36,652 research outputs found

    A comparative study on communication structures of Chinese journals in the social sciences

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    We argue that the communication structures in the Chinese social sciences have not yet been sufficiently reformed. Citation patterns among Chinese domestic journals in three subject areas -- political science and marxism, library and information science, and economics -- are compared with their counterparts internationally. Like their colleagues in the natural and life sciences, Chinese scholars in the social sciences provide fewer references to journal publications than their international counterparts; like their international colleagues, social scientists provide fewer references than natural sciences. The resulting citation networks, therefore, are sparse. Nevertheless, the citation structures clearly suggest that the Chinese social sciences are far less specialized in terms of disciplinary delineations than their international counterparts. Marxism studies are more established than political science in China. In terms of the impact of the Chinese political system on academic fields, disciplines closely related to the political system are less specialized than those weakly related. In the discussion section, we explore reasons that may cause the current stagnation and provide policy recommendations

    The metric tide: report of the independent review of the role of metrics in research assessment and management

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    This report presents the findings and recommendations of the Independent Review of the Role of Metrics in Research Assessment and Management. The review was chaired by Professor James Wilsdon, supported by an independent and multidisciplinary group of experts in scientometrics, research funding, research policy, publishing, university management and administration. This review has gone beyond earlier studies to take a deeper look at potential uses and limitations of research metrics and indicators. It has explored the use of metrics across different disciplines, and assessed their potential contribution to the development of research excellence and impact. It has analysed their role in processes of research assessment, including the next cycle of the Research Excellence Framework (REF). It has considered the changing ways in which universities are using quantitative indicators in their management systems, and the growing power of league tables and rankings. And it has considered the negative or unintended effects of metrics on various aspects of research culture. The report starts by tracing the history of metrics in research management and assessment, in the UK and internationally. It looks at the applicability of metrics within different research cultures, compares the peer review system with metric-based alternatives, and considers what balance might be struck between the two. It charts the development of research management systems within institutions, and examines the effects of the growing use of quantitative indicators on different aspects of research culture, including performance management, equality, diversity, interdisciplinarity, and the ‘gaming’ of assessment systems. The review looks at how different funders are using quantitative indicators, and considers their potential role in research and innovation policy. Finally, it examines the role that metrics played in REF2014, and outlines scenarios for their contribution to future exercises

    References made and citations received by scientific articles

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    This paper studies massive evidence about references made and citations received after a five-year citation window by 3.7 million articles published in 1998-2002 in 22 scientific fields. We find that the distributions of references made and citations received share a number of basic features across sciences. Reference distributions are rather skewed to the right, while citation distributions are even more highly skewed: the mean is about 20 percentage points to the right of the median, and articles with a remarkable or outstanding number of citations represent about 9% of the total. Moreover, the existence of a power law representing the upper tail of citation distributions cannot be rejected in 17 fields whose articles represent 74.7% of the total. Contrary to the evidence in other contexts, the value of the scale parameter is above 3.5 in 13 of the 17 cases. Finally, power laws are typically small but capture a considerable proportion of the total citations received.

    Citing for High Impact

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    The question of citation behavior has always intrigued scientists from various disciplines. While general citation patterns have been widely studied in the literature we develop the notion of citation projection graphs by investigating the citations among the publications that a given paper cites. We investigate how patterns of citations vary between various scientific disciplines and how such patterns reflect the scientific impact of the paper. We find that idiosyncratic citation patterns are characteristic for low impact papers; while narrow, discipline-focused citation patterns are common for medium impact papers. Our results show that crossing-community, or bridging citation patters are high risk and high reward since such patterns are characteristic for both low and high impact papers. Last, we observe that recently citation networks are trending toward more bridging and interdisciplinary forms.Comment: 10 pages, 6 figures, 1 tabl

    Construction of a Pragmatic Base Line for Journal Classifications and Maps Based on Aggregated Journal-Journal Citation Relations

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    A number of journal classification systems have been developed in bibliometrics since the launch of the Citation Indices by the Institute of Scientific Information (ISI) in the 1960s. These systems are used to normalize citation counts with respect to field-specific citation patterns. The best known system is the so-called "Web-of-Science Subject Categories" (WCs). In other systems papers are classified by algorithmic solutions. Using the Journal Citation Reports 2014 of the Science Citation Index and the Social Science Citation Index (n of journals = 11,149), we examine options for developing a new system based on journal classifications into subject categories using aggregated journal-journal citation data. Combining routines in VOSviewer and Pajek, a tree-like classification is developed. At each level one can generate a map of science for all the journals subsumed under a category. Nine major fields are distinguished at the top level. Further decomposition of the social sciences is pursued for the sake of example with a focus on journals in information science (LIS) and science studies (STS). The new classification system improves on alternative options by avoiding the problem of randomness in each run that has made algorithmic solutions hitherto irreproducible. Limitations of the new system are discussed (e.g. the classification of multi-disciplinary journals). The system's usefulness for field-normalization in bibliometrics should be explored in future studies.Comment: accepted for publication in the Journal of Informetrics, 20 July 201
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