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AbstractUsing data for 387 Nobel Prize winners in physics, chemistry, or physiology/medicine from 1901 to 2000, this study focuses on the relation between the timing of prestigious awards and human longevity. In particular, it uses a linear regression model to examine how a winner’s longevity is affected by (1) the age at which the prestigious award is won, (2) the total number of prestigious awards collected, and (3) the delay between the Nobel Prize work and recognition. To alleviate estimation issues stemming from survival selection, we conduct our analyses using subsamples of surviving individuals and controlling for age-specific life expectancy. Our results suggest that receiving the Nobel Prize at a younger age is related to a longer expected lifespan (e.g., obtaining the Nobel Prize 10 years earlier is associated with an additional 1 year of lifespan compared to the average population life expectancy). The results also point to a strong negative association between the age of receiving major scientific awards and relative life expectancy, which further indicates the benefit of early recognition. Yet, we did not find evidence suggesting that the number of prestigious awards received at an earlier age correlated with longevity. Nor are we able to observe that the duration between Nobel Prize work and the award reception (waiting time for the Nobel Prize recognition) is associated with changes in longevity.

AbstractThe sustainable development goals (SDGs) are a blueprint for achieving a better and more sustainable future for all by defining priorities and aspirations for 2030. This paper attempts to expand on the United Nations SDGs definition by leveraging the interrelationship between science and technology. We utilize SDG classification of scientific publications to compile a machine learning (ML) model to classify the SDG relevancy in patent documents, used as a proxy of technology development. The ML model was used to classify a sample of patent families registered in the European Patent Office (EPO). The analysis revealed the extent to which SDGs were addressed in patents. We also performed a case study to identify the offered extension of ML model detection regarding the SDG orientation of patents. In response to global goals and sustainable development initiatives, the findings can advance the identification challenges of science and technology artefacts. Furthermore, we offer input towards the alignment of R&D efforts and patenting strategies as well as measurement and management of their contribution to the realization of SDGs.

AbstractIn this article, we revisit the analysis of Laband and Tollison (Appl Econ 38(14):1649–1653, 2006) who documented that articles with two authors in alphabetical order are cited much more often than non-alphabetized papers with two authors in the American Economic Review and the American Journal of Agricultural Economics. Using more than 120,000 multi-authored articles from the Web of Science economics subject category, we demonstrate first that the alphabetization rate in economics has declined over the last decade. Second, we find no statistically significant relationship between alphabetized co-authorship and citations in economics using six different regression settings (the coefficients are very small). This result holds mostly true when accounting both for journal heterogeneity and intentionally or incidentally alphabetical ordering of authors. We find some evidence that alphabetization in case of two authos increases citations rates for very high-impact journals. Third, we show that the likelihood of non-alphabetized co-authorship increases the more authors an article has.

AbstractThis paper presents TeknoAssistant, a domain-specific tech mining method for building a problem–solution conceptual network aimed at helping technicians from a particular field to find alternative tools and pathways to implement when confronted with a problem. We evaluate our approach using Natural Language Processing field, and propose a 2-g text mining process adapted for analyzing scientific publications. We rely on a combination of custom indicators with Stanford OpenIE SAO extractor to build a Bernoulli Naïve Bayes classifier which is trained by using domain-specific vocabulary provided by the TeknoAssistant user. The 2-g contained in the abstracts of a scientific publication dataset are classified in either “problem”, “solution” or “none” categories, and a problem–solution network is built, based on the co-occurrence of problems and solutions in the abstracts. We propose a combination of clustering technique, visualization and Social Network Analysis indicators for guiding a hypothetical user in a domain-specific problem solving process.

ABSTRACTIntroductionCOVID-19-related (vs. non-related) articles appear to be more expeditiously processed and published in peer-reviewed journals. We aimed to evaluate: (i) whether COVID-19-related preprints were favored for publication, (ii) preprinting trends and public discussion of the preprints, and (iii) the relationship between the publication topic (COVID-19-related or not) and quality issues.MethodsManuscripts deposited at bioRxiv and medRxiv between January 1 and September 27 were assessed for the probability of publishing in peer-reviewed journals, and those published were evaluated for submission-to-acceptance time. The extent of public discussion was assessed based on Altmetric and Disqus data. The Retraction Watch Database and PubMed were used to explore the retraction of COVID-19 and non-COVID-19 articles and preprints.ResultsWith adjustment for the preprinting server and number of deposited versions, COVID-19-related preprints were more likely to be published within 120 days since the deposition of the first version (OR=2.04, 95%CI 1.87-2.23) as well as over the entire observed period (OR=1.42, 95%CI 1.33-1.52). Submission-to-acceptance was by 38.67 days (95%CI 34.96-42.39) shorter for COVID-19 articles. Public discussion of preprints was modest and COVID-19 articles were overrepresented in the pool of retracted articles in 2020.ConclusionCurrent data suggest a preference for publication of COVID-19-related preprints over the observed period.

Given how hard it is to recruit good reviewers who are aligned with authors in their functions, journal editors could consider the use of better incentives, such as paying reviewers for their time. In order to facilitate a speedy turn-around when a rapid decision is required, the peer-reviewed journal can also offer a review model in which selected peer reviewers are compensated to deliver high-quality and timely peer-review reports. In this paper, we consider a peer-reviewed journal in which the manuscript’s evaluation consists of a necessary peer review component and an optional speedy peer review component. We model and study that journal under two different scenarios to be compared: a paid peer-reviewing scenario that is considered as the benchmark; and a hybrid peer-review scenario where the manuscript’s author can decide whether to pay or not. In the benchmark scenario of paid peer-reviewing, the scholarly journal expects all authors to pay for the peer review and charges separately for the necessary and the optional speedy peer-review components. Alternatively, in a hybrid peer-review scenario, the peer-reviewed journal gives the option to the authors to not pay for the necessary peer review if they are not able to pay. This will determine an altruistic amplification of pay utility. However, the no-pay authors cannot avail of the optional speedy peer review, which determines a restriction-induced no-pay utility reduction. In this paper, we find that under the hybrid setting of compensated peer review where the author can decide whether to pay or not, the optimal price and review quality of the optional speedy peer review are always higher than under the benchmark scenario of paid peer-reviewing, due to the altruistic amplification of pay utility. Our results show that when the advantage of adopting the hybrid mode of compensated peer review is higher due to the higher difference between the altruistic author utility amplification and the restriction-induced no-pay utility reduction, the journal can increase its profitability by increasing the price for the necessary peer review above that in the benchmark scenario of paid peer review. A key insight from our results is the journal’s capability to increase the number of paying authors by giving the option to the authors to not pay for the necessary peer review if they are not able to pay. Funding for open access charge: Universidad de Granada/CBUA. This research was sponsored by the Spanish Board for Science, Technology, and Innovation under grant PID2021-122371NB-I00, and cofinanced with European FEDER funds. Spanish Board for Science, Technology, and Innovation PID2021-122371NB-I00 Universidad de Granada/CBUA European Commission

This study aims to analyze 343 retraction notices indexed in the Scopus database, published in 2001-2019, related to scientific articles (co-)written by at least one author affiliated with an Iranian institution. In order to determine reasons for retractions, we merged this database with the database from Retraction Watch. The data were analyzed using Excel 2016 and IBM-SPSS version 24.0, and visualized using VOSviewer software. Most of the retractions were due to fake peer review (95 retractions) and plagiarism (90). The average time between a publication and its retraction was 591 days. The maximum time-lag (about 3,000 days) occurred for papers retracted due to duplicate publications; the minimum time-lag (fewer than 100 days) was for papers retracted due to ''unspecified cause'' (most of these were conference papers). As many as 48 (14%) of the retracted papers were published in two medical journals: Tumor Biology (25 papers) and Diagnostic Pathology (23 papers). From the institutional point of view, Islamic Azad University was the inglorious leader, contributing to over one-half (53.1%) of retracted papers. Among the 343 retraction notices, 64 papers pertained to international collaborations with researchers from mainly Asian and European countries; Malaysia having the most retractions (22 papers). Since most retractions were due to fake peer review and plagiarism, the peer review system appears to be a weak point of the submission/publication process; if improved, the number of retractions would likely drop because of increased editorial control. Comment: 29 pages, 7 figures, 5 tables, 41 references

AbstractThe motivation for our research is the view, widespread among Polish scientists, that under the Communist Party’s rule it was always necessary to refer to Marx, Engels, Lenin or Stalin (we call them ‘classics’), especially in the highly-politicised fields like humanities and social sciences, in order for the work to pass the censorship procedures and be published. Therefore, in this paper, we aim to determine whether the 'classics' were commonly cited in a formally socialist country under the rule of the Communist Party (Polish Workers' Party/Polish United Workers’ Party). To address the main research question, we use the Citation Index of the History of Polish Media that covers all publications, whether scholarly articles or book publications, on the history of Polish media; in total, 6880 publications and 59,827 citations from the 1945‒2009 period. We found that citations of the works of the ‘classics’ (N = 296) constitute 0.49% of all citations in the database used and that the practice of citing the 'classics' was extremely rare (just 64 occurrences in the analysed sample). Our research also contributes to the development of reflection in historical bibliometrics and argues that bibliographical databases need to cover various types of publications, especially scholarly book publications, written in different languages (not only in English).