Trends in Brain Research: A Bibliometric Analysis.

BACKGROUND: Bibliometrics methods have allowed researchers to assess the popularity of brain research through the ever-growing number of brain-related research papers. While many topics of brain research have been covered by previous studies, there is no comprehensive overview of the evolution of brain research and its various specialties and funding practices over a long period of time. OBJECTIVE: This paper aims to (1) determine how brain research has evolved over time in terms of number of papers, (2) countries' relative and absolute positioning in terms of papers and impact, and (3) how those various trends vary by area. METHODS: Using a list of validated keywords, we extracted brain-related articles and journals indexed in the Web of Science over the 1991-2020 period, for a total of 2,467,708 papers. We used three indicators to perform: number of papers, specialization, and research impact. RESULTS: Our results show that over the past 30 years, the number of brain-related papers has grown at a faster pace than science in general, with China being at the forefront of this growth. Different patterns of specialization among countries and funders were also underlined. Finally, the NIH, the European Commission, the National Natural Science Foundation of China, the UK Medical Research Council, and the German Research Foundation were found to be among the top funders. CONCLUSION: Despite data-related limitations, our findings provide a large-scope snapshot of the evolution of brain research and its funding, which may be used as a baseline for future studies on these topics.

Predicting Research Productivity in STEM Faculty: The Role of Self-determined Motivation.

How are university faculty members in STEM disciplines motivated to conduct research, and how does motivation predict their success? The current study assessed how multiple types of self-determined motivation predict research productivity in a sample of 651 faculty from 10 US institutions. Using structural equation modeling, the basic psychological needs of autonomy and competence predicted autonomous motivation (enjoyment, value) that, in turn, was the strongest predictor of self-reported research productivity. Using negative binomial regression, autonomous motivation was the strongest predictor of faculty publications and citations, with a one-standard deviation increase in autonomous motivation (approximately a half response option on a 1-5 Likert scale) corresponding to an 11.63% increase in publications and a 22.57% increase in citations over a three-year period. Occupational and social-environmental background variables (e.g., research percentage on contract, career age, balance, collegiality), as well as controlled motivation (guilt, rewards), had comparatively limited predictive effects. These results are of relevance to higher education institutions aiming to support scholarly productivity in STEM faculty in identifying specific beneficial and detrimental aspects of faculty motivation that contribute to measurable gains in research activity.

The relationship between parenting engagement and academic performance.

Gender differences in research productivity have been well documented. One frequent explanation of these differences is disproportionate child-related responsibilities for women. However, changing social dynamics around parenting has led to fathers taking an increasingly active role in parenting. This demands a more nuanced approach to understanding the relationship between parenting and productivity for both men and women. To gain insight into associations between parent roles, partner type, research productivity, and research impact, we conducted a global survey that targeted 1.5 million active scientists; we received viable responses from 10,445 parents (< 1% response rate), thus providing a basis for exploratory analyses that shed light on associations between parenting models and research outcomes, across men and women. Results suggest that the gendered effect observed in production may be related by differential engagement in parenting: men who serve in lead roles suffer similar penalties for parenting engagement, but women are more likely to serve in lead roles and to be more engaged across time and tasks, therefore suffering a higher penalty. Taking a period of parental leave is associated with higher levels of productivity; however, the productivity advantage dissipates after six months for the US-sample, and at 12-months for the non-US sample. These results suggest that parental engagement is a more powerful variable to explain gender differences in academic productivity than the mere existence of children, and that policies should factor these labor differentials into account.

From art to science: A bibliometric analysis of architectural scholarly production from 1980 to 2015.

According to recent literature on "architecture" as a discipline, practical knowledge relevant to its process of making has decreased in importance in favor of a more academic approach. Using data derived from Ulrich's Periodical Directory and Clarivate Analytics's Web of Science, this paper suggests providing empirical evidence supporting of such shift, as revealed by an overview of the dissemination practices in architecture scholarly production between 1980 and 2015. Our results support that architecture is becoming increasingly academic, as demonstrated by the growing proportion of articles and journals intended for scholars rather than for professionals. We also show that architecture is increasingly global, with decreased interest in local and/or national issues and the growing prevalence of English as a publication language. Finally, this academic focus is manifested in references cited by architectural papers with the gradual substitution of professional and artistic oriented knowledge, for scientific approaches tied to engineering and technology.

National differences in dissemination and use of open access literature.

Open Access (OA) dissemination has been gaining a lot of momentum over the last decade, thanks to the implementation of several OA policies by funders and institutions, as well as the development of several new platforms that facilitate the publication of OA content at low or no cost. Studies have shown that nearly half of the contemporary scientific literature could be available online for free. However, few studies have compared the use of OA literature across countries. This study aims to provide a global picture of OA adoption by countries, using two indicators: publications in OA and references made to articles in OA. We find that, on average, low-income countries are publishing and citing OA at the highest rate, while upper middle-income countries and higher-income countries publish and cite OA articles at below world-average rates. These results highlight national differences in OA uptake and suggest that more OA initiatives at the institutional, national, and international levels are needed to support wider adoption of open scholarship.

The latent structure of global scientific development.

Science is essential to innovation and economic prosperity. Although studies have shown that national scientific development is affected by geographic, historic and economic factors, it remains unclear whether there are universal structures and trajectories of national scientific development that can inform forecasting and policy-making. Here, by examining the scientific 'exports'-publications that are indexed in international databases-of countries, we reveal a three-cluster structure in the relatedness network of disciplines that underpin national scientific development and the organization of global science. Tracing the evolution of national research portfolios reveals that while nations are proceeding to more diverse research profiles individually, scientific production is increasingly specialized in global science over the past decades. By uncovering the underlying structure of scientific development and connecting it with economic development, our results may offer a new perspective on the evolution of global science.

Who tweets climate change papers? investigating publics of research through users' descriptions.

As social issues like climate change become increasingly salient, digital traces left by scholarly documents can be used to assess their reach outside of academia. Our research examine who shared climate change research papers on Twitter by looking at the expressions used in profile descriptions. We categorized users in eight categories (academia, communication, political, professional, personal, organization, bots and publishers) associated to specific expressions. Results indicate how diverse publics may be represented in the communication of scholarly documents on Twitter. Supplementing our word detection analysis with qualitative assessments of the results, we highlight how the presence of unique or multiple categorizations in textual Twitter descriptions provides evidence of the publics of research in specific contexts. Our results show a more substantial communication by academics and organizations for papers published in 2016, whereas the general public comparatively participated more in 2015. Overall, there is significant participation of publics outside of academia in the communication of climate change research articles on Twitter, although the extent to which these publics participate varies between individual papers. This means that papers circulate in specific communities which need to be assessed to understand the reach of research on social media. Furthermore, the flexibility of our method provide means for research assessment that consider the contextuality and plurality of publics involved on Twitter.

China's Research Evaluation Reform: What are the Consequences for Global Science?

In the 1990s, China created a research evaluation system based on publications indexed in the Science Citation Index (SCI) and on the Journal Impact Factor. Such system helped the country become the largest contributor to the scientific literature and increased the position of Chinese universities in international rankings. Although the system had been criticized by many because of its adverse effects, the policy reform for research evaluation crawled until the breakout of the COVID-19 pandemic, which accidently accelerates the process of policy reform. This paper highlights the background and principles of this reform, provides evidence of its effects, and discusses the implications for global science.

Cumulative advantage and citation performance of repeat authors in scholarly journals.

Cumulative advantage-commonly known as the Matthew Effect-influences academic output and careers. Given the challenge and uncertainty of gauging the quality of academic research, gatekeepers often possess incentives to prefer the work of established academics. Such preferences breach scientific norms of universalism and can stifle innovation. This article analyzes repeat authors within academic journals as a possible exemplar of the Matthew Effect. Using publication data for 347 economics journals from 1980-2017, as well as from three major generalist science journals, we analyze how articles written by repeat authors fare vis-à-vis less-experienced authors. Results show that articles written by repeat authors steadily decline in citation impact with each additional repeat authorship. Despite these declines, repeat authors also tend to garner more citations than debut authors. These contrasting results suggest both benefits and drawbacks associated with repeat authorships. Journals appear to respond to feedback from previous publications, as more-cited authors in a journal are more likely to be selected for repeat authorships. Institutional characteristics of journals also affect the likelihood of repeat authorship, as well as citation outcomes. Repeat authorships-particularly in leading academic journals-reflect innovative incentives and professional reward structures, while also influencing the intellectual content of science.

Avoiding bias when inferring race using name-based approaches.

Racial disparity in academia is a widely acknowledged problem. The quantitative understanding of racial-based systemic inequalities is an important step towards a more equitable research system. However, because of the lack of robust information on authors' race, few large-scale analyses have been performed on this topic. Algorithmic approaches offer one solution, using known information about authors, such as their names, to infer their perceived race. As with any other algorithm, the process of racial inference can generate biases if it is not carefully considered. The goal of this article is to assess the extent to which algorithmic bias is introduced using different approaches for name-based racial inference. We use information from the U.S. Census and mortgage applications to infer the race of U.S. affiliated authors in the Web of Science. We estimate the effects of using given and family names, thresholds or continuous distributions, and imputation. Our results demonstrate that the validity of name-based inference varies by race/ethnicity and that threshold approaches underestimate Black authors and overestimate White authors. We conclude with recommendations to avoid potential biases. This article lays the foundation for more systematic and less-biased investigations into racial disparities in science.

The effect of data sources on the measurement of open access: A comparison of Dimensions and the Web of Science.

With the growing number of open access (OA) mandates, the accurate measurement of OA publishing is an important policy issue. Existing studies have provided estimates of the prevalence of OA publications ranging from 27.9% to 53.7%, depending on the data source and period of investigation. This paper aims at providing a comparison of the proportion of OA publishing as represented in two major bibliometric databases, Web of Science (WoS) and Dimensions, and assesses how the choice of database affects the measurement of OA across different countries. Results show that a higher proportion of publications indexed in Dimensions are OA than those indexed by WoS, and that this is particularly true for publications originating from outside North America and Europe. The paper concludes with a discussion of the cause and consequences of these differences, motivating the use of more inclusive databases when examining OA, especially for publications originating beyond North America and Europe.

Paracetamol (acetaminophen) use in infants and children was never shown to be safe for neurodevelopment: a systematic review with citation tracking.

Although widely believed by pediatricians and parents to be safe for use in infants and children when used as directed, increasing evidence indicates that early life exposure to paracetamol (acetaminophen) may cause long-term neurodevelopmental problems. Furthermore, recent studies in animal models demonstrate that cognitive development is exquisitely sensitive to paracetamol exposure during early development. In this study, evidence for the claim that paracetamol is safe was evaluated using a systematic literature search. Publications on PubMed between 1974 and 2017 that contained the keywords "infant" and either "paracetamol" or "acetaminophen" were considered. Of those initial 3096 papers, 218 were identified that made claims that paracetamol was safe for use with infants or children. From these 218, a total of 103 papers were identified as sources of authority for the safety claim.   Conclusion: A total of 52 papers contained actual experiments designed to test safety, and had a median follow-up time of 48 h. None monitored neurodevelopment. Furthermore, no trial considered total exposure to drug since birth, eliminating the possibility that the effects of drug exposure on long-term neurodevelopment could be accurately assessed. On the other hand, abundant and sufficient evidence was found to conclude that paracetamol does not induce acute liver damage in babies or children when used as directed. What is Known: • Paracetamol (acetaminophen) is widely thought by pediatricians and parents to be safe when used as directed in the pediatric population, and is the most widely used drug in that population, with more than 90% of children exposed to the drug in some reports. • Paracetamol is known to cause liver damage in adults under conditions of oxidative stress or when used in excess, but increasing evidence from studies in humans and in laboratory animals indicates that the target organ for paracetamol toxicity during early development is the brain, not the liver. What is New: • This study finds hundreds of published reports in the medical literature asserting that paracetamol is safe when used as directed, providing a foundation for the widespread belief that the drug is safe. • This study shows that paracetamol was proven to be safe by approximately 50 short-term studies demonstrating the drug's safety for the pediatric liver, but the drug was never shown to be safe for neurodevelopment. Paracetamol is widely believed to be safe for infants and children when used as directed, despite mounting evidence in humans and in laboratory animals indicating that the drug is not safe for neurodevelopment. An exhaustive search of published work cited for safe use of paracetamol in the pediatric population revealed 52 experimental studies pointing toward safety, but the median follow-up time was only 48 h, and neurodevelopment was never assessed.

Intersectional inequalities in science.

The US scientific workforce is primarily composed of White men. Studies have demonstrated the systemic barriers preventing women and other minoritized populations from gaining entry to science; few, however, have taken an intersectional perspective and examined the consequences of these inequalities on scientific knowledge. We provide a large-scale bibliometric analysis of the relationship between intersectional identities, topics, and scientific impact. We find homophily between identities and topic, suggesting a relationship between diversity in the scientific workforce and expansion of the knowledge base. However, topic selection comes at a cost to minoritized individuals for whom we observe both between- and within-topic citation disadvantages. To enhance the robustness of science, research organizations should provide adequate resources to historically underfunded research areas while simultaneously providing access for minoritized individuals into high-prestige networks and topics.

Investigating disagreement in the scientific literature.

Disagreement is essential to scientific progress but the extent of disagreement in science, its evolution over time, and the fields in which it happens remain poorly understood. Here we report the development of an approach based on cue phrases that can identify instances of disagreement in scientific articles. These instances are sentences in an article that cite other articles. Applying this approach to a collection of more than four million English-language articles published between 2000 and 2015 period, we determine the level of disagreement in five broad fields within the scientific literature (biomedical and health sciences; life and earth sciences; mathematics and computer science; physical sciences and engineering; and social sciences and humanities) and 817 meso-level fields. Overall, the level of disagreement is highest in the social sciences and humanities, and lowest in mathematics and computer science. However, there is considerable heterogeneity across the meso-level fields, revealing the importance of local disciplinary cultures and the epistemic characteristics of disagreement. Analysis at the level of individual articles reveals notable episodes of disagreement in science, and illustrates how methodological artifacts can confound analyses of scientific texts.

Mapping the biomedical sciences using Medical Subject Headings: a comparison between MeSH co-assignments and MeSH citation pairs.

OBJECTIVE: This study compares two maps of biomedical sciences using Medical Subject Headings (MeSH) term co-assignments versus MeSH terms of citing/cited articles and reveals similarities and differences between the two approaches. METHODS: MeSH terms assigned to 397,475 journal articles published in 2015, as well as their 4,632,992 cited references, were retrieved from Web of Science and MEDLINE databases, respectively, which formed over 7 million MeSH co-assignments and nearly 18 million direct citation pairs. We generated six network visualizations of biomedical science at three levels using Gephi software based on these MeSH co-assignments and citation pairs. RESULTS: The MeSH co-assignment map contained more nodes and edges, as MeSH co-assignments cover all medical topics discussed in articles. By contrast, the MeSH citation map contained fewer but larger nodes and wider edges, as citation links indicate connections to two similar medical topics. CONCLUSION: These two types of maps emphasize different aspects of biomedical sciences, with MeSH co-assignment maps focusing on the relationship between topics in different categories and MeSH direct citation maps providing insights into relationships between topics in the same or similar category.

The gendered nature of authorship.

Authorship is the primary form of symbolic capital in science. Despite this, authorship is rife with injustice and malpractice, with women expressing concerns regarding the fair attribution of credit. Based on an international survey, we examine gendered practices in authorship communication, disagreement, and fairness. Our results demonstrate that women were more likely to experience authorship disagreements and experience them more often. Their contributions to research papers were more often devalued by both men and women. Women were more likely to discuss authorship with coauthors at the beginning of the project, whereas men were more likely to determine authorship unilaterally at the end. Women perceived that they received less credit than deserved, while men reported the opposite. This devaluation of women's work in science creates cumulative disadvantages in scientific careers. Open discussion regarding power dynamics related to gender is necessary to develop more equitable distribution of credit for scientific labor.

Do authors of research funded by the Canadian Institutes of Health Research comply with its open access mandate?: A meta-epidemiologic study.

BACKGROUND: Since 2008, the Canadian Institutes of Health Research (CIHR) has mandated that studies it funds either in whole or in part are required to publish their results as open access (OA) within 12 months of publication using either online repositories and/or OA journals. Yet, there is evidence that authors are poorly compliant with this mandate. Specifically, there has been an apparent decrease in OA publication after 2015, which coincides with a change in the OA policy during the same year. One particular policy change that may have contributed to this decline was lifting the requirement that authors deposit their article in an OA repository immediately upon publication. We investigated the proportion of OA compliance of CIHR-funded studies in the period before and after the policy change of 2015 with manual confirmation of both CIHR funding and OA status. METHODS AND FINDINGS: We identified CIHR-funded studies published between the years 2014 to 2017 using a comprehensive search in the Web of Science (WoS). We took a stratified random sample from all four years (i.e. 2014 to 2017), with 250 studies from each year. Two authors independently reviewed the final full-text publications retrieved from the journal web page to determine to confirm CIHR funding, as indicated in the acknowledgements or elsewhere in the paper. For each study, we also collected bibliometric data that included citation count and Altmetric attention score Statistical analyses were conducted using two-tailed Fisher's exact test with relative risk (RR). Among the 851 receiving CIHR funding published from 2014 to 2017, the percentage of CIHR-funded studies published as OA significantly decreased from 79.6% in 2014 to 70.3% in 2017 (RR = 0.88, 95% CI: 0.79-0.99, P = 0.028). When considering all four years, there was no significant difference in the percentage of CIHR-funded studies published as OA in both 2014 and 2015 compared to both 2016 and 2017 (RR = 0.97, 95% CI: 0.90-1.05, P = 0.493). Additionally, OA publications had significantly higher citation count (both in year of publication and in total) and higher attention scores (P<0.05). CONCLUSIONS: Overall, we found that there was a significant decrease in the proportion of CIHR funded studies published as OA from 2014 compared to 2017, though this difference did not persist when comparing both 2014-2015 to 2016-2017. The primary limitation was the reliance of self-reported data from authors on CIHR funding status. We posit that this decrease may be attributable to CIHR's OA policy change in 2015. Further exploration is warranted to both validate these studies using a larger dataset and, if valid, investigate the effects of potential interventions to improve the OA compliance, such as use of a CIHR publication database, and reinstatement of a policy for authors to immediately submit their findings to OA repositories upon publication.

Task specialization across research careers.

Research careers are typically envisioned as a single path in which a scientist starts as a member of a team working under the guidance of one or more experienced scientists and, if they are successful, ends with the individual leading their own research group and training future generations of scientists. Here we study the author contribution statements of published research papers in order to explore possible biases and disparities in career trajectories in science. We used Bayesian networks to train a prediction model based on a dataset of 70,694 publications from PLoS journals, which included 347,136 distinct authors and their associated contribution statements. This model was used to predict the contributions of 222,925 authors in 6,236,239 publications, and to apply a robust archetypal analysis to profile scientists across four career stages: junior, early-career, mid-career and late-career. All three of the archetypes we found - leader, specialized, and supporting - were encountered for early-career and mid-career researchers. Junior researchers displayed only two archetypes (specialized, and supporting), as did late-career researchers (leader and supporting). Scientists assigned to the leader and specialized archetypes tended to have longer careers than those assigned to the supporting archetype. We also observed consistent gender bias at all stages: the majority of male scientists belonged to the leader archetype, while the larger proportion of women belonged to the specialized archetype, especially for early-career and mid-career researchers.