Concept: Natural science
Biologists should submit their preprints to open servers, a practice common in mathematics and physics, to open and accelerate the scientific process.
Gender disparities appear to be decreasing in academia according to a number of metrics, such as grant funding, hiring, acceptance at scholarly journals, and productivity, and it might be tempting to think that gender inequity will soon be a problem of the past. However, a large-scale analysis based on over eight million papers across the natural sciences, social sciences, and humanities reveals a number of understated and persistent ways in which gender inequities remain. For instance, even where raw publication counts seem to be equal between genders, close inspection reveals that, in certain fields, men predominate in the prestigious first and last author positions. Moreover, women are significantly underrepresented as authors of single-authored papers. Academics should be aware of the subtle ways that gender disparities can occur in scholarly authorship.
PhD recipients acquire discipline-specific knowledge and a range of relevant skills during their training in the life sciences, physical sciences, computational sciences, social sciences, and engineering. Empirically testing the applicability of these skills to various careers held by graduates will help assess the value of current training models. This report details results of an Internet survey of science PhDs (n = 8099) who provided ratings for fifteen transferrable skills. Indeed, analyses indicated that doctoral training develops these transferrable skills, crucial to success in a wide range of careers including research-intensive (RI) and non-research-intensive (NRI) careers. Notably, the vast majority of skills were transferrable across both RI and NRI careers, with the exception of three skills that favored RI careers (creativity/innovative thinking, career planning and awareness skills, and ability to work with people outside the organization) and three skills that favored NRI careers (time management, ability to learn quickly, ability to manage a project). High overall rankings suggested that graduate training imparted transferrable skills broadly. Nonetheless, we identified gaps between career skills needed and skills developed in PhD training that suggest potential areas for improvement in graduate training. Therefore, we suggest that a two-pronged approach is crucial to maximizing existing career opportunities for PhDs and developing a career-conscious training model: 1) encouraging trainees to recognize their existing individual skill sets, and 2) increasing resources and programmatic interventions at the institutional level to address skill gaps. Lastly, comparison of job satisfaction ratings between PhD-trained employees in both career categories indicated that those in NRI career paths were just as satisfied in their work as their RI counterparts. We conclude that PhD training prepares graduates for a broad range of satisfying careers, potentially more than trainees and program leaders currently appreciate.
In growing recognition of the importance of how scientific research is designed, performed, communicated, and evaluated, PLOS Biology announces a broadening of its scope to cover meta-research articles.
A restatement of the natural science evidence base concerning neonicotinoid insecticides and insect pollinators
- Proceedings. Biological sciences / The Royal Society
- Published almost 7 years ago
There is evidence that in Europe and North America many species of pollinators are in decline, both in abundance and distribution. Although there is a long list of potential causes of this decline, there is concern that neonicotinoid insecticides, in particular through their use as seed treatments are, at least in part, responsible. This paper describes a project that set out to summarize the natural science evidence base relevant to neonicotinoid insecticides and insect pollinators in as policy-neutral terms as possible. A series of evidence statements are listed and categorized according to the nature of the underlying information. The evidence summary forms the appendix to this paper and an annotated bibliography is provided in the electronic supplementary material.
This study tests if the drives to empathize (E) and systemize (S), measured by the Systemizing Quotient-Revised (SQ-R) and Empathy Quotient (EQ), show effects of sex and academic degree. The responses of 419 students from the Humanities and the Physical Sciences were analyzed in terms of the E-S theory predictions. Results confirm that there is an interaction between sex, degree and the drive to empathize relative to systemize. Female students in the Humanities on average had a stronger drive to empathize than to systemize in comparison to males in the Humanities. Male students in the Sciences on average had a stronger drive to systemize than to empathize in comparison to females in the Sciences. Finally, students in the sciences on average had a stronger drive to systemize more than to empathize, irrespective of their sex. The reverse is true for students in the Humanities. These results strongly replicate earlier findings.
A better understanding of the natural history of model organisms will increase their value as model systems and also keep them at the forefront of research.
Federal funding for basic scientific research is the cornerstone of societal progress, economy, health and well-being. There is a direct relationship between financial investment in science and a nation’s scientific discoveries, making it a priority for governments to distribute public funding appropriately in support of the best science. However, research grant proposal success rate and funding level can be skewed toward certain groups of applicants, and such skew may be driven by systemic bias arising during grant proposal evaluation and scoring. Policies to best redress this problem are not well established. Here, we show that funding success and grant amounts for applications to Canada’s Natural Sciences and Engineering Research Council (NSERC) Discovery Grant program (2011-2014) are consistently lower for applicants from small institutions. This pattern persists across applicant experience levels, is consistent among three criteria used to score grant proposals, and therefore is interpreted as representing systemic bias targeting applicants from small institutions. When current funding success rates are projected forward, forecasts reveal that future science funding at small schools in Canada will decline precipitously in the next decade, if skews are left uncorrected. We show that a recently-adopted pilot program to bolster success by lowering standards for select applicants from small institutions will not erase funding skew, nor will several other post-evaluation corrective measures. Rather, to support objective and robust review of grant applications, it is necessary for research councils to address evaluation skew directly, by adopting procedures such as blind review of research proposals and bibliometric assessment of performance. Such measures will be important in restoring confidence in the objectivity and fairness of science funding decisions. Likewise, small institutions can improve their research success by more strongly supporting productive researchers and developing competitive graduate programming opportunities.
It is known that statistically significant (positive) results are more likely to be published than non-significant (negative) results. However, it has been unclear whether any increasing prevalence of positive results is stronger in the “softer” disciplines (social sciences) than in the “harder” disciplines (physical sciences), and whether the prevalence of negative results is decreasing over time. Using Scopus, we searched the abstracts of papers published between 1990 and 2013, and measured longitudinal trends of multiple expressions of positive versus negative results, including p-values between 0.041 and 0.049 versus p-values between 0.051 and 0.059, textual reporting of “significant difference” versus “no significant difference,” and the reporting of p < 0.05 versus p > 0.05. We found no support for a “hierarchy of sciences” with physical sciences at the top and social sciences at the bottom. However, we found large differences in reporting practices between disciplines, with p-values between 0.041 and 0.049 over 1990-2013 being 65.7 times more prevalent in the biological sciences than in the physical sciences. The p-values near the significance threshold of 0.05 on either side have both increased but with those p-values between 0.041 and 0.049 having increased to a greater extent (2013-to-1990 ratio of the percentage of papers = 10.3) than those between 0.051 and 0.059 (ratio = 3.6). Contradictorily, p < 0.05 has increased more slowly than p > 0.05 (ratios = 1.4 and 4.8, respectively), while the use of “significant difference” has shown only a modest increase compared to “no significant difference” (ratios = 1.5 and 1.1, respectively). We also compared reporting of significance in the United States, Asia, and Europe and found that the results are too inconsistent to draw conclusions on cross-cultural differences in significance reporting. We argue that the observed longitudinal trends are caused by negative factors, such as an increase of questionable research practices, but also by positive factors, such as an increase of quantitative research and structured reporting.
ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software’s ability to handle the requirements of modern science.