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1. Creative Destruction: The Structural Consequences of Scientific Curation

   https://doi.org/10.1177/0003122421996323  

   McMahan, Peter; McFarland, Daniel A. (April 2021, American Sociological Review)

   null (Ed.)

   Communication of scientific findings is fundamental to scholarly discourse. In this article, we show that academic review articles, a quintessential form of interpretive scholarly output, perform curatorial work that substantially transforms the research communities they aim to summarize. Using a corpus of millions of journal articles, we analyze the consequences of review articles for the publications they cite, focusing on citation and co-citation as indicators of scholarly attention. Our analysis shows that, on the one hand, papers cited by formal review articles generally experience a dramatic loss in future citations. Typically, the review gets cited instead of the specific articles mentioned in the review. On the other hand, reviews curate, synthesize, and simplify the literature concerning a research topic. Most reviews identify distinct clusters of work and highlight exemplary bridges that integrate the topic as a whole. These bridging works, in addition to the review, become a shorthand characterization of the topic going forward and receive disproportionate attention. In this manner, formal reviews perform creative destruction so as to render increasingly expansive and redundant bodies of knowledge distinct and comprehensible. 

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2. Protection of the human gene research literature from contract cheating organizations known as research paper mills

   https://doi.org/10.1093/nar/gkac1139  

   Byrne, Jennifer A.; Park, Yasunori; Richardson, Reese A. K.; Pathmendra, Pranujan; Sun, Mengyi; Stoeger, Thomas (December 2022, Nucleic Acids Research)

   Abstract Human gene research generates new biology insights with translational potential, yet few studies have considered the health of the human gene literature. The accessibility of human genes for targeted research, combined with unreasonable publication pressures and recent developments in scholarly publishing, may have created a market for low-quality or fraudulent human gene research articles, including articles produced by contract cheating organizations known as paper mills. This review summarises the evidence that paper mills contribute to the human gene research literature at scale and outlines why targeted gene research may be particularly vulnerable to systematic research fraud. To raise awareness of targeted gene research from paper mills, we highlight features of problematic manuscripts and publications that can be detected by gene researchers and/or journal staff. As improved awareness and detection could drive the further evolution of paper mill-supported publications, we also propose changes to academic publishing to more effectively deter and correct problematic publications at scale. In summary, the threat of paper mill-supported gene research highlights the need for all researchers to approach the literature with a more critical mindset, and demand publications that are underpinned by plausible research justifications, rigorous experiments and fully transparent reporting. 

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3. How Data Scientists Review the Scholarly Literature

   https://doi.org/10.1145/3576840  

   Mysore, Sheshera; Jasim, Mahmood; Song, Haoru; Akbar, Sarah; Randall, Andre Kenneth; Mahyar, Narges (March 2023, ACM)

   Gwizdka, Jacek; Rieh, Soo Young (Ed.)

   Keeping up with the research literature plays an important role in the workflow of scientists – allowing them to understand a field, formulate the problems they focus on, and develop the solutions that they contribute, which in turn shape the nature of the discipline. In this paper, we examine the literature review practices of data scientists. Data science represents a field seeing an exponential rise in papers, and increasingly drawing on and being applied in numerous diverse disciplines. Recent efforts have seen the development of several tools intended to help data scientists cope with a deluge of research and coordinated efforts to develop AI tools intended to uncover the research frontier. Despite these trends indicative of the information overload faced by data scientists, no prior work has examined the specific practices and challenges faced by these scientists in an interdisciplinary field with evolving scholarly norms. In this paper, we close this gap through a set of semi-structured interviews and think-aloud protocols of industry and academic data scientists (N = 20). Our results while corroborating other knowledge workers’ practices uncover several novel findings: individuals (1) are challenged in seeking and sensemaking of papers beyond their disciplinary bubbles, (2) struggle to understand papers in the face of missing details and mathematical content, (3) grapple with the deluge by leveraging the knowledge context in code, blogs, and talks, and (4) lean on their peers online and in-person. Furthermore, we outline future directions likely to help data scientists cope with the burgeoning research literature. 

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4. System Factors Affecting Underrepresented Minorities in Doctoral Programs in Engineering: A Literature Review

   https://doi.org/10.1109/FIE49875.2021.9637208  

   Bouhrira, Neirouz; Cruz, Juan M. (October 2021, 2021 IEEE Frontiers in Education Conference (FIE))

   Several studies have shown that underrepresented minorities (URM) (African Americans, Native Americans, Pacific Islanders, and Latinos) are more likely to drop out of engineering doctorate programs before graduation compared to international and majority students. In addition, transitioning into the doctoral programs without having a good understanding of what it entails can make the PhD experience difficult. To address this issue, a team of researchers from four US universities developed a project called “the Rising Doctoral Institute (RDI)’’. One of the research goals of this project is to better understand how factors in the academic system interact dynamically to influence (i.e., support or hinder) incoming URM students’ access, success, persistence, and retention in engineering doctoral programs. To accomplish this goal, we will use a comprehensive analysis approach known as System Dynamic Model (SDM). This work-In-Progress article represents the starting point to develop this model and its overall goal is to conduct a systematic literature review to identify the factors in the academic system that impact URM students’ experience in doctoral engineering programs. We followed a process suggested by Okoli and Schabram [1] which consists of four major steps. The first step is presenting the purpose of the literature review, protocol, and training. The second step consists of selecting the literature and practical screen. The next step is the quality appraisal and data extraction. Finally, the analysis of findings and writing the review. By identifying the factors and the relation between them, we could help ensure a more diverse and equitable STEM education. Although some external factors can affect students’ access, success, persistence and retention in engineering PhD programs, this study is limited to exploring the factors and interactions within the academic system that can potentially impact the successful experience of underrepresented minorities in PhD programs in engineering such as Advisor-Advisee Relationship, Student’s Experience, Academic Support and Faculty-Students Interaction 

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5. Visualizing Scholarly Publications and Citations to Enhance Author Profiles

   https://doi.org/10.1145/3041021.3053058  

   Portenoy, Jason; West, Jevin D. (April 2017, WWW '17 Companion Proceedings of the 26th International Conference on World Wide Web Companion)

   With data on scholarly publications becoming more abundant and accessible, there exist new opportunities for using this information to provide rich author profiles to display and explore scholarly work. We present a pair of linked visualizations connected to the Microsoft Academic Graph that can be used to explore the publications and citations of individual authors. We provide an online application with which a user can manage collections of papers and generate these visualizations. 

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