research output. We found that research quality for the top 2% scientists is maximized with ~100 citations/paper and with about ~100 publications. A major advantage of these indices is that they are relative to the academic peers with similar accomplishments in publications and citations, and therefore, are independent of career stages. Since Q indices are positively correlated with H/N ratios, the research quality can also be quickly and conveniently estimated by the readily accessible values calculated using the equation H/ (N)^(2/3) or H/(Nc)^(1/2) .
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质量研究遵循幂律
研究成果可以用生产率和影响力来评估,生产率和影响力分别用出版物数量(N)和引用次数(N c)来量化。h 指数(H)将这两个因素统一起来。然而,作为一个广泛的变量,它随着研究成果数量的增加而增长,并有利于资深研究人员而非年轻研究人员。在本报告中,通过分析在线数据库中世界排名前 2% 的科学家(n = 179 597)的数据,我们发现 h 指数遵循幂律,并提出了与赫希最初提出的不同的模型。我们提出了密集指数(Q N 和 Q C),通过比较研究人员的实际 h 指数和前 2% 科学家的幂律拟合 h 指数(发表论文数和引用次数分别相同)来衡量研究质量。我们还计算了动态研究质量(Q 1 = Q N / Q C)和缩减指数(Q 2 =( Q N Q C ) 0.5),以评估随时间变化的研究质量。我们认为,高质量研究的幂律依赖性是由于其生产途径的异质性,与 "常规 "研究成果相比,需要付出额外的努力。我们发现,排名前 2% 的科学家的研究质量在约 100 次引用/篇论文和约 100 篇论文时达到最高水平。这些指数的一个主要优点是,它们是相对于在论文和引用方面取得类似成就的学术同行而言的,因此与职业阶段无关。由于 Q 指数与 H/N 比值呈正相关,因此也可以通过使用公式 H/ (N)^(2/3) 或 H/(Nc)^(1/2) 计算出的现成值,快速方便地估算出研究质量。
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来源期刊
Journal of Scientometric Research
Journal of Scientometric Research INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
1.30
自引率
12.50%
发文量
52
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