Frontiers in research metrics and analytics最新文献

In the book Laboratory Life Latour and Woolgar present an account of how scientific "facts" are formed through a process of microsocial interactions among individuals and "inscription devices" in the lab initially described as social construction. The process moves through a series of steps during which the details and nature of the object become more and more certain until all qualifications are dropped, and the "fact" emerges as secure scientific knowledge. An alternative to this account is described based on a Bayesian probabilistic framework which arrives at the same end point. The motive force for the constructivist approach appears to involve social processes of convincing colleagues while the Bayesian approach relies on the consistency of theory and evidence as judged by the participants. The role of social processes is discussed in Bayesian terms, the acquisition and asymmetry of information, and its analogy to puzzle solving. Some parallels between the Bayesian and constructivist accounts are noted especially in relation to information theory.

Background: INPLASY^® is an international platform for registering systematic reviews and meta-analysis protocols that was launched in March 2020. INPLASY^® provides an online database in which the protocols are maintained as permanent public records and can be accessed on its website (www.inplasy.com).

Methods: We described the database features and registered information of all records published since the launch of the registry on March 31, 2023. Additionally, we analyzed the website statistics dataset to explore user experience and promote data transparency.

Results: Four thousand six hundred fifty-eight records were registered in INPLASY^®, and more than 94% of the protocols were published within 24 h. Most of the submissions were from China, followed by Portugal, Taiwan, Malaysia, and Brazil. The INPLASY^® website received 386,395 page views from 64,568 visitors during the first three years. The accesses were obtained from 170 countries. Most of the accesses were from China, followed by the US, the UK, and Portugal. The review status "completed and published" was observed in 898 protocols, and these studies were published in 372 different scientific peer-reviewed journals. The features of INPLASY^® include the following: (i) INPLASY^® identifier, a unique protocol number; (ii) the digital object identifier (DOI) number, the URL of the protocol linked to a specific DOI; (iii) ORCID update, INPLASY^® automatically updates authors' ORCID page, including their protocol; and (iv) search tools, the protocols are freely accessible on www.inplasy.com.

Conclusions: INPLASY^® has several practical and useful features that should be considered when planning the registration of a systematic review protocol. Furthermore, the sharp increase in the number of protocols registered in INPLASY^® in the first three years and the database statistics demonstrate that INPLASY^® has become an important source of systematic review protocols. Therefore, authors should access INPLASY^® before planning a future review study to avoid unintended duplication of efforts and to obtain timely registration.

Introduction: Altmetrics have been demonstrated as a promising tool for analyzing scientific communication on social media. Nevertheless, its application for research evaluation remains underdeveloped, despite the advancement of research in the study of diverse scientific interactions.

Methods: This paper develops a method for applying altmetrics in the evaluation of researchers, focusing on a case study of the Environment/Ecology ESI field publications by researchers at the University of Granada. We considered Twitter as a mirror of social attention, news outlets as media, and Wikipedia as educational, exploring mentions from these three sources and the associated actors in their respective media, contextualizing them using various metrics.

Results: Our analysis evaluated different dimensions such as the type of audience, local attention, engagement generated around the mention, and the profile of the actor. Our methodology effectively provided dashboards that gave a comprehensive view of the different instances of social attention at the author level.

Discussion: The use of altmetrics for research evaluation presents significant potential, as shown by our case study. While this is a novel method, our results suggest that altmetrics could provide valuable insights into the social attention that researchers garner. This can be an important tool for research evaluation, expanding our understanding beyond traditional metrics.

While the COVID-19 pandemic morphs into less malignant forms, the virus has spawned a series of poorly understood, post-infection symptoms with staggering ramifications, i. e., long COVID (LC). This bibliometric study profiles the rapidly growing LC research domain [5,243 articles from PubMed and Web of Science (WoS)] to make its knowledge content more accessible. The article addresses What? Where? Who? and When? questions. A 13-topic Concept Grid presents bottom-up topic clusters. We break out those topics with other data fields, including disciplinary concentrations, topical details, and information on research "players" (countries, institutions, and authors) engaging in those topics. We provide access to results via a Dashboard website. We find a strongly growing, multidisciplinary LC research domain. That domain appears tightly connected based on shared research knowledge. However, we also observe notable concentrations of research activity in different disciplines. Data trends over 3 years of LC research suggest heightened attention to psychological and neurodegenerative symptoms, fatigue, and pulmonary involvement.

Introduction: Do externalities work and matter differently in a world of scarcity vs. a world of abundance? In this article, we critically examine the economic phenomena of externalities. The concept of externality, an important idea in economics and law, is useful in exploring the complex and dynamic relationships between resource supply and human flourishing within various sociotechnical systems.

Methods: First, we define the basic concept and explain why it is fundamental to economic analysis of complex social environments Second, we briefly survey the intellectual history of externalities with the goal of tying together a few different strands of economic theory and providing a roadmap for a general theory of externalities. This discussion highlights a latent conflict between those who pursue and those who resist perfectibility (optimization) of social systems by internalizing externalities. Third, we compare externalities in worlds of scarcity and abundance.

Results: This article develops the theoretical framework, including a brief intellectual history and notes toward the development of a general theory of externalities. As a conceptual tool, externalities enable one to identify and examine social interdependencies and to map their causes and consequences. Externalities provide evidence of social demand for governance institutions. This descriptive utility can and should inform normative analysis, the design of governance institutions, and comparative institutional analysis. We also raise a series of (mostly empirical) questions that should frame comparative institutional analysis and evaluation of different externalities in the digital networked world.

Discussion: We focus on the scarcity and abundance of knowledge resources and the (technological) means for participating in the production, dissemination, and modification of such resources. In the real, necessarily imperfect world where abundance and scarcity vary across resources, people, and contexts, externalities persist, indicate social demand for governance, and inform comparative analysis and design of governance institutions.

Jel classification: D62, B52, D02.

Introduction: Math achievement for economically disadvantaged students remains low, despite positive developments in research, pedagogy, and funding. In the current paper, we focused on the research-to-practice divide as possible culprit. Our argument is that urban-poverty schools lack the stability that is necessary to deploy the trusted methodology of hypothesis-testing. Thus, a type of efficacy methodology is needed that could accommodate instability.

Method: We explore the details of such a methodology, building on already existing emancipatory methodologies. Central to the proposed solution-based research (SBR) is a commitment to the learning of participating students. This commitment is supplemented with a strength-and-weaknesses analysis to curtail researcher bias. And it is supplemented with an analysis of idiosyncratic factors to determine generalizability. As proof of concept, we tried out SBR to test the efficacy of an afterschool math program.

Results: We found the SBR produced insights about learning opportunities and barrier that would not be known otherwise. At the same time, we found that hypothesis-testing remains superior in establishing generalizability.

Discussion: Our findings call for further work on how to establish generalizability in inherently unstable settings.

Scientific integrity necessitates applying scientific methods properly, collecting and analyzing data appropriately, protecting human subjects rightly, performing studies rigorously, and communicating findings transparently. But who is responsible for upholding research integrity, mitigating misinformation, and increasing trust in science beyond individual researchers? We posit that supporting the scientific reputation requires a coordinated approach across all stakeholders: funding agencies, publishers, scholarly societies, research institutions, and journalists and media, and policy-makers.

Patent protection typically lasts about 20 years from the filing date and is in exchange for sufficiently disclosing the invention. The disclosure aims to enrich technical knowledge globally, promote creativity and technological innovation and contribute to sustainable socio-economic development. After this protection period, the patent expires, and in principle, any person may begin practicing the specific subject matter previously protected by the patent. Since the invention originally met all the patentability requirements, it was disclosed sufficiently to stimulate further innovation by others through a thorough understanding of existing developments in the patent literature. Thus, in addition to scholarly research articles, this makes patents potentially valuable sources of technical information in research and academia, unlocking new technology opportunities. We use the exploratory research method to study a potentially genuine and vital research stream that uncovers the overlooked yet valuable scientific and technical information sources that higher education institutions could utilize to complement academic research articles. This work establishes a necessary research agenda that critically challenges researchers to tap into the immediately available and promising technology opportunities presented by patents in the public domain. Using case studies to gain in-depth, multi-faceted explorations about the impact of these patents, we find that technologies contained in expired patents, abandoned patents, and technologies not protected by IPRs, resulting in improved research quality and increased collaboration with industry, if adequately exploited and integrated with other technologies. Moreover, this could lead to increased academic patenting and commercialization with support from the university's Technology Transfer Office.

Introduction: This study examines the performance of active learning-aided systematic reviews using a deep learning-based model compared to traditional machine learning approaches, and explores the potential benefits of model-switching strategies.

Methods: Comprising four parts, the study: 1) analyzes the performance and stability of active learning-aided systematic review; 2) implements a convolutional neural network classifier; 3) compares classifier and feature extractor performance; and 4) investigates the impact of model-switching strategies on review performance.

Results: Lighter models perform well in early simulation stages, while other models show increased performance in later stages. Model-switching strategies generally improve performance compared to using the default classification model alone.

Discussion: The study's findings support the use of model-switching strategies in active learning-based systematic review workflows. It is advised to begin the review with a light model, such as Naïve Bayes or logistic regression, and switch to a heavier classification model based on a heuristic rule when needed.

To help cross-disciplinary science teams navigate through internal and external complexities, this perspective article explores the application of three conceptual frameworks: Theory U, Divergence-Convergence Diamond, and Strategic Doing. These frameworks enable science teams to avoid common pitfalls by operationalizing collaborative leadership as iterative cycles of distributed sense making, decision making and action taking. Implications for team science practices include facilitating the process, prototyping the future and applying dynamic roles and responsibilities.