Women are credited less in science than men.

There is a well-documented gap between the observed number of works produced by women and by men in science, with clear consequences for the retention and promotion of women1. The gap might be a result of productivity differences2-5, or it might be owing to women's contributions not being acknowledged6,7. Here we find that at least part of this gap is the result of unacknowledged contributions: women in research teams are significantly less likely than men to be credited with authorship. The findings are consistent across three very different sources of data. Analysis of the first source-large-scale administrative data on research teams, team scientific output and attribution of credit-show that women are significantly less likely to be named on a given article or patent produced by their team relative to their male peers. The gender gap in attribution is present across most scientific fields and almost all career stages. The second source-an extensive survey of authors-similarly shows that women's scientific contributions are systematically less likely to be recognized. The third source-qualitative responses-suggests that the reason that women are less likely to be credited is because their work is often not known, is not appreciated or is ignored. At least some of the observed gender gap in scientific output may be owing not to differences in scientific contribution, but rather to differences in attribution.

RNA-RNA interactions between respiratory syncytial virus and miR-26 and miR-27 are associated with regulation of cell cycle and antiviral immunity.

microRNAs (miRNAs) regulate nearly all physiological processes but our understanding of exactly how they function remains incomplete, particularly in the context of viral infections. Here, we adapt a biochemical method (CLEAR-CLIP) and analysis pipeline to identify targets of miRNAs in lung cells infected with Respiratory syncytial virus (RSV). We show that RSV binds directly to miR-26 and miR-27 through seed pairing and demonstrate that these miRNAs target distinct gene networks associated with cell cycle and metabolism (miR-27) and antiviral immunity (miR-26). Many of the targets are de-repressed upon infection and we show that the miR-27 targets most sensitive to miRNA inhibition are those associated with cell cycle. Finally, we demonstrate that high confidence chimeras map to long noncoding RNAs (lncRNAs) and pseudogenes in transcriptional regulatory regions. We validate that a proportion of miR-27 and Argonaute 2 (AGO2) is nuclear and identify a long non-coding RNA (lncRNA) as a miR-27 target that is linked to transcriptional regulation of nearby genes. This work expands the target networks of miR-26 and miR-27 to include direct interactions with RSV and lncRNAs and implicate these miRNAs in regulation of key genes that impact the viral life cycle associated with cell cycle, metabolism, and antiviral immunity.

New linked data on research investments: scientific workforce, productivity, and public value.

Longitudinal micro-data derived from transaction level information about wage and vendor payments made by federal grants on multiple U.S. campuses are being developed in a partnership involving researchers, university administrators, representatives of federal agencies, and others. This paper describes the UMETRICS data initiative that has been implemented under the auspices of the Committee on Institutional Cooperation. The resulting data set reflects an emerging conceptual framework for analyzing the process, products, and impact of research. It grows from and engages the work of a diverse and vibrant community. This paper situates the UMETRICS effort in the context of research evaluation and ongoing data infrastructure efforts in order to highlight its novel and valuable features. Refocusing data construction in this field around individuals, networks, and teams offers dramatic possibilities for data linkage, the evaluation of research investments, and the development of rigorous conceptual and empirical models. Two preliminary analyses of the scientific workforce and network approaches to characterizing scientific teams ground a discussion of future directions and a call for increased community engagement.

After Covid-19, The US Statistical System Needs to Change.

Julia Lane calls for a new, more democratic, public data infrastructure.

Proximity and Economic Activity: An Analysis of Vendor-University Transactions.

This paper using transaction based data to provide new insights into the link between the geographic proximity of businesses and associated economic activity. It contributes to the literature by developing both two new measures of distance and a set of stylized facts on the distances between observed transactions between vendors and customers for a research intensive sector - universities. We show that spending on research inputs is more likely to be expended at businesses physically closer to universities than those farther away. That relationship is stronger for High Tech and R&D performing businesses than businesses in general, which is consistent with theories emphasizing the role of tacit knowledge. We find that firms behave in a way that is consistent with the notion that propinquity is good for business: if a firm supplies a project at a university in a given year, it is more likely to open an establishment near that university in subsequent years than other firms. We also investigate the link between transactional distance and economic activity and show that when a vendor has been a supplier to a project at least one time, that vendor is subsequently more likely to be a vendor on the same or related project.

Gender and the Publication Output of Graduate Students: A Case Study.

We examine gender differences among the six PhD student cohorts 2004-2009 at the California Institute of Technology using a new dataset that includes information on trainees and their advisors and enables us to construct detailed measures of teams at the advisor level. We focus on the relationship between graduate student publications and: (1) their gender; (2) the gender of the advisor, (3) the gender pairing between the advisor and the student and (4) the gender composition of the team. We find that female graduate students co-author on average 8.5% fewer papers than men; that students writing with female advisors publish 7.7% more. Of particular note is that gender pairing matters: male students working with female advisors publish 10.0% more than male students working with male advisors; women students working with male advisors publish 8.5% less. There is no difference between the publishing patterns of male students working with male advisors and female students working with female advisors. The results persist and are magnified when we focus on the quality of the published articles, as measured by average Impact Factor, instead of number of articles. We find no evidence that the number of publications relates to the gender composition of the team. Although the gender effects are reasonably modest, past research on processes of positive feedback and cumulative advantage suggest that the difference will grow, not shrink, over the careers of these recent cohorts.

Wrapping it up in a person: Examining employment and earnings outcomes for Ph.D. recipients.

In evaluating research investments, it is important to establish whether the expertise gained by researchers in conducting their projects propagates into the broader economy. For eight universities, it was possible to combine data from the UMETRICS project, which provided administrative records on graduate students supported by funded research, with data from the U.S. Census Bureau. The analysis covers 2010-2012 earnings and placement outcomes of people receiving doctorates in 2009-2011. Almost 40% of supported doctorate recipients, both federally and nonfederally funded, entered industry and, when they did, they disproportionately got jobs at large and high-wage establishments in high-tech and professional service industries. Although Ph.D. recipients spread nationally, there was also geographic clustering in employment near the universities that trained and employed the researchers. We also show large differences across fields in placement outcomes.

Balancing access to health data and privacy: a review of the issues and approaches for the future.

BACKGROUND: There has been a dramatic increase in the types of microdata, and this holds great promise for health services research. However, legislative efforts to protect individual privacy have reduced the flow of health care data for research purposes and increased costs and delays, affecting the quality of analysis. AIM: This paper provides an overview of the challenges raised by concerns about data confidentiality in the context of health services research, the current methodologies used to ensure data security, and a description of one successful approach to balancing access and privacy. Materials and Methods. We analyze the issues of access and privacy using a conceptual framework based on balancing the risk of reidentification with the utility associated with data analysis. The guiding principle should be to generate released data that are as close to the maximum acceptable risk as possible. HIPAA and other privacy measures can perhaps be seen as having had the effect of lowering the "maximum acceptable risk" level and rendering some data unreleasable. RESULTS: We discuss the levels of risk and utility associated with different types of data used in health services research and the ability to link data from multiple sources as well as current models of data sharing and their limitations. DISCUSSION: One particularly compelling approach is to establish a remote access "data enclave," where statistical protections are applied to the data, technical protections ensure compliance with data-sharing requirements, and operational controls limit researchers' access to the data they need for their specific research questions. CONCLUSION: We recommend reducing delays in access to data for research, increasing the use of remote access data enclaves, and disseminating knowledge and promulgating standards for best practices related to data protection.