Pub Date : 2024-06-28DOI: 10.1007/s11192-024-05088-y
Yannis Tzitzikas, Giorgos Dovas
H-Index is a widely used metric for measuring scientific output. In this paper we showcase the weakness of this index as regards co-authorship. By ignoring the number of co-authors, each author gets the full credit of a joint work, something that is not fair for evaluation purposes. For this purpose we report the results of simulation scenarios that demonstrate the impact that co-authorship can have. To tackle this weakness, and achieve a more fair evaluation, we propose a few simple variations of H-index that consider the number of co-authors, as well as the active time period of a researcher. In particular we propose using HI/co and HI/(coy), two metrics that are simple to understand and compute, and thus they are convenient for decision making. The simulation shows that they can tackle well co-authorship. Subsequently we report measurements over real data of researchers coming from five universities (Cambridge, Crete, Harvard, Oxford and Ziauddin), as well as other datasets, that reveal big variations in the average number of co-authors. In total, we analyzed 526 authors, having in total more than 127 thousands publications, and 16.7 million citations. These measurements revealed big variations of the number of co-authors. Consequently, by including the number of co-authors in the measures for scientific output (e.g. through the proposed HI/co) we get rankings that differ significantly from the rankings obtained by citations, or by the plain H-Index. The normalized Kendall’s tau distance of these rankings ranged from 0.28 to 0.46, which is quite high.
H-Index 是一种广泛使用的衡量科学产出的指标。在本文中,我们展示了该指数在合著方面的弱点。由于忽略了共同作者的人数,每位作者都获得了共同成果的全部荣誉,这对于评估目的来说是不公平的。为此,我们报告了模拟情景的结果,以证明共同作者可能产生的影响。为了解决这个问题,并实现更公平的评估,我们提出了一些简单的 H 指数变体,这些变体考虑了共同作者的数量以及研究人员的活跃时间。我们特别建议使用 HI/co 和 HI/(coy),这两个指标易于理解和计算,因此便于决策。模拟结果表明,这两个指标可以很好地解决合著问题。随后,我们报告了对来自五所大学(剑桥大学、克里特大学、哈佛大学、牛津大学和齐亚丁大学)的研究人员的真实数据以及其他数据集的测量结果,这些数据集揭示了共同作者平均人数的巨大差异。我们总共分析了 526 位作者,他们总共发表了超过 12.7 万篇论文,引用次数超过 1670 万次。这些测量结果表明,共同作者的数量变化很大。因此,通过将共同作者人数纳入科学产出的衡量标准(如通过建议的 HI/co),我们得到的排名与通过引用或普通 H 指数得到的排名有很大不同。这些排名的归一化 Kendall's tau 距离从 0.28 到 0.46 不等,相当高。
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Pub Date : 2024-06-28DOI: 10.1007/s11192-024-05083-3
Jennifer A. Horney, Adam Bitunguramye, Shazia Shaukat, Zackery White
Gender-Based differences in h-indices across fields, including psychology, social work, and the biomedical sciences have been reported. These differences are persistent across all faculty ranks, including assistant, associate, and full professors, but may be larger for early career and senior faculty. Even with these known biases, the h-index remains a widely used metric of the productivity and impact of research scientists and university faculty. Recently, several studies have drawn attention to the potential for a widening gender gap in academic metrics given the ways in which gendered roles, and thus research productivity, were inequitably impacted by the COVID-19 pandemic. We describe the association between gender and h-index among a sample of tenured faculty from epidemiology departments in Schools and Programs of Public Health. Gender explained 1.2% of the variance in h-indices; after adjustment for professional age, gender explained only 0.1% of the variance. There was also crossover interaction for professional age and gender, with women having lower h-indices in early career yet overtaking males later. If h-indices are utilized as metrics for promotion and tenure, or as criteria for appointments to leadership or other roles, gender bias will continue to limit early- and mid-career women’s inclusion and advancement.
据报道,不同领域(包括心理学、社会工作和生物医学)的 h 指数存在性别差异。这些差异在包括助理教授、副教授和正教授在内的所有教职员工职级中都持续存在,但在职业生涯早期和高级教职员工中可能更大。即使存在这些已知的偏差,h 指数仍然是衡量研究科学家和大学教师生产力和影响力的一个广泛使用的指标。最近,几项研究引起了人们对学术指标中性别差距扩大可能性的关注,因为在 COVID-19 大流行病中,性别角色以及研究生产力受到了不公平的影响。我们描述了公共卫生学院和项目流行病学系终身教职员工样本中性别与 h 指数之间的关联。性别解释了 1.2% 的 h 指数差异;在对专业年龄进行调整后,性别仅解释了 0.1% 的差异。职业年龄和性别之间还存在交叉互动,女性在职业生涯早期的 h 指数较低,但在职业生涯后期却超过了男性。如果将 h 指数作为晋升和终身教职的衡量标准,或作为领导或其他职位的任命标准,那么性别偏见将继续限制职业生涯早期和中期女性的融入和晋升。
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Pub Date : 2024-06-28DOI: 10.1007/s11192-024-05089-x
Wenxuan Shi, Renli Wu
Prevailing attention centers on the plight of female scientists in modern academia. However, female contributions and potential remain insufficiently recognized. To unravel this veil, we leverage large-scale cross-disciplinary datasets from SciSciNet to portray female participation over the past 20 years and quantify the female effect on research using bibliometric indicators. Female ratio is utilized to gauge gender composition within teams. Through successive modeling including mixed-effect and multivariate regressions, we disentangle the intricate effects of female presence and extent of female participation on research impact and dual innovation metrics. We find a steady rise in female-inclusive teams and per-team female ratios over time, with variations across disciplines and broad categories. We demonstrate an inverted U-shaped relationship between female ratio and citation counts—gender-balanced teams typically garner peak citations, while highly-cited vertices drift toward male-skewed teams in male-majority areas. Increasing female participation yields significant gains in innovation. In the upstream of knowledge flow, as captured by novelty (z-scores), female-skewed teams tend to combine more unconventional knowledge. For the downstream, as encapsulated through disruption, female-skewed teams’ innovation efforts have been recognized by follow-on citations. Notably, the female advantage in innovation becomes more evident in male-dominated fields and intensifies over time. Our study offers insights into the unique academic value and the tremendous scientific contributions of females, providing important visions for institutional and policy reforms.
现代学术界普遍关注女科学家的困境。然而,女性的贡献和潜力仍未得到充分认可。为了揭开这层面纱,我们利用来自 SciSciNet 的大规模跨学科数据集来描绘过去 20 年中女性的参与情况,并使用文献计量学指标来量化女性对研究的影响。女性比例用于衡量团队中的性别构成。通过混合效应和多元回归等连续建模,我们厘清了女性存在和女性参与程度对研究影响和双重创新指标的复杂影响。我们发现,随着时间的推移,包含女性的团队和每个团队的女性比例在稳步上升,但不同学科和大类之间存在差异。我们证明了女性比例与引用次数之间的倒 U 型关系--性别均衡的团队通常能获得最高引用率,而在男性占多数的领域,高引用率顶点则向男性倾斜的团队倾斜。女性参与度的提高会带来显著的创新收益。在知识流的上游,正如新颖性(Z 值)所反映的那样,女性偏向的团队往往结合了更多的非常规知识。在下游方面,如用破坏性来概括,女性偏向团队的创新努力得到了后续引用的认可。值得注意的是,女性在创新方面的优势在男性主导的领域更加明显,并随着时间的推移而加强。我们的研究深入揭示了女性的独特学术价值和巨大科学贡献,为制度和政策改革提供了重要的愿景。
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Pub Date : 2024-06-28DOI: 10.1007/s11192-024-05073-5
Irina Gerasimov, Binita KC, Armin Mehrabian, James Acker, Michael P. McGuire
The rapid increase of Earth science data from remote sensing, models, and ground-based observations highlights an urgent need for effective data management practices. Data repositories track provenance and usage metrics which are crucial for ensuring data integrity and scientific reproducibility. Although the introduction of Digital Object Identifiers (DOIs) for datasets in the late 1990s has significantly aided in crediting creators and enhancing dataset discoverability (akin to traditional research citations), considerable challenges persist in establishing linkage of datasets used with scholarly documents. This study evaluates the citation coverage of datasets from NASA’s Earth Observing System Data and Information System (EOSDIS) across several major bibliographic sources ‒ namely Google Scholar (GS), Web of Science (WoS), Scopus, Crossref, and DataCite—which helps data managers in making informed decisions when selecting bibliographic sources. We provide a robust and comprehensive understanding of the citation landscape, crucial for advancing data management practices and advancing open science. Our study searched and analyzed temporal trends across the bibliographic sources for publications that cite approximately 11,000 DOIs associated with EOSDIS datasets, yielding 17,000 unique journal and conference articles, reports, and book records linked to 3,000 dataset DOIs. GS emerged as the most comprehensive source while Crossref lagged significantly behind the other major sources. Crossref’s record references revealed that the absence of dataset DOIs and shortcomings in the Crossref Event data interface likely contributed to its underperformance. Scopus initially outperformed WoS until 2020, after which WoS began to show superior performance. Overall, our study underscores the necessity of utilizing multiple bibliographic sources for citation analysis, particularly for exploring dataset-to-document connections.
{"title":"Comparison of datasets citation coverage in Google Scholar, Web of Science, Scopus, Crossref, and DataCite","authors":"Irina Gerasimov, Binita KC, Armin Mehrabian, James Acker, Michael P. McGuire","doi":"10.1007/s11192-024-05073-5","DOIUrl":"https://doi.org/10.1007/s11192-024-05073-5","url":null,"abstract":"<p>The rapid increase of Earth science data from remote sensing, models, and ground-based observations highlights an urgent need for effective data management practices. Data repositories track provenance and usage metrics which are crucial for ensuring data integrity and scientific reproducibility. Although the introduction of Digital Object Identifiers (DOIs) for datasets in the late 1990s has significantly aided in crediting creators and enhancing dataset discoverability (akin to traditional research citations), considerable challenges persist in establishing linkage of datasets used with scholarly documents. This study evaluates the citation coverage of datasets from NASA’s Earth Observing System Data and Information System (EOSDIS) across several major bibliographic sources ‒ namely Google Scholar (GS), Web of Science (WoS), Scopus, Crossref, and DataCite—which helps data managers in making informed decisions when selecting bibliographic sources. We provide a robust and comprehensive understanding of the citation landscape, crucial for advancing data management practices and advancing open science. Our study searched and analyzed temporal trends across the bibliographic sources for publications that cite approximately 11,000 DOIs associated with EOSDIS datasets, yielding 17,000 unique journal and conference articles, reports, and book records linked to 3,000 dataset DOIs. GS emerged as the most comprehensive source while Crossref lagged significantly behind the other major sources. Crossref’s record references revealed that the absence of dataset DOIs and shortcomings in the Crossref Event data interface likely contributed to its underperformance. Scopus initially outperformed WoS until 2020, after which WoS began to show superior performance. Overall, our study underscores the necessity of utilizing multiple bibliographic sources for citation analysis, particularly for exploring dataset-to-document connections.</p>","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-27DOI: 10.1007/s11192-024-05081-5
Ruimin Pei, Langqiu Li, Yiying Yang, Quan Zhou
Science and technology human resources are fundamental components for enhancing the efficiency of the national innovation system. This study aims to examine the co-evolutionary relationship between scientific collaboration and scientific mobility, explore the dynamic development process of collaboration and talent flow within the global science system, and offer insights for developing suitable policies related to scientific mobility and international collaboration. The study employs Scopus data from 1788 to 2020 to investigate the systematic co-evolution of scientific talent flow and scientific collaboration from a macro and long-term perspective. The findings indicate that: (1) The global scientific flow and collaboration networks are increasingly interconnected, with a rising prevalence of international mobility and intensified worldwide collaboration. (2) Both networks exhibit cluster structures that have evolved over time, with a shift towards more random network configurations, reflecting more extensive and frequent global scientific interactions. (3) The “Matthew Effect” is observed, highlighting an imbalance with a few dominant players and many minor participants, while advanced countries demonstrate greater alignment between collaboration and mobility networks than lagging ones. Policy implications include encouraging international research mobility, supporting cooperation within scientific clusters, and prioritizing connections with global research hubs while engaging with peripheral countries.
{"title":"Co-evolution of international scientific mobility and international collaboration: a Scopus-based analysis","authors":"Ruimin Pei, Langqiu Li, Yiying Yang, Quan Zhou","doi":"10.1007/s11192-024-05081-5","DOIUrl":"https://doi.org/10.1007/s11192-024-05081-5","url":null,"abstract":"<p>Science and technology human resources are fundamental components for enhancing the efficiency of the national innovation system. This study aims to examine the co-evolutionary relationship between scientific collaboration and scientific mobility, explore the dynamic development process of collaboration and talent flow within the global science system, and offer insights for developing suitable policies related to scientific mobility and international collaboration. The study employs Scopus data from 1788 to 2020 to investigate the systematic co-evolution of scientific talent flow and scientific collaboration from a macro and long-term perspective. The findings indicate that: (1) The global scientific flow and collaboration networks are increasingly interconnected, with a rising prevalence of international mobility and intensified worldwide collaboration. (2) Both networks exhibit cluster structures that have evolved over time, with a shift towards more random network configurations, reflecting more extensive and frequent global scientific interactions. (3) The “Matthew Effect” is observed, highlighting an imbalance with a few dominant players and many minor participants, while advanced countries demonstrate greater alignment between collaboration and mobility networks than lagging ones. Policy implications include encouraging international research mobility, supporting cooperation within scientific clusters, and prioritizing connections with global research hubs while engaging with peripheral countries.</p>","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-27DOI: 10.1007/s11192-024-05091-3
Hashem Atapour, Robabeh Maddahi, Rasoul Zavaraqi
Policy citations are considered as one of the important indicators of the societal impact of research. Scientometrics is a field that, among other goals, focus on contributing to science policy, so the presence of scientometric researches in policy documents become important. Accordingly, this study aims to measure the impact of scientometric researches on policy by examining the mentions of scientometric articles in policy documents. The dataset used in this study includes 5525 scientometric articles indexed in Web of Science between 2013 and 2022. The Overton database were used to collect policy citations. The results showed that out of 5525 scientometric articles, 921 articles (16.67%) were cited at least once in policy documents. Additionally, older articles were cited more frequently than recent ones in policy documents. Scientometrics Journal ranked first in terms of the number of articles being cited in policy documents, while Research Policy and Research Evaluation Journals ranked first and second, respectively, in terms of coverage, density, and intensity. Subject analysis of the cited articles in policy documents showed that articles on national/international scholar collaborations, scholar productivity/scholar performance, and funding and sponsorship were cited more frequently in policy documents. Finally, Open Access articles were cited more frequently than non-open access articles in policy documents. However, there was not significant difference between policy citations of multi-authored and sing-authored articles. Overall, policy citations of scientometric articles were fair compared to other fields, and for greater impact of this field on policy, publishing open access, and greater attention to the topics identified in this study can be helpful.
政策引文被认为是衡量研究的社会影响的重要指标之一。科学计量学是一个以促进科学政策为主要目标的领域,因此,科学计量学研究在政策文件中的出现变得非常重要。因此,本研究旨在通过考察科学计量学文章在政策文件中的提及情况来衡量科学计量学研究对政策的影响。本研究使用的数据集包括 2013 年至 2022 年期间被 Web of Science 索引的 5525 篇科学计量学文章。研究使用 Overton 数据库收集政策引文。结果显示,在5525篇科学计量学文章中,有921篇(16.67%)在政策文件中至少被引用过一次。此外,较早的文章在政策文件中被引用的频率高于近期的文章。在政策文件中被引用的文章数量方面,《科学计量学杂志》排名第一,而在《研究政策》和《研究评价》的覆盖面、密度和强度方面,《科学计量学杂志》分别排名第一和第二。对政策文件中被引用文章的主题分析表明,有关国内/国际学者合作、学者生产力/学者绩效以及资金和赞助的文章在政策文件中被引用的频率较高。最后,在政策文件中,开放存取文章的引用频率高于非开放存取文章。然而,多作者文章和单一作者文章的政策引用率没有明显差异。总体而言,与其他领域相比,科学计量学文章的政策引用率尚可,要想提高该领域对政策的影响,出版开放获取的文章以及更多地关注本研究确定的主题可能会有所帮助。
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Pub Date : 2024-06-27DOI: 10.1007/s11192-024-05074-4
Dengsheng Wu, Huidong Wu, Jianping Li
The number of positive words in scientific papers has exhibited a notable upwards trend over the past few decades. However, there remains a gap in our comprehensive understanding of the relationship between positive words and research impact. In this study, we conduct a multifaceted exploration of the citation advantage associated with positive words based on social cognitive theory, examining its predictability, temporal evolution, and universality across journals of varying quality grades. Drawing from a corpus encompassing 124,144 papers published in the management field between 2001 and 2020, our regression results provide compelling evidence suggesting that positive words can serve as a significant predictor of the citation counts of academic papers, supporting the citation advantage of positive words. However, it is essential to recognize that over time, the citation advantage attributed to positive words is experiencing a conspicuous decline. The universality of the above phenomenon has been further verified in the analysis of journals of different quality. Our findings prompt a discussion regarding the need to pay more attention to the overuse and misuse of positive words, as well as practical considerations for enhancing scientific communication within the academic community.
{"title":"Citation advantage of positive words: predictability, temporal evolution, and universality in varied quality journals","authors":"Dengsheng Wu, Huidong Wu, Jianping Li","doi":"10.1007/s11192-024-05074-4","DOIUrl":"https://doi.org/10.1007/s11192-024-05074-4","url":null,"abstract":"<p>The number of positive words in scientific papers has exhibited a notable upwards trend over the past few decades. However, there remains a gap in our comprehensive understanding of the relationship between positive words and research impact. In this study, we conduct a multifaceted exploration of the citation advantage associated with positive words based on social cognitive theory, examining its predictability, temporal evolution, and universality across journals of varying quality grades. Drawing from a corpus encompassing 124,144 papers published in the management field between 2001 and 2020, our regression results provide compelling evidence suggesting that positive words can serve as a significant predictor of the citation counts of academic papers, supporting the citation advantage of positive words. However, it is essential to recognize that over time, the citation advantage attributed to positive words is experiencing a conspicuous decline. The universality of the above phenomenon has been further verified in the analysis of journals of different quality. Our findings prompt a discussion regarding the need to pay more attention to the overuse and misuse of positive words, as well as practical considerations for enhancing scientific communication within the academic community.</p>","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-27DOI: 10.1007/s11192-024-05095-z
Weishu Liu, Ruifeng Zhang
A recent study published in Scientometrics used publications in Scopus and Web of Science Core Collection to exam the decades-long scientific collaboration between Cuba and China (Ronda-Pupo, Scientometrics 129:785–802, 2024). Ronda-Pupo’s finding of the significant growth of research collaboration between these two countries evidenced by the number of co-authored papers is different from our daily perception of the scientific collaboration between China and Cuba. By using the same data, we find the dominating role of multilateral co-authorship rather than bilateral or trilateral co-authorship in Cuba-China scientific collaboration. This important finding gives an alternative explanation of the increasing Cuba-China co-authored publications. Through the supplement of our exploration, readers can have a better understanding of the Cuba-China scientific collaboration.
最近发表在《科学计量学》(Scientometrics)上的一项研究利用 Scopus 和 Web of Science Core Collection 中的论文来考察古巴和中国之间长达数十年的科研合作(Ronda-Pupo,《科学计量学》129:785-802,2024 年)。Ronda-Pupo 的研究发现,两国之间的科研合作有了显著增长,合著论文的数量也证明了这一点,这与我们日常对中古两国科研合作的认识有所不同。通过使用相同的数据,我们发现在古中两国的科研合作中,多边合著而非双边或三边合著占据了主导地位。这一重要发现为中古合著出版物的增加提供了另一种解释。通过补充我们的探索,读者可以更好地了解古中科学合作。
{"title":"Multilateral co-authorship: an important but easily overlooked pattern in international scientific collaboration research","authors":"Weishu Liu, Ruifeng Zhang","doi":"10.1007/s11192-024-05095-z","DOIUrl":"https://doi.org/10.1007/s11192-024-05095-z","url":null,"abstract":"<p>A recent study published in Scientometrics used publications in Scopus and Web of Science Core Collection to exam the decades-long scientific collaboration between Cuba and China (Ronda-Pupo, Scientometrics 129:785–802, 2024). Ronda-Pupo’s finding of the significant growth of research collaboration between these two countries evidenced by the number of co-authored papers is different from our daily perception of the scientific collaboration between China and Cuba. By using the same data, we find the dominating role of multilateral co-authorship rather than bilateral or trilateral co-authorship in Cuba-China scientific collaboration. This important finding gives an alternative explanation of the increasing Cuba-China co-authored publications. Through the supplement of our exploration, readers can have a better understanding of the Cuba-China scientific collaboration.</p>","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-27DOI: 10.1007/s11192-024-05084-2
Arjun Prakash, Jeevan John Varghese, Shruti Aggarwal
This study comprehensively analyses gender representation and citation disparities in gender studies by examining the position of female scholars as first and corresponding authors. The research uncovers a pattern of gender-homogeneous co-authorship and investigates the geographical and economic disparities in academic contributions, scrutinising the impact of a country’s economic status on citation rates and open-access publications, particularly in relation to citation rates and open-access publications. The study uses a Logistics Regression and Zero-Inflated Negative Binomial Regression model to explore factors influencing open-access publication and citation rates. The study’s findings demonstrate the predominant presence of female scholars in gender-focused literature within social sciences, in contrast to their underrepresentation in STEM fields. The findings also reveal a tendency towards gender-homogenous collaborations and a significant concentration of scholarly output from the high-income regions, highlighting both geographic and economic disparities. The present study provides an analytical foundation for future studies on the global distribution of scholarly contributions and the complex interplay of various factors affecting academic publishing in gender studies.
{"title":"Gender of gender studies: examining regional and gender-based disparities in scholarly publications","authors":"Arjun Prakash, Jeevan John Varghese, Shruti Aggarwal","doi":"10.1007/s11192-024-05084-2","DOIUrl":"https://doi.org/10.1007/s11192-024-05084-2","url":null,"abstract":"<p>This study comprehensively analyses gender representation and citation disparities in gender studies by examining the position of female scholars as first and corresponding authors. The research uncovers a pattern of gender-homogeneous co-authorship and investigates the geographical and economic disparities in academic contributions, scrutinising the impact of a country’s economic status on citation rates and open-access publications, particularly in relation to citation rates and open-access publications. The study uses a Logistics Regression and Zero-Inflated Negative Binomial Regression model to explore factors influencing open-access publication and citation rates. The study’s findings demonstrate the predominant presence of female scholars in gender-focused literature within social sciences, in contrast to their underrepresentation in STEM fields. The findings also reveal a tendency towards gender-homogenous collaborations and a significant concentration of scholarly output from the high-income regions, highlighting both geographic and economic disparities. The present study provides an analytical foundation for future studies on the global distribution of scholarly contributions and the complex interplay of various factors affecting academic publishing in gender studies.</p>","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-27DOI: 10.1007/s11192-024-05071-7
Yuefen Wang, Lipeng Fan, Lei Wu
Exploring a robust and universal appeal bibliometric indicator for assessing creativity is essential but challenging. The novelty measure of innovation proposed by Uzzi et al. (NoveltyU) has sparked considerable interest and debate. Thus, further validation and understanding of its portfolio form of novelty and scope of application are necessary. This paper delves into the calculation and application of the NoveltyU method to shed light on its effectiveness and scope. Analysis of the calculation process reveals that journal pairs with higher novelty often span independent fundamental areas, while those with lower novelty tend to focus on similar and applied fields. Utilizing collaboration patterns between institutions, as discussed in our prior study (Fan et al., Scientometrics 125:1179–1196, 2020), offers insight into the method’s performance in real-world contexts. Results consistently show higher mean NoveltyU values in MM pattern over time, affirming the method’s validity. Categorizing papers into high conventional, low conventional, low novel, and high novel categories unveils higher overlap degree of terms among different patterns in high novel papers. Moreover, leading terms in MM pattern exhibit specific information, while delay terms tend to be more general, and simultaneous terms are even more so. These findings offer valuable insights into identifying hot and frontier topics, bolstering the credibility and application potential of the NoveltyU method, aligning with the broader objective of establishing valid measures of innovativeness in research.
{"title":"A validation test of the Uzzi et al. novelty measure of innovation and applications to collaboration patterns between institutions","authors":"Yuefen Wang, Lipeng Fan, Lei Wu","doi":"10.1007/s11192-024-05071-7","DOIUrl":"https://doi.org/10.1007/s11192-024-05071-7","url":null,"abstract":"<p>Exploring a robust and universal appeal bibliometric indicator for assessing creativity is essential but challenging. The novelty measure of innovation proposed by Uzzi et al. (NoveltyU) has sparked considerable interest and debate. Thus, further validation and understanding of its portfolio form of novelty and scope of application are necessary. This paper delves into the calculation and application of the NoveltyU method to shed light on its effectiveness and scope. Analysis of the calculation process reveals that journal pairs with higher novelty often span independent fundamental areas, while those with lower novelty tend to focus on similar and applied fields. Utilizing collaboration patterns between institutions, as discussed in our prior study (Fan et al., Scientometrics 125:1179–1196, 2020), offers insight into the method’s performance in real-world contexts. Results consistently show higher mean NoveltyU values in MM pattern over time, affirming the method’s validity. Categorizing papers into high conventional, low conventional, low novel, and high novel categories unveils higher overlap degree of terms among different patterns in high novel papers. Moreover, leading terms in MM pattern exhibit specific information, while delay terms tend to be more general, and simultaneous terms are even more so. These findings offer valuable insights into identifying hot and frontier topics, bolstering the credibility and application potential of the NoveltyU method, aligning with the broader objective of establishing valid measures of innovativeness in research.</p>","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}