No Arabic abstract
This paper presents a study that analyzes and gives quantitative means for measuring the gender gap in computing research publications. The data set built for this study is a geo-gender tagged authorship database named authorships that integrates data from computing journals indexed in the Journal Citation Reports (JCR) and the Microsoft Academic Graph (MAG). We propose a gender gap index to analyze female and male authors participation gap in JCR publications in Computer Science. Tagging publications with this index, we can classify papers according to the degree of participation of both women and men in different domains. Given that working contexts vary for female scientists depending on the country, our study groups analytics results according to the country of authors affiliation institutions. The paper details the method used to obtain, clean and validate the data, and then it states the hypothesis adopted for defining our index and classifications. Our study results have led to enlightening conclusions concerning various aspects of female authorships geographical distribution in computing JCR publications.
Gender diversity in the tech sector is - not yet? - sufficient to create a balanced ratio of men and women. For many women, access to computer science is hampered by socialization-related, social, cultural and structural obstacles. The so-called implicit gender bias has a great influence in this respect. The lack of contact in areas of computer science makes it difficult to develop or expand potential interests. Female role models as well as more transparency of the job description should help women to promote their - possible - interest in the job description. However, gender diversity can also be promoted and fostered through adapted measures by leaders.
In this research, we examine the hypothesis that gender disparities in international research collaboration differ by collaboration intensity, academic position, age, and academic discipline. The following are the major findings: (1) while female scientists exhibit a higher rate of general, national, and institutional collaboration, male scientists exhibit a higher rate of international collaboration, a finding critically important in explaining gender disparities in impact, productivity, and access to large grants. (2) An aggregated picture of gender disparities hides a more nuanced cross-disciplinary picture of them. (3) An analysis of international research collaboration at three separate intensity levels (low, medium, and high) reveals that male scientists dominate in international collaboration at each level. However, at each level, there are specific disciplines in which females collaborate more than males. Further (4), gender disparities are clearly linked with age. Until about the age of 40, they are marginal and then they begin to grow. Finally, we estimate the odds of being involved in international research collaboration using an analytical linear logistic model. The examined sample includes 25,463 internationally productive Polish university professors from 85 universities, grouped into 27 disciplines, who authored 159,943 Scopus-indexed articles.
Computer science is a relatively young discipline combining science, engineering, and mathematics. The main flavors of computer science research involve the theoretical development of conceptual models for the different aspects of computing and the more applicative building of software artifacts and assessment of their properties. In the computer science publication culture, conferences are an important vehicle to quickly move ideas, and journals often publish deep
Knowledge of how science is consumed in public domains is essential for a deeper understanding of the role of science in human society. While science is heavily supported by public funding, common depictions suggest that scientific research remains an isolated or ivory tower activity, with weak connectivity to public use, little relationship between the quality of research and its public use, and little correspondence between the funding of science and its public use. This paper introduces a measurement framework to examine public good features of science, allowing us to study public uses of science, the public funding of science, and how use and funding relate. Specifically, we integrate five large-scale datasets that link scientific publications from all scientific fields to their upstream funding support and downstream public uses across three public domains - government documents, the news media, and marketplace invention. We find that the public uses of science are extremely diverse, with different public domains drawing distinctively across scientific fields. Yet amidst these differences, we find key forms of alignment in the interface between science and society. First, despite concerns that the public does not engage high-quality science, we find universal alignment, in each scientific field and public domain, between what the public consumes and what is highly impactful within science. Second, despite myriad factors underpinning the public funding of science, the resulting allocation across fields presents a striking alignment with the fields collective public use. Overall, public uses of science present a rich landscape of specialized consumption, yet collectively science and society interface with remarkable, quantifiable alignment between scientific use, public use, and funding.
Our current knowledge of scholarly plagiarism is largely based on the similarity between full text research articles. In this paper, we propose an innovative and novel conceptualization of scholarly plagiarism in the form of reuse of explicit citation sentences in scientific research articles. Note that while full-text plagiarism is an indicator of a gross-level behavior, copying of citation sentences is a more nuanced micro-scale phenomenon observed even for well-known researchers. The current work poses several interesting questions and attempts to answer them by empirically investigating a large bibliographic text dataset from computer science containing millions of lines of citation sentences. In particular, we report evidences of massive copying behavior. We also present several striking real examples throughout the paper to showcase widespread adoption of this undesirable practice. In contrast to the popular perception, we find that copying tendency increases as an author matures. The copying behavior is reported to exist in all fields of computer science; however, the theoretical fields indicate more copying than the applied fields.