H-Index Has More Than Quantity (Publication Productivity) And Quality (Citation Impact) Nomological Dimensions

J. Balogun, Efe Mamuzo, F. Okonofua, Adetutu O. Balogun, Adetoyeje Y. Oyeyemi
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Abstract

Of all the bibliometric parameters, the h-index is the most widely used to gauge the academic productivity and contribution to disciplines. In 2005, Hirsch proposed the h-index as a robust indicator of the quantity (number of publications) and quality (impact of the citations) of a scientific publication, but this speculation has not been empirically tested. This investigation determined the contributions of quantity and quality dimensions to the prediction of h-index and identify which of the dimension is the most viable in predicting it. The h-index, total number of publications, citation, and co-authorship counts for the 80 medical and health sciences fellows of the African Academy of Sciences were obtained from the Scopus database. The h-index is significantly related to publication (r = .388, p<.001), citation (r = .309, p<.01) and co-authorship (r = .246, p<.05) counts. The three independent variables combined significantly predicted h-index (F (3, 76) = 4.68, p<.01, R2 = .156). Although the regression model is a good fit for the data, only 15.6% of the variance in h-index was accounted for by the three bibliometric parameters. Publication count is the only viable predictor, explaining 15.1% out of the 15.6% total variability in the h-index. The remaining 84.4% variance that is unexplained in this study suggests that h-index has more than the quantity and quality nomological dimensions. Follow up studies should explore the predictive viability of other bibliometric measures such as the number of “reads,” book and chapter authorships, invited presentation engagements and conference proceedings.
H-Index不仅具有数量(出版效率)和质量(引用影响)的法理维度
在所有的文献计量参数中,h指数被最广泛地用于衡量学术生产力和对学科的贡献。2005年,Hirsch提出将h指数作为科学出版物数量(出版物数量)和质量(引用影响)的有力指标,但这一推测尚未得到实证检验。本研究确定了数量维度和质量维度对h指数预测的贡献,并确定了哪一个维度在预测h指数时最可行。从Scopus数据库中获得了非洲科学院80名医学和健康科学研究员的h指数、出版物总数、引文数和共同作者数。h-index与发表数(r = 0.388, p< 0.001)、被引数(r = 0.309, p< 0.01)和合著数(r = 0.246, p< 0.05)显著相关。三个自变量联合显著预测h指数(F (3,76) = 4.68, p<。0.01, r2 = .156)。虽然回归模型很好地拟合了数据,但三个文献计量参数仅占h指数方差的15.6%。发表数是唯一可行的预测因子,解释了h指数15.6%总变异性中的15.1%。剩余的84.4%的方差在本研究中无法解释,这表明h-index具有比数量和质量更多的形态学维度。后续研究应该探索其他文献计量指标的预测可行性,如“阅读”次数、书籍和章节作者、受邀演讲和会议记录。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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