Appointing early-career researchers to positions of influence within scientific societies would be mutually beneficial for both.
![Figure][1] At the AAAS meeting, Hamburg said scientists must address cultural shifts in their fields. PHOTO: ROBB COHEN PHOTOGRAPHY & VIDEO The American Association for the Advancement of Science has joined 77 leading academic and professional societies in a new group to address sexual harassment in science, technology, engineering, mathematics, and medicine (STEMM). The Societies Consortium on Sexual Harassment in STEMM, launched 15 February, acknowledges the unique role that professional societies have in setting standards and taking action on sexual and gender harassment in the sciences, its leaders said at the 2019 AAAS Annual Meeting in Washington, D.C. "We need to put our positions on the record," said AAAS senior adviser Shirley Malcom during a panel session that announced the consortium. "Harassment of any kind is death to our enterprise. We are trying to attract and encourage talent, but when we don't provide a climate that is safe, we either push them out or we don't get them in to begin with." The consortium will provide research, resources, and guidance to address sexual harassment in the member societies, as well as more broadly in the fields they represent. As a start, the group will focus on model policies and procedures for society honors and awards. In September 2018, the AAAS Council approved a new policy that established sexual and gender-based harassment as a breach of professional ethics that could lead to the revocation of AAAS Fellow status. AAAS has also joined the American Educational Resource Association and 73 scientific societies in opposing proposed changes to the federal Title IX law that would narrow the definition of sexual harassment and restrict processes for reporting harassment at U.S. schools and colleges. AAAS "recognizes that in our role of defending the conditions under which science can thrive, we must promote diversity, protect against bias, and foster opportunity," the society's CEO, Rush Holt, said at a breakfast for international reporters at the Annual Meeting. A 2018 analysis by the U.S. National Academies concluded that more than 50% of women faculty and staff, and 20 to 50% of women students, at U.S. academic institutions report having been sexually harassed. These reports and others confirm that the scientific community "is not immune" to problems of harassment and prejudice that have gained prominence in recent years, said Margaret Hamburg in her presidential address to open the 2019 meeting. "We must recognize that, in our own community, certain groups are, and have always been, disenfranchised in ways that harm well-being and prevent people from fulfilling their potential," said Hamburg, who now serves as AAAS Board chair. "It is no longer enough to be concerned, even outraged, by this problem. It's time to fix it." Attendees discussed issues related to women and underrepresented minorities across several scientific symposia and career workshops throughout the meeting, including the disparate numbers of women in the life sciences compared to engineering and computer science, the underrepresentation of women as first and last authors in top-tier journal papers, and the specific challenges faced by minorities in the science, technology, engineering, and mathematics (STEM) career pipeline. Harassment, bias, and disenfranchisement of women and underrepresented minorities take a toll on the national research and innovation enterprise, said Kelvin Droegemeier, head of the U.S. Office of Science & Technology Policy (OSTP), in a keynote speech at the meeting. "The enhancement of diversity in STEM is absolutely essential. It is not an option, it is a national imperative and progress is needed right now." The speech was Droegemeier's first major public address since taking on the role of White House OSTP director in January. Echoing remarks by Hamburg and others at the meeting, Droegemeier suggested that scientists could "light a path for others" on the issue of harassment. "The standard of behavior that we expect from the scientific community must apply everywhere that research is conducted." The Washington, D.C., meeting, held from 14 through 17 February, was the 185th gathering of AAAS. Under the theme "Science Transcending Boundaries," participants discussed ways to enhance and protect science's international collaborations from trends such as the rise in nationalism in the United States and other countries. "We want to continue to support and emphasize that kind of science which has proven so productive rather than retreat into an approach that is really focused on what we are doing domestically," said Hamburg, who chose the meeting theme at the start of her AAAS presidency. Other topics at the meeting blurred boundaries between scientific disciplines and suggested new ways for researchers to work across their fields. In several symposia and lectures, speakers noted the importance of collaborations with social science researchers in order to meet the challenges posed by robotics and artificial intelligence, respond to natural disasters, and prepare for the local economic impacts of climate change. Family Science Days, a free weekend event held by AAAS in conjunction with its Annual Meeting since 2004, gave the public a chance to do experiments like extracting strawberry DNA and to participate in conversations with researchers-with some interviews conducted by students wielding reporters' notebooks courtesy of the public engagement program Science Storytellers. "What makes Family Science Days unique is that it is incredibly interactive," said Stacey Baker, who organizes the event for the AAAS Center for Public Engagement with Science and Technology. "When deciding who's exhibiting, everything is based on what hands-on activity they're providing for the kids. It's a place where they can really jump right in and experience the science for themselves." [1]: pending:yes
Communication within the scientific community without twitter has become hard to imagine. It was only a matter of time, then, until someone started examining what makes a tweet scientific in itself. Dr Athanasios Mazarakis has examined this more closely and, in his guest article, reveals what he discovered when researching the scientific character of tweets.
Early career researchers appear to be at the vanguard of open research, with them reporting more positive attitudes towards sharing of code compared to more experienced researchers.
![][1] ILLUSTRATION: DAVIDE BONAZZI/SALZMANART Many government data, such as sensitive information on individuals' taxes, income, employment, or health, are available only to accredited users within a secure computing environment. Though they can be cumbersome to access, such microdata can allow researchers to pursue questions that could not be addressed with only public data ([ 1 ][2]). However, researchers using confidential data are inexorably challenged with regard to research reproducibility ([ 2 ][3]). Empirical results cannot be easily reproduced by peers and journal referees, as access to the underpinning data are restricted. We describe an approach that allows researchers who analyze confidential data to signal the reproducibility of their research. It relies on a certification process conducted by a specialized agency accredited by the confidential-data producers and which can guarantee that the code and the data used by a researcher indeed produce the results reported in a scientific paper. In general, research is said to be reproducible if the researchers provide all the resources such as computer code, data, and documentation required to obtain published results ([ 3 ][4], [ 4 ][5]). Reproducibility has the potential to serve as a minimum standard for judging scientific claims ([ 5 ][6], [ 6 ][7]). Recent promising initiatives to facilitate reproducible research include new research environments (e.g., Code Ocean, Popper convention, Whole Tale), workflow systems (e.g., Kepler, Kurator), and dissemination platforms or data repositories (e.g., DataHub, Dataverse, openICPSR, IEEE DataPort, Mendeley). The journal BioStatistics introduced a process in which an editorial board member aims to reproduce the results in a new submission using the code and data provided by the authors ([ 7 ][8]). Other examples of internal reproducibility assessments include the Applications and Case Studies of the Journal of the American Statistical Association ([ 8 ][9]) or the artifact evaluation process of the Principles and Practice of Parallel Programming (PPoPP) conferences. Alternatively, the reproducibility review can be outsourced to a third party, as in the partnership between the American Journal of Political Science (AJPS) and the Odum Institute ([ 9 ][10]). Yet, despite the proliferation of such efforts, current computational research does not always comply with the most basic principles of reproducibility ([ 10 ][11], [ 11 ][12]). Use of confidential data are often mentioned as a major impediment ([ 12 ][13]). Since the end of the 1970s, with the development of computers and a growing concern about privacy protection, legal frameworks regarding access to sensitive personal information have been reinforced in most countries. Though initially only direct identification (e.g., name, address, and social security number) was considered for defining confidentiality, the perimeter has been gradually enlarged to indirect identification that points to the use of multiple variables that potentially lead to a risk of identification ([ 6 ][7]). Given the extension of the legal spectrum of confidential data, a growing fraction of data used in science can fall into this category. One possible approach to engaging in reproducible research with confidential data is to generate synthetic data by applying an information-preserving but anonymizing transformation to the initial data ([ 13 ][14]). By contrast, all Public Library of Science (PLOS) journals request that whenever data cannot be accessed by other researchers, a public dataset that can be used to validate the original conclusions must be provided. An alternative approach relies on improving the accessibility of restricted data for researchers-for example, the research passport proposed by the Inter-university Consortium for Political and Social Research, or the DataTags framework developed within Dataverse and the multidisciplinary Privacy Tools Project. The natural tension between confidentiality and reproducibility could be alleviated by using a third-party certification agency to formally test whether the results in the tables and figures of a given scientific article can be reproduced from the computer code and the confidential data used by the researcher. A first attempt to implement such an external certification process is under way in France. Explicitly designed to deal with confidential data, the reproducibility assessment, like the original analysis, is conducted within a restricted-access data environment. In France, the Centre d'Accès Sécurisé aux Données (CASD) is a public research infrastructure that allows users to access and work with government confidential data under secured conditions. This center currently provides access to data from the French Statistical Institute and the French Ministries for Finance, Justice, Education, Labor, and Agriculture, as well as Social Security contributions and health data. The application process for researchers to get access to the CASD datasets takes around 6 months and requires a presentation of the research project before the French Statistical Secrecy Committee, which gathers data producers. Once the accreditation is granted, CASD creates a virtual machine allowing the researcher to access the specific source datasets required for the project, as well as the required statistical software. Remote access to the virtual machine is made possible thanks to a specific piece of hardware provided by CASD, which includes a fingerprint biometric reader. Since the inception of CASD in 2010, the question of allowing journal referees to get access to data used by researchers has been heavily debated. However, both the legal framework and the technical restrictions made intermittent and short-period access for referees difficult. The Certification Agency for Scientific Code and Data (cascad, [www.cascad.tech][15]) is a not-for-profit certification agency created by academics (all coauthors of this paper) with the support of the French National Centre for Scientific Research, foundations, universities, and local governments. During initial meetings between cascad and CASD teams, they quickly understood the mutual benefit of joining forces to design a reproducibility certification process for confidential data. Thanks to this partnership, cascad was granted a permanent accreditation by the French Statistical Secrecy Committee to all 280 datasets available on CASD. This first-of-its-kind accreditation was motivated by the fact that cascad was providing a solution to the long-recognized problem of the lack of reproducibility of research based on confidential data. Also key for the approval was that the whole certification process remains within the CASD environment and that no data can ever be downloaded. When an author requests a cascad certification for a paper, he or she needs to provide the paper, the computer code used in the analysis, and any additional information (software version, readme files, etc.) required to reproduce the results. Then, a reproducibility reviewer, who is a full-time cascad employee specialized in the software used by the author, accesses a CASD virtual machine that is a clone of the one used by the author. It includes a copy of the source datasets and of the author's computer code, as well as all software required to run the code. The reviewer executes the code, compares the output with the results displayed in the tables and figures of the paper, and lists any potential discrepancies in an execution report. In practice, such discrepancies can arise because of typos in the manuscript, numerical convergence issues, or differences in software package versions. This execution report is transferred to a cascad reproducibility editor, a senior researcher specialized in the author's research field, who ultimately decides on the reproducibility of the article. Lastly, a reproducibility certificate is sent to the author and is stored in the cascad database. An example of a study recently certified by cascad is one that proposes a direct measure of tax-filing inefficiency in French cohabiting couples ([ 14 ][16]). The analysis relies on the Echantillon Démographique Permanent , an administrative dataset only available through CASD that combines information from birth, death, and marriage registers; electoral registers; censuses; tax returns; and pay slips. All the tables and figures of the paper have been reproduced by a cascad reproducibility reviewer from the source datasets, and Python scripts provided by the authors [see certificate ([ 15 ][17])]. While complying with strict data confidentiality rules, the cascad-CASD partnership offers several advantages: (i) signal research reproducibility when data are confidential. The author can transfer the reproducibility certificate to an academic journal when submitting a new manuscript, similar to the reproducibility badges introduced by the Association for Computing Machinery; (ii) outsource reproducibility review. External certification enriches the peer review process, but this extra step is outsourced by academic journals, as in the AJPS-Odum partnership. The staff of the certification agency is specialized and has more time than editorial teams at academic journals; (iii) provide economies of scale to the research community. This model connects a data-provision organization (CASD, a single entry point to a large number of data producers) and a reproducibility certification organization (cascad, a single entry point to a large number of journals and researchers). The cascad-CASD model is a generalization of the standard reproducibility process in which a single researcher goes through the whole reproducibility process on his or her own, obtaining similar data and redoing the analysis; (iv) speed up reproducibility review. Any skeptical researcher can still seek to reproduce the work himself or herself, but unlike researchers who need to go through a 6-month application process, cascad reviewers benefit from a fast-track process (2 days) to access any data necessary to conduct the reproducibility assessment. The certification process is supposed to be completed within 2 weeks; (v) ease replication and robustness tests. Once certification is completed, the computer code and detailed information about the source datasets (metadata) can be publicly posted on the Zenodo archive and used to facilitate additional replication and robustness analyses. Undoubtedly, the biggest challenge for any new certification service is to build trust. To build trust and increase credibility, cascad implements a transparent and detailed certification process. For each certification, all the actions, interactions, and problems that occurred during the process are recorded. Furthermore, all operations carried out within the virtual machine by the reviewer are recorded and traceable. Once the reviewing process is over, the environment is closed, sealed, and archived. The recorded operations and output can be referenced externally and shared with journal editors after proper accreditation. Trust by data producers makes the process feasible, and trust by academic journals makes the process useful and worthwhile. Cascad has the trust of data producers at CASD, who want their data to be useful to society and accessible for reproducibility. Now cascad needs to convince researchers and journals to value its certificates. Overall, the experience with cascad thus far suggests that preserving confidentiality and privacy does not necessarily have to lead to opaque and nonreproducible research. 1. [↵][18]1. L. Einav, 2. J. Levin , Science 346, 1243089 (2014). [OpenUrl][19][Abstract/FREE Full Text][20] 2. [↵][21]1. C. Lagoze, 2. L. Vilhuber , Chance 30, 68 (2017). [OpenUrl][22] 3. [↵][23]1. A. Antoniadis, 2. G. Oppenheim 1. J. B. Buckheit, 2. D. L. Donoho , in Wavelets and Statistics, A. Antoniadis, G. Oppenheim, Eds., Lecture Notes in Statistics (Springer, New York, 1995), vol. 103, pp. 55-81. [OpenUrl][24] 4. [↵][25]1. V. Stodden et al ., Science 354, 1240 (2016). [OpenUrl][26][Abstract/FREE Full Text][27] 5. [↵][28]1. G. Christensen, 2. E. Miguel , J. Econ. Lit. 56, 920 (2018). [OpenUrl][29] 6. [↵][30]1. Y.-A. de Montjoye et al ., Sci. Data 5, 180286 (2018). [OpenUrl][31] 7. [↵][32]1. R. D. Peng , Science 334, 1226 (2011). [OpenUrl][33][Abstract/FREE Full Text][34] 8. [↵][35]1. M. Fuentes , Amstat News (2016); . 9. [↵][36]1. T.-M. Christian, 2. S. Lafferty-Hess, 3. W. G. Jacoby, 4. T. Carsey , Int. J. Digit. Curation 13, 114 (2018). [OpenUrl][37] 10. [↵][38]1. A. C. Chang, 2. P. Li , Am. Econ. Rev. 107, 60 (2017). [OpenUrl][39] 11. [↵][40]1. V. Stodden, 2. J. Seiler, 3. Z. Ma , Proc. Natl. Acad. Sci. U.S.A. 115, 2584 (2018). [OpenUrl][41][Abstract/FREE Full Text][42] 12. [↵][43]1. J. K. Harris et al ., PLOS ONE 13, e0202447 (2018). [OpenUrl][44] 13. [↵][45]1. B. E. Shepherd, 2. M. Blevins Peratikos, 3. P. F. Rebeiro, 4. S. N. Duda, 5. C. C. McGowan , Am. J. Epidemiol. 186, 387 (2017). [OpenUrl][46] 14. [↵][47]1. O. Bargain, 2. D. Echevin, 3. N. Moreau, 4. A. Pacifico , working paper (2019); . 15. [↵][48][https://doi.o rg/10.5281/zenodo.3256633][49]. Acknowledgments: We are grateful to the anonymous referees and to conference participants at the 2018 Conference of European Statistics Stakeholders (Bamberg, Germany) and 2019 Advances in Social Sciences using Administrative and Survey Data (Paris, France) for their comments. We thank the French Statistical Secrecy Committee and its president Jean-Eric Schoettl, the French National Research Agency (ANR-10-EQPX-17), the French National Center for Scientific Research (CNRS), the region Centre-Val de Loire, and the HEC Paris Foundation for their support. [1]: /embed/graphic-1.gif [2]: #ref-1 [3]: #ref-2 [4]: #ref-3 [5]: #ref-4 [6]: #ref-5 [7]: #ref-6 [8]: #ref-7 [9]: #ref-8 [10]: #ref-9 [11]: #ref-10 [12]: #ref-11 [13]: #ref-12 [14]: #ref-13 [15]: http://www.cascad.tech [16]: #ref-14 [17]: #ref-15 [18]: #xref-ref-1-1 "View reference 1 in text" [19]: {openurl}?query=rft.jtitle%253DScience%26rft.stitle%253DScience%26rft.aulast%253DEinav%26rft.auinit1%253DL.%26rft.volume%253D346%26rft.issue%253D6210%26rft.spage%253D1243089%26rft.epage%253D1243089%26rft.atitle%253DEconomics%2Bin%2Bthe%2Bage%2Bof%2Bbig%2Bdata%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscience.1243089%26rft_id%253Dinfo%253Apmid%252F25378629%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [20]: 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#xref-ref-4-1 "View reference 4 in text" [26]: {openurl}?query=rft.jtitle%253DScience%26rft.stitle%253DScience%26rft.aulast%253DStodden%26rft.auinit1%253DV.%26rft.volume%253D354%26rft.issue%253D6317%26rft.spage%253D1240%26rft.epage%253D1241%26rft.atitle%253DEnhancing%2Breproducibility%2Bfor%2Bcomputational%2Bmethods%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscience.aah6168%26rft_id%253Dinfo%253Apmid%252F27940837%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [27]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6Mzoic2NpIjtzOjU6InJlc2lkIjtzOjEzOiIzNTQvNjMxNy8xMjQwIjtzOjQ6ImF0b20iO3M6MjI6Ii9zY2kvMzY1LzY0NDkvMTI3LmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ== [28]: #xref-ref-5-1 "View reference 5 in text" [29]: 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{openurl}?query=rft.jtitle%253DInt.%2BJ.%2BDigit.%2BCuration%26rft.volume%253D13%26rft.spage%253D114%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [38]: #xref-ref-10-1 "View reference 10 in text" [39]: {openurl}?query=rft.jtitle%253DAm.%2BEcon.%2BRev.%26rft.volume%253D107%26rft.spage%253D60%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [40]: #xref-ref-11-1 "View reference 11 in text" [41]: {openurl}?query=rft.jtitle%253DProc.%2BNatl.%2BAcad.%2BSci.%2BU.S.A.%26rft_id%253Dinfo%253Adoi%252F10.1073%252Fpnas.1708290115%26rft_id%253Dinfo%253Apmid%252F29531050%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [42]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoicG5hcyI7czo1OiJyZXNpZCI7czoxMToiMTE1LzExLzI1ODQiO3M6NDoiYXRvbSI7czoyMjoiL3NjaS8zNjUvNjQ0OS8xMjcuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9 [43]: #xref-ref-12-1 "View reference 12 in text" [44]: {openurl}?query=rft.jtitle%253DPLOS%2BONE%26rft.volume%253D13%26rft.spage%253De0202447%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [45]: #xref-ref-13-1 "View reference 13 in text" [46]: {openurl}?query=rft.jtitle%253DAm.%2BJ.%2BEpidemiol.%26rft.volume%253D186%26rft.spage%253D387%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [47]: #xref-ref-14-1 "View reference 14 in text" [48]: #xref-ref-15-1 "View reference 15 in text" [49]: https://doi.org/10.5281/zenodo.3256633
Science benefits when junior scientists sign up as reviewers. It's also good for their careers.
Early career researchers (ECRs) will play a key role in transitioning the scientific community to more widespread use of Open Science from pre-registration to publication, but they also face unique challenges in adopting these practices.
Many researchers have strong views on peer review. To find out what early-career researchers think we conducted a survey in which we asked 10 questions about different aspects of peer review.
The Manifesto for Early Career Researchers calls for increasing the recognition of the research activity and fostering diversified research careers at a European level.
Mentorship in academia facilitates personal growth through pairing trainees with mentors who can share insight and expertise.Expertise can be purely academic, on work‐life balance, personal branding and networking, or general career advice. Mentoring has been shown to be beneficial for mentees, both in terms of objective research productivity and subjective outcomes. Several institutions/organizations have formal in‐person mentoring programs that pair early‐ to mid‐career researchers with mentors who are not their direct supervisors. With global integration in science, however, geographical proximity between mentors and mentees is relevant to a lesser degree.
Learn how two early career publishers are tackling the thorny issue of pay equity and inclusion in today's interview with Rebecca Bostock (Ohio State UP) and Dominique J Moore (University of Illinois Press).
The Early-Career Advisory Group is looking for five early-career researchers to join our advisory group and help us realise our mission to transform research communication.
Grants are becoming a more common component of a faculty candidate’s resume for biomedical faculty positions.
An analysis of the eligibility rules, assessment criteria and potential gender bias in best researcher and best paper awards from broad-scope ecology and evolution journals and societies shows a lack of assessment transparency, few attempts to foster equitable access and minimal consideration of open science.
Young scientists are expected to change country and jobs every few years on average to get a chance to progress their academic career. Mobility in science stems from a long tradition. It is favoured for bringing very enriching experiences. But post docs and their scientific work do not always benefit from mobility. Here, EuroScientist looks into how being on the move every few years affects the life of researchers and looks at ways of enhancing work/life balance.
Early career researchers commonly peer review manuscripts on behalf of invited reviewers, often without receiving feedback or being named to the journal.
Responding to early-career researchers' honest questions with accusations of misconduct is a travesty of open science.
This paper analyses an approach to fostering the skills required for successful cross-disciplinary collaboration from the perspective of an interdisciplinary group of early-career researchers.
Little is known about the long-term effects of early-career setback. Here, the authors compare junior scientists who were awarded a NIH grant to those with similar track records, who were not, and find that individuals with the early setback systematically performed better in the longer term.
Stress and long working hours are regrettably common among early-career researchers, reveals a survey by the group the Young Academy of Europe.
"Do you have any advice for future graduate students?" I asked. The student had recently defended his Ph.D., and I was conducting an exit interview-something I do with every graduating biomedical Ph.D. student at my university, where I am in charge of evaluating our medical school's Ph.D. training programs. He sat back in his chair and thought for a minute before responding: He wished he had started to plan for his post-Ph.D. career earlier. My shoulders dropped and I let out a sigh. "Program directors recommend this to incoming students every year, but some don't seem to hear it," I said. "How do you think we can get them to listen?" This time, he didn't hesitate. "They are graduate students in science ," he exclaimed. "Show them the data!" > "Even when you're just getting started, you need to look forward." That was my aha moment. I immediately began to document the responses to this question in subsequent interviews. It has been 3 years now, and the data I've collected confirm my suspicions-the same answers come up again and again. As a new cohort of Ph.D. students starts grad school this fall, here are the five pieces of advice graduates offer most frequently. Thirty-two percent of graduating students said this is the most critical decision a Ph.D. student can make. Many students gravitate toward mentors who work in areas they find interesting and exciting, but it is also important to think about what style of mentoring you respond to best. Finding a mentor with the right mentoring approach for you is at least as important as finding one who studies a specific topic. You need time to (a) decide which career paths you find appealing and (b) start preparing for those careers. Twenty percent of graduating students recommended exploring future careers as early as possible so you can use your time in grad school to build additional skills you will need. To learn about specific professions, you can conduct informational interviews, attend seminars where alumni discuss their careers, do an internship, or engage in a variety of other options. Graduate school is full of ups and downs. Thirteen percent of graduates said that if you feel the need to talk to someone on or off campus, don't hesitate. "If you are not happy, try to do something about it and make a change," one student said. If you feel isolated, another student recommended joining a campus group to connect with others. Twelve percent of graduates recommended that students consistently and critically evaluate their progress throughout their training. Make an outline of your research and career goals and when you want to achieve them, and hold yourself to that plan. Some students use an individual development plan to prompt discussions with their mentor and thesis committee. But don't wait for these meetings; setting goals and holding yourself accountable should be a continuous habit. This looks different for different people, but don't ignore it. You should expect to work hard in grad school, but the right work-life balance can have an important influence on your mental health and overall quality of life. Nine percent of graduates recommended finding something that helps you unwind, such as pursuing hobbies, getting together with friends, or volunteering in the community. Observant readers may notice that the numbers above only add up to 86%. Other pieces of advice included be assertive and ask for what you need, learn to trust your experimental results as long as the controls work, and plan your projects around what's needed for a publishable paper. But the most important thing is to take these pointers to heart early on. Even when you're just getting started, you need to look forward.
While we need to alert researchers to the presence of predatory journals, we should mostly put our efforts into transforming the academic research environment and reward systems, raising standards and developing true collegiality both within and between institutions.
Here, the authors study mentorship in scientific collaborations, and find that mentorship quality predicts the scientific impact of protégés post mentorship. Moreover, female protégés collaborating with male mentors become more impactful post mentorship than those who collaborate with female mentors.
By examining publication records of scientists from four disciplines, the authors show that coauthoring a paper with a top-cited scientist early in one's career predicts lasting increases in career success, especially for researchers affiliated with less prestigious institutions.
