- Proceedings of the National Academy of Sciences of the United States of America
- Published about 4 years ago
National randomized experiments and validation studies were conducted on 873 tenure-track faculty (439 male, 434 female) from biology, engineering, economics, and psychology at 371 universities/colleges from 50 US states and the District of Columbia. In the main experiment, 363 faculty members evaluated narrative summaries describing hypothetical female and male applicants for tenure-track assistant professorships who shared the same lifestyle (e.g., single without children, married with children). Applicants' profiles were systematically varied to disguise identically rated scholarship; profiles were counterbalanced by gender across faculty to enable between-faculty comparisons of hiring preferences for identically qualified women versus men. Results revealed a 2:1 preference for women by faculty of both genders across both math-intensive and non-math-intensive fields, with the single exception of male economists, who showed no gender preference. Results were replicated using weighted analyses to control for national sample characteristics. In follow-up experiments, 144 faculty evaluated competing applicants with differing lifestyles (e.g., divorced mother vs. married father), and 204 faculty compared same-gender candidates with children, but differing in whether they took 1-y-parental leaves in graduate school. Women preferred divorced mothers to married fathers; men preferred mothers who took leaves to mothers who did not. In two validation studies, 35 engineering faculty provided rankings using full curricula vitae instead of narratives, and 127 faculty rated one applicant rather than choosing from a mixed-gender group; the same preference for women was shown by faculty of both genders. These results suggest it is a propitious time for women launching careers in academic science. Messages to the contrary may discourage women from applying for STEM (science, technology, engineering, mathematics) tenure-track assistant professorships.
You finished your PhD, have been a postdoc for a while, and you start wondering, “What’s next?” Suppose you come to the conclusion that you want to stay in academia, and move up the ladder to become a principal investigator (PI). How does one reach this goal given that academia is one of the most competitive environments out there? And suppose you do manage to snatch your dream position, how do you make sure you hit the ground running? Here we report on the workshop “P2P - From Postdoc To Principal Investigator” that we organized at ISMB 2012 in Long Beach, California. The workshop addressed some of the challenges that many postdocs and newly appointed PIs are facing. Three experienced PIs, Florian Markowetz (Group Leader, Cambridge Research Institute, Cancer Research UK), Gary Bader (Associate Professor, The Donnelly Centre, University of Toronto), and Philip Bourne (Professor, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego), provided insight into the transition from a trainee to PI and shared advice on how to make the best out it.
International Conference on Nanopore Technology (Shenzhen), 30 March-1 April 2017, Shenzhen, China The International Conference on Nanopore Technology (Shenzhen) was held from 30 March to 1 April 2017 in Shenzhen, China. The goal of the meeting was threefold: leverage the unique properties of nanopore technology to promote transformative advances in medicine, encourage cross-disciplinary collaborations in the research community within China and abroad; and discuss critical challenges that need to be addressed to rapidly advance the field. The meeting was chaired by Peixuan Guo, Endowed chair professor and Director of The Center for RNA Nanobiotechnology & Nanomedicine at The Ohio State University, USA and co-chaired by Xian-En Zhang, distinguished professor of the Institute of Biophysics, Chinese Academy of Sciences, China. The conference was attended by more than 300 academic researchers, hospital administrators, government leaders and scientists from many disciplines across the country from both academic institutions and industry.
Anonymous student evaluations of teaching (SETs) are used by colleges and universities to measure teaching effectiveness and to make decisions about faculty hiring, firing, re-appointment, promotion, tenure, and merit pay. Although numerous studies have found that SETs correlate with various teaching effectiveness irrelevant factors (TEIFs) such as subject, class size, and grading standards, it has been argued that such correlations are small and do not undermine the validity of SETs as measures of professors' teaching effectiveness. However, previous research has generally used inappropriate parametric statistics and effect sizes to examine and to evaluate the significance of TEIFs on personnel decisions. Accordingly, we examined the influence of quantitative vs. non-quantitative courses on SET ratings and SET based personnel decisions using 14,872 publicly posted class evaluations where each evaluation represents a summary of SET ratings provided by individual students responding in each class. In total, 325,538 individual student evaluations from a US mid-size university contributed to theses class evaluations. The results demonstrate that class subject (math vs. English) is strongly associated with SET ratings, has a substantial impact on professors being labeled satisfactory vs. unsatisfactory and excellent vs. non-excellent, and the impact varies substantially depending on the criteria used to classify professors as satisfactory vs. unsatisfactory. Professors teaching quantitative courses are far more likely not to receive tenure, promotion, and/or merit pay when their performance is evaluated against common standards.
Debates over the pros and cons of a “publish or perish” philosophy have inflamed academia for at least half a century. Growing concerns, in particular, are expressed for policies that reward “quantity” at the expense of “quality,” because these might prompt scientists to unduly multiply their publications by fractioning (“salami slicing”), duplicating, rushing, simplifying, or even fabricating their results. To assess the reasonableness of these concerns, we analyzed publication patterns of over 40,000 researchers that, between the years 1900 and 2013, have published two or more papers within 15 years, in any of the disciplines covered by the Web of Science. The total number of papers published by researchers during their early career period (first fifteen years) has increased in recent decades, but so has their average number of co-authors. If we take the latter factor into account, by measuring productivity fractionally or by only counting papers published as first author, we observe no increase in productivity throughout the century. Even after the 1980s, adjusted productivity has not increased for most disciplines and countries. These results are robust to methodological choices and are actually conservative with respect to the hypothesis that publication rates are growing. Therefore, the widespread belief that pressures to publish are causing the scientific literature to be flooded with salami-sliced, trivial, incomplete, duplicated, plagiarized and false results is likely to be incorrect or at least exaggerated.
“Publish or perish” is the time-honored “principle” for academicians who race to accumulate lines under the “publications” section of a curriculum vitae. The original intent of publication-to inform others of findings and further scientific knowledge-has been corrupted by factors including (1) exponential growth of journals and the journal industry, fueled in part by intrusion of the Internet into all aspects of academic life; and (2) adoption of journal metrics (rather than written content) as the measure of scientific quality. The proprietary Thomson Reuters Impact Factor is the most pernicious metric, having caused editors and publishers to change editorial practices to boost the number. At the same time, gullible administrators and government agencies have been persuaded that metrics for the journal in which materials are published can be used as a measure of the worth of individual investigators (and institutions) and their research efforts: simple numbers can be substituted for the burdensome effort required to read and assess research quality. Thus, granting of research funds, awarding of academic rank and tenure, and determination of salaries (including bonus payments) have become tied to manipulable journal metrics rather than the significance or quality of reported research. Therefore, it is no wonder that the integrity of science is more often being questioned. How should a young investigator approach the “publish or perish” dilemma? Performing sound research and preparing optimal materials for publication must remain the overriding goals: properly articulate the question addressed by the study; thoroughly document all methods and case information; carefully describe results including any conflicting or negative findings; discuss the importance of the findings along with how the results address the initial question and whether findings refute or confirm previous studies; prepare properly cited bibliographic references; list all author contributions, potential conflicts of interest, financial support, and required ethical approvals; and provide a catchy title and an abstract containing sufficient information that other investigators perusing scientific indices will be enticed to read the published article. Submit the completed manuscript to the most appropriate journal based on that journal’s previously published content and relevance to the field of study regardless of journal metrics. On publication, notify investigators in the same field to ask for their comments on the work. Thus, an individual will become known for the quality of his or her work product and the worshiping of publication metrics will be unnecessary.
In the most recent cohort, 2002-2015, the experiences of men and women differed substantially among STEM disciplines. Female assistant professors were more likely than men to leave the institution and to leave without tenure in engineering, but not in the agricultural, biological and biomedical sciences and natural resources or physical and mathematical sciences. In contrast, the median times to promotion from associate to full professor were similar for women and men in engineering and the physical and mathematical sciences, but one to two years longer for women than men in the agricultural, biological and biomedical sciences and natural resources.
Publication of scientific research papers is important for professionals working in academic medical centres. Quantitative measures of scientific output determine status and prestige, and serve to rank universities as well as individuals. The pressure to generate maximum scientific output is high, and quantitative aspects may tend to dominate over qualitative ones. How this pressure influences professionals' perception of science and their personal well-being is unknown.
Abstract Fifty years after Title IX, women remain sparsely represented in high ranks and leadership in academic medicine. Although men and women enter the career pipeline at similar rates, academic medicine does not equivalently advance them. Currently, women account for 32% of associate professors, 20% of full professors, 14% of department chairs, and 11% of deans at U.S. medical schools-far from the near sex parity seen in medical students since the 1990s. Over 30 years of research confirms that gender stereotypes can operate to disadvantage women in review processes and consequently bar their advancement in domains like science and medicine. The authors present three vignettes to illustrate how gender stereotypes can also operate to disadvantage women in social interactions by positioning them in the “out-group” for many career-advancing opportunities. The authors argue that policies alone will not achieve gender equity in the academic medicine workforce. Addressing stereotype-based gender bias is critical for the future of academic medicine. Interventions that treat gender bias as a remediable habit show promise in promoting gender equity and transforming institutional culture to achieve the full participation of women at all career stages. A critical step is to recognize when gender stereotyped assumptions are influencing judgments and decision making in ourselves and others, challenge them as unjust, and deliberately practice replacing them with accurate and objective data.
Unrelated human males regularly interact in groups , which can include higher and lower ranked individuals. In contrast, from early childhood through adulthood, females often reduce group size in order to interact with only one individual of equal rank [1-5]. In many species, when either sex maintains a group structure, unrelated individuals must cooperate with those differing in rank . Given that human males interact more than females in groups, we hypothesized that dyadic cooperation between individuals of differing rank should occur more frequently between human males than females. We examined this hypothesis in academic psychology. Numbers of co-authored peer-reviewed publications were used as an objective measure of cooperation, and professorial status as a measure of rank. We compiled all publications co-authored by full professors with same-sex departmental colleagues over four years in 50 North American universities, and calculated the likelihood of co-authorship in relation to the number of available professors in the same department (Supplemental information). Among those of equal status (full professors) there was no gender difference for likelihood of co-authorship: women and men were equally likely to co-author publications with another full professor of the same gender. In contrast, male full professors were more likely than female full professors to co-author publications with a same-gender assistant professor. This is consistent with a tendency for men to cooperate more than women with same-sex individuals of differing rank.