At 101007/s11192-023-04675-9, supplementary material related to the online version is located.

Previous researches into the use of positive and negative terminology in academic contexts have indicated a inclination for utilizing more positive language in academic prose. However, a significant gap exists in our understanding of how linguistic positivity's traits and processes might differ depending on the particular academic area. Beyond this, the association between positive language in research and its overall impact warrants further consideration. To address the existing issues, this study explored linguistic positivity in academic writing with a cross-disciplinary perspective. A 111-million-word corpus of research article abstracts from Web of Science provided the data for the study's examination of the diachronic shifts in positive/negative language within eight academic disciplines. The study also investigated the relationship between linguistic positivity and the number of citations. Across the academic disciplines examined, the results highlighted a prevalent increase in linguistic positivity. Furthermore, hard disciplines demonstrated a more pronounced and rapidly escalating linguistic positivity than soft disciplines. selleck inhibitor In conclusion, a marked positive connection emerged between citation frequency and the level of linguistic positivity. A thorough examination of the factors that influence the temporal and disciplinary dynamics of linguistic positivity, and its subsequent implications for the scientific community, was conducted.

The impact of journalistic articles published in highly regarded scientific journals can be profound, notably in dynamic and evolving research fields. The meta-research analysis explored the publication records, influence, and declared conflicts of interest of non-research authors who had published more than 200 Scopus-indexed articles in highly regarded journals, including Nature, Science, PNAS, Cell, BMJ, Lancet, JAMA, or the New England Journal of Medicine. A substantial 154 prolific authors were recognized, 148 of whom had penned 67825 publications in their primary journal, not as researchers. These authors frequently contribute to Nature, Science, and the BMJ. The journalistic publications analyzed by Scopus include 35% classified as full articles and a separate 11% categorized as concise surveys. A significant 264 papers garnered in excess of 100 citations each. Among the 41 most cited research papers published between 2020 and 2022, a noteworthy 40 papers concentrated on pertinent COVID-19 topics. Twenty-five highly prolific authors, each exceeding 700 publications in a particular journal, saw a substantial proportion achieving significant citations (median exceeding 2273). Consistently, they primarily concentrated their publication output in their designated journal, contributing little to other Scopus-indexed literature. Their impactful works encompassed diverse timely topics throughout their careers. From the twenty-five participants, three had earned a doctorate in any subject area and seven held a master's in journalism. Only the BMJ, on its website, provided disclosures of potential conflicts of interest for prolific science writers, but even then, only two of the twenty-five highly prolific authors revealed specific potential conflicts. The necessity for a more thorough examination of the impact of non-researchers' influence on scientific discourse is underscored, as is the importance of emphasizing disclosures regarding potential conflicts of interest.

The internet age, marked by a dramatic rise in research volume, has underscored the crucial role of retracting published papers from scientific journals in ensuring scientific integrity. Since the onset of the COVID-19 pandemic, there has been a marked increase in public and professional engagement with scientific literature, with the intent of enhancing personal understanding of the virus. The Retraction Watch Database COVID-19 blog, accessed in June and November 2022, underwent a rigorous examination to guarantee the articles' conformity with inclusion criteria. Article-level data including citations and SJR/CiteScore were extracted from the Google Scholar and Scopus databases. On average, a journal publishing an article had an SJR of 1531 and a CiteScore of 73. The average number of citations for the retracted articles stood at 448, which was substantially higher than the average CiteScore, a statistically significant difference (p=0.001). COVID-19 articles retracted between June and November received a combined 728 new citations; the presence of 'withdrawn' or 'retracted' in the title did not impact the citation rate. Based on the assessment, 32% of articles fell short of meeting the COPE guidelines regarding retraction statements. It is our hypothesis that COVID-19 publications, which have been retracted, were more inclined to make bold claims that attracted a significantly higher level of scientific attention. Beyond that, a substantial number of journals were not forthcoming with detailed explanations for retractions. The use of retractions to advance scientific discourse is conceivable, yet at present we are only privy to the observable outcomes, missing the fundamental causal explanations, or the 'why'.

Open science (OS) is inextricably linked to data sharing, and a rising trend shows open data (OD) policies being mandated by more and more institutions and journals. Although OD is recommended to strengthen academic spheres and stimulate scientific progress, the specifics of its implementation remain poorly articulated. This research delves into the intricate effects of OD policies on the citation patterns observable in articles published within Chinese economics journals.
The pioneering (CIE) journal, the sole Chinese social science publication, has implemented a mandatory open data policy, thereby requiring that every published article divulge the original data and processing codes. Employing article-level data and the difference-in-differences (DID) methodology, we analyze the citation performance of articles published in CIE versus 36 comparable journals. A notable outcome of the OD policy was a prompt rise in citation numbers, with articles, on average, receiving 0.25, 1.19, 0.86, and 0.44 additional citations in their initial four years post-publication. The study's results further substantiated a considerable and persistent decrease in the citation benefits of the OD policy, turning negative five years after the publication. In summary, this evolving citation pattern underscores an OD policy's dual nature; it can promptly elevate citation counts yet concurrently expedite the decline in relevance of articles.
Within the online version's context, supplementary materials are located at the URL 101007/s11192-023-04684-8.
101007/s11192-023-04684-8 houses the supplementary material for the online version.

Despite the strides made in overcoming gender inequality in Australian scientific endeavors, the matter still requires significant attention. In order to gain a more thorough understanding of gender imbalances in Australian science, all gendered Australian first-authored articles published from 2010 to 2020, which were listed in the Dimensions database, were analyzed critically. Article classification used the Field of Research (FoR), whereas the Field Citation Ratio (FCR) facilitated citation comparisons. A rising trend of female first authorships was observed in scholarly publications across all disciplines, except for the field of information and computing sciences, over the years. The number of single-authored articles written by women also showed an improvement during the study period. selleck inhibitor The Field Citation Ratio analysis suggests a citation advantage held by female researchers in several disciplines, encompassing mathematical sciences, chemical sciences, technology, built environment and design, studies of human society, law and legal studies, and studies in creative arts and writing. In terms of average FCR, female first-authored articles outperformed their male counterparts, a trend that continued across several disciplines including mathematical sciences, where male authors produced more articles.

Funding institutions frequently request text-based research proposals to determine the suitability of potential recipients. Institutions can gain a better understanding of the research output available within their area of expertise by examining the information presented in these documents. We present an end-to-end semi-supervised clustering method for documents, which partially automates the assignment of research proposals to thematic interest areas. selleck inhibitor Comprising three stages, the methodology involves: (1) the manual annotation of a document sample, (2) semi-supervised clustering of these documents, and (3) an evaluation of the cluster results using quantitative metrics and qualitative assessments (coherence, relevance, and distinctiveness) by experts. The methodology's thorough description, along with its demonstration using real-world data, facilitates replication. This demonstration sought to arrange proposals pertaining to technological advances in military medicine, submitted to the US Army Telemedicine and Advanced Technology Research Center (TATRC), into specific categories. A comparative evaluation of methodological attributes was undertaken, encompassing unsupervised and semi-supervised clustering techniques, diverse document vectorization approaches, and various cluster outcome selection strategies. Pretrained Bidirectional Encoder Representations from Transformers (BERT) embeddings exhibited greater efficacy for the assigned task than older text embedding methods, as implied by the gathered outcomes. A comparative analysis of expert ratings across algorithms reveals that semi-supervised clustering yielded coherence ratings approximately 25% higher than standard unsupervised clustering, while exhibiting minimal variations in cluster distinctiveness. It was ultimately determined that a cluster result selection approach that adequately considered both internal and external validity resulted in the best outcomes. For institutional use, this methodological framework, upon further refinement, proves promising as a useful analytical tool for unlocking hidden knowledge from untapped archives and similar administrative document collections.