Normative versus strategic accounts of acknowledgment data: The case of the top-five journals of economics

被引:10
作者
Baccini, Alberto [1 ]
Petrovich, Eugenio [1 ]
机构
[1] Univ Siena, Dept Econ & Stat, Siena, Italy
关键词
Acknowledgments analysis; Scientific collaboration; Quantitative studies of science; Top five journals of economics; Directed network analysis; Intellectual and social similarity; Symmetric acyclic decomposition; CUMULATIVE ADVANTAGE; COLLABORATION; AUTHORSHIP; COMMUNICATION; 20TH-CENTURY; CITATIONS; GRATITUDE; PATTERNS; ENGLISH; SCIENCE;
D O I
10.1007/s11192-021-04185-6
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Two alternative accounts can be given of the information contained in the acknowledgments of academic publications. According to the mainstream normative account the acknowledgments serve to repay debts towards formal or informal collaborators. According to the strategic account, by contrast, the acknowledgments serve to increase the perceived quality of papers by associating the authors to influential scholars. The two accounts are assessed by analyzing the acknowledgments indexed in Web of Science of 1218 articles published in the "top-five journals" of economics for the years 2015-2019. The analysis is focused on six dimensions: (i) the style of acknowledging texts, (ii) the distribution of mentions, (iii) the identity of the most mentioned acknowledgees, (iv) the shares of highly and lowly mentioned acknowledgees, (v) the hierarchy of the acknowledgment network, and (vi) the correlation at a paper level between intellectual similarity, measured by common references, and social similarity, measured by common acknowledges. Results show that the normative and the strategic account should be considered as valid but partial explanations of acknowledging behavior. Hence, acknowledgments should be used with extreme caution for investigating collaboration practices and they should not be used to produce acknowledgments-based metrics of scholars for evaluative purposes.
引用
收藏
页码:603 / 635
页数:33
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