Cassidy R. Sugimoto and colleagues present a bibliometric analysis confirming that gender imbalances persist in research output worldwide.

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Her current research examines failures of interorganizational networks, information and communication technology innovation in complex organizations, and digital divide and social inclusion.

Interdisciplinarity has been studied using cognitive connections among individuals in corresponding domains, but rarely from the perspective of academic genealogy. This article utilizes academic genealogy network data from 3,038 PhD dissertations in Library and Information Science (LIS) over a span of 80 years (1930-2009) to describe interdisciplinary changes in the discipline. Aspects of academic pedigree of advisors and committee members are analyzed, such as country, school, and discipline of highest degree, to reveal the interdisciplinary features of LIS. The results demonstrate a strong history of mentors from fields such as education and psychology, a decreasing trend of mentors with LIS degrees, and an increasing trend in mentors receiving degrees in computer science, business, and communication, among other disciplines. This work proposes and explores the use of academic genealogy as an indicator of interdisciplinarity and calls for additional research on the role of doctoral committee composition in a student's subsequent academic career.

We analyzed gender disparities in patenting by country, technological area, and type of assignee using the 4.6 million utility patents issued between 1976 and 2013 by the United States Patent and Trade Office (USPTO). Our analyses of fractionalized inventorships demonstrate that women’s rate of patenting has increased from 2.7% of total patenting activity to 10.8% over the nearly 40-year period. Our results show that, in every technological area, female patenting is proportionally more likely to occur in academic institutions than in corporate or government environments. However, women’s patents have a lower technological impact than that of men, and that gap is wider in the case of academic patents. We also provide evidence that patents to which women—and in particular academic women—contributed are associated with a higher number of International Patent Classification (IPC) codes and co-inventors than men. The policy implications of these disparities and academic setting advantages are discussed.

Authorship is the primary form of symbolic capital in science. Despite this, authorship is rife with injustice and malpractice, with women expressing concerns regarding the fair attribution of credit. Based on an international survey, we examine gendered practices in authorship communication, disagreement, and fairness. Our results demonstrate that women were more likely to experience authorship disagreements and experience them more often. Their contributions to research papers were more often devalued by both men and women. Women were more likely to discuss authorship with coauthors at the beginning of the project, whereas men were more likely to determine authorship unilaterally at the end. Women perceived that they received less credit than deserved, while men reported the opposite. This devaluation of women's work in science creates cumulative disadvantages in scientific careers. Open discussion regarding power dynamics related to gender is necessary to develop more equitable distribution of credit for scientific labor.

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This paper performs an analysis on the influence of different factors on users' choices of specific word changes in query reformulation during a search session. We study three types of word changes: whether to remove or retain a word in the current query; whether or not to add a brand-new word to the query; whether or not to reuse a word (included in previous queries, but removed in the current query). Three types of factors are examined: session-level factors measuring task and user characteristics; query-level factors related to past user activities in a session; word-level factors for the characteristics of the examined word and its relation to the current query and search results. Statistical analysis suggests that: word-level factors strongly influence all three types of word changes; query-level factors only show a clear influence on retaining or removing a word; task-level factors exhibit limited direct influence on all three types of word changes. Analysis also disclose reasons for different word changes: users remove a word to stop exploring a subtask, or to correct bad performing queries; they look for related, unused words from recently viewed result summaries and add to queries; reusing a word usually indicates reverting from a subtask to the main task or another subtask.