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Climb atop shoulders and wait for funerals. That, suggested Newton and then Planck, is how science advances (more or less). We've come far since then, but many notions about how people and practices, policies, and resources influence the course of science are still more rooted in traditions and intuitions than in evidence. We can and must do better, lest we resign ourselves to “intuition-based policy” when making decisions and investments aimed at driving scientific progress. Science invited experts to highlight key aspects of the scientific enterprise that are steadily yielding to empirical investigation—and to explain how Newton and Planck got it right (and Einstein got it wrong). — Brad Wible

One of the central goals in any scientific endeavor is to understand causality. Experiments that seek to demonstrate a cause/effect relation most often manipulate the postulated causal factor. Aarts et al. describe the replication of 100 experiments reported in papers published in 2008 in three high-ranking psychology journals. Assessing whether the replication and the original experiment yielded the same result according to several criteria, they find that about one-third to one-half of the original findings were also observed in the replication study. Science , this issue 10.1126/science.aac4716 A large-scale assessment suggests that experimental reproducibility in psychology leaves a lot to be desired. Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.

The science of science (SciSci) is based on a transdisciplinary approach that uses large data sets to study the mechanisms underlying the doing of science—from the choice of a research problem to career trajectories and progress within a field. In a Review, Fortunato et al. explain that the underlying rationale is that with a deeper understanding of the precursors of impactful science, it will be possible to develop systems and policies that improve each scientist's ability to succeed and enhance the prospects of science as a whole. Science , this issue p. eaao0185 Identifying fundamental drivers of science and developing predictive models to capture its evolution are instrumental for the design of policies that can improve the scientific enterprise—for example, through enhanced career paths for scientists, better performance evaluation for organizations hosting research, discovery of novel effective funding vehicles, and even identification of promising regions along the scientific frontier. The science of science uses large-scale data on the production of science to search for universal and domain-specific patterns. Here, we review recent developments in this transdisciplinary field.

There is a widely held perception that science is becoming more international—through multi-national collaborations—and interdisciplinary, drawing on knowledge from multiple domains. However, these hypothesized trends have not yet been quantitatively characterized. With the publication metadata from OpenAlex, we examine trends in two groups of journals: disciplinary journals in natural sciences, life sciences, social sciences, and multidisciplinary journals that publish articles in multiple fields. Supporting existing perceptions, we find an almost universal trend towards increasing internationalization of both sets of journals. Nevertheless, we find disparities: medicine journals are less international than journals in other disciplines and do not increase their levels of internationalization, whereas physics journals appear to be segregating between those that are international and those that are not. We also find that multidisciplinary journals have undergone significant shifts in their disciplinary focuses over the past century, whereas disciplinary journals appear to have largely maintained their degree of interdisciplinarity.

This study examined the patterns and nature of science co-publications between the USA and China. Based on a scientometric study of Scopus co-publications over the past 5 years, the results demonstrated a continuous rise of bilateral collaboration between the two countries. Challenging the US political rhetoric and attempts to curb international research engagement with China, the findings demonstrated ways that China plays a leading role in US-China research collaboration, based on first authorship and governmental funding patterns. Findings also showed that over the past 5 years, US research article publications would have declined without co-authorship with China, whereas China’s publication rate would have risen without the USA. Using zero-sum and positive-sum frameworks, this study shows the benefits of US collaboration with China for both the US nation-state and global science.

In this article, Maria Ong, Carol Wright, Lorelle Espinosa, and Gary Orfield review nearly forty years of scholarship on the postsecondary educational experiences of women of color in science, technology, engineering, and mathematics (STEM). Their synthesis of 116 works of scholarship provides insight into the factors that influence the retention, persistence, and achievement of women of color in STEM fields. They argue that the current underrepresentation of women of color in STEM fields represents an unconscionable underutilization of our nation's human capital and raises concerns of equity in the U.S. educational and employment systems. They refute the pervasive myth that underrepresented minority women are less interested in pursuing STEM fields and then present a complex portrait of the myriad factors that influence the undergraduate and graduate experiences of women of color in STEM fields. Finally, the authors discuss the policy implications of their findings and highlight gaps in the literature where further research is needed, providing a knowledge base for educators, policy makers, and researchers to continue the mission of advancing the status of women of color in STEM. (Contains 2 tables, 2 figures and 15 notes.)

The goal of all reform documents in science education is to target scientific literacy. Toward that end, having students understand the nature of science (NOS) is a critical component. As it turns out, the development of NOS conceptions is a cognitive learning outcome. Therefore, an explicit approach needs to be promoted and emphasized in the classrooms to address students’ conceptions of NOS. At the same time, the development of NOS conceptions among learners is context dependent. Consequently, different learning frameworks might influence the NOS conceptions of learners in various ways. There are several frameworks to contextualize NOS instruction in relation to three different contexts: history of science (HOS), scientific inquiry (SI), and socioscientific issues (SSI). As such, the aim of this study was to review studies on NOS instruction, categorize the reviewed studies into different contexts, and investigate the effect of these different contexts on the improvement in students’ conceptions of NOS. As a conclusion, implications for future research and classroom practice related to the explicit teaching about NOS in these contexts were discussed.

There is substantial research in science education about students’, teachers’, and scientists’ views of nature of science (NOS). Many studies have used NOS frameworks that focus on particular ideas such as tentativeness of scientific knowledge and cultural embeddedness of science. In this paper, we investigate NOS from the perspective of the Family Resemblance Approach (FRA) which considers clusters of ideas about science in terms of categories that offer a comprehensive analytical lens to studying NOS views. The empirical study re-analyzes NOS views obtained from 7 and 8th grade students, science teachers, and scientists using the FRA lens. Statements from all three groups were obtained using a free-write questionnaire on nature of knowledge and nature of knowing. The statements were reclassified using the FRA framework. Epistemic network analysis (ENA) was applied to the statements produced by each group of participants, and the resulting network models were interpreted and compared. The results show that student and teacher network models possessed no central idea, and more tangible ideas about science were frequently connected. Scientist network models showed more connections across their statements which indicate a higher degree of agreement and coherence among a variety of ideas compared to student and teacher network models. The paper discusses the findings as well as the methodological contributions, and concludes with implications for future research.

Authorship on papers is one of the major currencies of the scientific enterprise. Nevertheless, the contributions of different authors to a given paper have remained relatively opaque. Contributions are generally inferred from the order of authors, and implications of position on the authorship list vary between different investigators and scientific fields. A year ago, a group of editors and publishers across a wide range of disciplines met to discuss how to provide a more systemic solution to make author contributions more transparent. This week, their recommendations have been released ( www.pnas.org/cgi/doi/10.1073/pnas.1715374115 ), and I applaud this effort and urge the wide adoption of this system.

Rebalance incentives to promote culture change The U.S. graduate education system for science technology, engineering, and mathematics (STEM) is widely regarded as among the best in the world. However, evolution in the structure and functioning of the U.S. graduate education system is lagging ongoing changes in the broader scientific enterprise, in the requirements of employers, in the demographics of the student population, and, particularly, in their career ambitions. In response to these disconnects, the U.S. National Academies of Sciences, Engineering, and Medicine (NASEM) recently released a report ( 1 ) that lays out a vision of an ideal modern graduate education in any STEM field and a comprehensive plan to achieve that vision. The report emphasizes core competencies that all students should acquire, a rebalancing of incentives to better reward faculty teaching and mentoring of students, increased empowerment of graduate students, and the need for the system to better monitor and adapt to changing conditions over time. Although these issues have been raised in the past, and some institutions have taken positive steps, graduate students are still too often seen as being primarily sources of inexpensive skilled labor for teaching undergraduates and for performing research. Graduate students should demand the kind of education outlined in the report.