The role of gender in scholarly authorship.
Jevin D. West,Jennifer Jacquet,Molly M. King,Shelley J. Correll,Carl T. Bergstrom,Carl T. Bergstrom +5 more
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TLDR
A large-scale analysis based on over eight million papers across the natural sciences, social sciences, and humanities reveals a number of understated and persistent ways in which gender inequities remain this paper.Abstract:
Gender disparities appear to be decreasing in academia according to a number of metrics, such as grant funding, hiring, acceptance at scholarly journals, and productivity, and it might be tempting to think that gender inequity will soon be a problem of the past. However, a large-scale analysis based on over eight million papers across the natural sciences, social sciences, and humanities reveals a number of understated and persistent ways in which gender inequities remain. For instance, even where raw publication counts seem to be equal between genders, close inspection reveals that, in certain fields, men predominate in the prestigious first and last author positions. Moreover, women are significantly underrepresented as authors of single-authored papers. Academics should be aware of the subtle ways that gender disparities can occur in scholarly authorship.read more
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Proceedings of the National Academy of Sciences
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Bibliometrics: Global gender disparities in science
TL;DR: Sugimoto et al. as mentioned in this paper presented a bibliometric analysis confirming that gender imbalances persist in research output worldwide, and they concluded that gender imbalance persists in all fields.
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Science of science
Santo Fortunato,Carl T. Bergstrom,Katy Börner,James A. Evans,Dirk Helbing,Staša Milojević,Alexander M. Petersen,Filippo Radicchi,Roberta Sinatra,Roberta Sinatra,Brian Uzzi,Alessandro Vespignani,Alessandro Vespignani,Ludo Waltman,Dashun Wang,Albert-László Barabási,Albert-László Barabási,Albert-László Barabási +17 more
TL;DR: The Science of Science (SciSci) as discussed by the authors provides a quantitative understanding of the interactions among scientific agents across diverse geographic and temporal scales, providing insights into the conditions underlying creativity and the genesis of scientific discovery, with the ultimate goal of developing tools and policies that have the potential to accelerate science.
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The Diversity-Innovation Paradox in Science
Bas Hofstra,Vivek Kulkarni,Sebastian Munoz-Najar Galvez,Bryan He,Dan Jurafsky,Daniel A. McFarland +5 more
TL;DR: This paper used text analysis and machine learning to answer a series of questions: How do we detect scientific innovations? Are underrepresented groups more likely to generate scientific innovations, and are the innovations of under-represented groups adopted and rewarded?
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The gender gap in science: How long until women are equally represented?
TL;DR: The gender gap in Science, Technology, Engineering, Mathematics, and Medicine will not close without further reforms in education, mentoring, and academic publishing, it is concluded.
References
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Maps of random walks on complex networks reveal community structure
Martin Rosvall,Carl T. Bergstrom +1 more
TL;DR: An information theoretic approach is introduced that reveals community structure in weighted and directed networks of large-scale biological and social systems and reveals a directional pattern of citation from the applied fields to the basic sciences.
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The Increasing Dominance of Teams in Production of Knowledge
TL;DR: It is demonstrated that teams increasingly dominate solo authors in the production of knowledge, suggesting that the process of knowledge creation has fundamentally changed.
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Science faculty’s subtle gender biases favor male students
TL;DR: In a randomized double-blind study, science faculty from research-intensive universities rated the application materials of a student as significantly more competent and hireable than the (identical) female applicant, and preexisting subtle bias against women played a moderating role.
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Community detection algorithms: a comparative analysis.
TL;DR: Three recent algorithms introduced by Rosvall and Bergstrom and Ronhovde and Nussinov have an excellent performance, with the additional advantage of low computational complexity, which enables one to analyze large systems.