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      Peer review in an Era of Evaluation : Understanding the Practice of Gatekeeping in Academia 

      Hierarchies and Universal Inclusion in Scientific Communities

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      Springer International Publishing

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          Abstract

          This chapter explains the genesis of inequalities and hierarchies in modern science. It studies the forms and mechanisms of scientific communication on the basis of which the social structures of science are built: publications, authorship, co- and multiple authorship, citations as units of information and as social rewards, peer review as evaluation of publications (and of projects and careers). This is a network of institutions that seems to guarantee universal access to participation in science to all those who fulfill basic conditions. But the chapter demonstrates how in all these institutional dimensions differences arise between successful and not equally successful participations. Success generates influence and social attractiveness (e.g. as a co-author). Influential and attractive participants are recruited into positions where they assess the achievements of others and thereby limit and control inclusion in publications, funding and careers. Equality at the start is transformed into hierarchies of control. Finally, the chapter asks for potential alternative control structures that transform a conservative hierarchy into decentralized ‘market’ controls that involve everyone in a more dynamic production and evaluation of scientific achievements.

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          The Matthew Effect in Science, II: Cumulative Advantage and the Symbolism of Intellectual Property

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            Cumulative Advantage as a Mechanism for Inequality: A Review of Theoretical and Empirical Developments

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              Clustering and preferential attachment in growing networks.

              We study empirically the time evolution of scientific collaboration networks in physics and biology. In these networks, two scientists are considered connected if they have coauthored one or more papers together. We show that the probability of a pair of scientists collaborating increases with the number of other collaborators they have in common, and that the probability of a particular scientist acquiring new collaborators increases with the number of his or her past collaborators. These results provide experimental evidence in favor of previously conjectured mechanisms for clustering and power-law degree distributions in networks.
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                Author and book information

                Book Chapter
                2022
                January 03 2022
                : 37-52
                10.1007/978-3-030-75263-7_2
                066fb958-aecf-48ad-9b65-90a04ad64416
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