The supplementary material, integral to the online version, is available through the link 101007/s11192-023-04675-9.

Past studies concerning the employment of positive and negative linguistic components in academic writing have highlighted a tendency for the increased application of positive language in academic prose. Although this is the case, the variability of linguistic positivity's attributes and procedures across academic specializations is not fully understood. Moreover, a significant exploration of the link between positive language use and the research impact is vital. From a cross-disciplinary perspective, the current investigation examined linguistic positivity in academic writing to address these issues. From a 111-million-word corpus of research article abstracts gathered from Web of Science, the study scrutinized the diachronic changes in positive and negative language in eight academic disciplines. The research also investigated the relationship between the degree of linguistic positivity and the frequency of citations. The examined academic disciplines exhibited a common trend of increased linguistic positivity, as the results demonstrate. There was a more significant and quicker rise in linguistic positivity in hard disciplines compared to soft disciplines. NX-5948 Lastly, a prominent positive correlation was identified between the number of citations and the degree of positive language used. A study was conducted to explore the reasons behind the temporal shifts and disciplinary differences in linguistic positivity, and the implications for the scientific community were then discussed.

Highly influential journalistic contributions are frequently published in high-impact scientific journals, especially within the most current and active research areas. A meta-research analysis assessed the publication histories, influence, and conflict-of-interest disclosures of non-research authors who had authored more than 200 Scopus-indexed papers in esteemed journals like Nature, Science, PNAS, Cell, BMJ, Lancet, JAMA, and the New England Journal of Medicine. Prolific authors numbered 154, 148 of whom had published a total of 67825 papers in their main journal in a non-research context. These authors frequently contribute to Nature, Science, and the BMJ. Scopus categorized 35% of the journalistic publications as full articles, while an additional 11% were classified as brief surveys. A considerable 264 papers surpassed the 100-citation mark. During the period from 2020 to 2022, the most cited research papers, comprising 40 out of a total of 41 publications, concentrated on the critical COVID-19 issues. From among 25 highly prolific authors, each with more than 700 publications in a particular journal, many exhibited substantial influence, evidenced by median citation counts exceeding 2273. Practically all of these authors’ research, aside from their central journal, was quite limited or nonexistent in the Scopus-indexed literature. Their contributions, with a broad scope, included numerous timely topics across their respective careers. Of the twenty-five individuals studied, three earned a PhD in any field, and seven achieved a master's degree 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. A rigorous examination of the practice of granting considerable authority to non-researchers in scientific discussions is vital, coupled with an increased emphasis on disclosing potential conflicts of interest.

The internet era's concomitant surge in research output has highlighted the importance of retracting published scientific papers for the preservation of scientific integrity. The COVID-19 pandemic has ignited a surge in public and professional interest in scientific literature, with individuals actively seeking knowledge and understanding of the virus since the outbreak. The Retraction Watch Database COVID-19 blog, consulted in both June and November 2022, underwent a thorough analysis to ensure the articles met established criteria for inclusion. To ascertain citation counts and SJR/CiteScore values, articles were retrieved from Google Scholar and Scopus. The average SJR and CiteScore of journals that published articles similar to one in question were measured at 1531 and 73, respectively. Significantly surpassing the average CiteScore (p=0.001), the retracted articles received an average of 448 citations. Retracted COVID-19 articles accumulated 728 new citations between June and November; the presence of 'withdrawn' or 'retracted' in the article title did not impact the citation rates. Of the articles examined, 32% did not meet the COPE guidelines for retraction statements. Our opinion is that retracted COVID-19 publications may have been more likely to include audacious claims that generated a markedly high degree of attention amongst the scientific community. Moreover, a substantial amount of scholarly journals were not explicit in articulating the rationale behind retracted publications. Retractions, while potentially enriching scientific dialogue, currently only offer a partial picture, revealing the 'what' but obscuring the 'why'.

Open data (OD) policies are increasingly common within institutions and journals, which acknowledge data sharing as integral to open science (OS). Advocating for OD to cultivate academic impact and drive scientific advancement is commendable, though the specifics of this approach lack clarity. The study examines the nuanced ways in which OD policies influence citation patterns, focusing on the case of Chinese economics journals.
Among Chinese social science journals, (CIE) is the first and only one to introduce a mandatory open data policy, obligating all published articles to share the original data and computational procedures. To compare the citation performance of articles published in CIE against 36 peer journals, we adopt an article-level dataset and the difference-in-differences (DID) methodology. The OD policy's immediate effect was a substantial surge in citations; each paper, on average, gained 0.25, 1.19, 0.86, and 0.44 citations in the first four years following publication. Our research also showed a pronounced and sustained deterioration in citation impact from the OD policy, culminating in negative effects by the fifth year post-publication. Overall, the changing citation pattern highlights a double-edged effect of an OD policy; it can sharply increase citation numbers in the short term but simultaneously speed up the obsolescence of research articles.
101007/s11192-023-04684-8 hosts the supplementary content accompanying the online document.
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While progress has been made in reducing gender inequality within Australian science, the issue remains unresolved. A comprehensive investigation was conducted into the manifestations of gender inequality within Australian science, evaluating all gendered Australian first-authored research articles indexed in the Dimensions database during the period from 2010 to 2020. The Field of Research (FoR) was utilized for classifying articles, and the Field Citation Ratio (FCR) was employed for evaluating citations. Female first authorships showed an overall upward pattern in publications across all fields of research, with the singular exception being information and computing sciences. The study period showed an improvement in the ratio of articles authored solely by female researchers. NX-5948 Female researchers exhibited a higher citation rate, as determined by the Field Citation Ratio, compared to male researchers in a range of fields: mathematical sciences, chemical sciences, technology, built environment and design, studies of human society, law and legal studies, and studies in creative arts and writing. The average FCR for women's first-authored articles surpassed that of men's in the majority of cases, including within areas like mathematical sciences, where male authors achieved a higher publication count.

Potential recipients are often required to submit text-based research proposals for review by funding institutions. Understanding the research supply within a specific domain can be assisted by the insights found within these documents. This work proposes an end-to-end methodology for semi-supervised document clustering, partly automating the classification of research proposals by their subject areas of interest. NX-5948 The methodology entails a three-stage approach, beginning with (1) manual annotation of a sample document, proceeding to (2) semi-supervised clustering of the documents, and concluding with (3) the evaluation of the cluster results via quantitative metrics and qualitative assessments of coherence, relevance, and distinctiveness by experts. To encourage reproducibility, the methodology is extensively detailed and demonstrated using real-world data. In this demonstration, proposals submitted to the US Army Telemedicine and Advanced Technology Research Center (TATRC) were sorted, with a focus on technological innovations in the field of military medicine. An examination of method characteristics, including unsupervised and semi-supervised clustering, various document vectorization techniques, and diverse cluster selection approaches, was conducted for a comparative analysis. The results show that the pretrained Bidirectional Encoder Representations from Transformers (BERT) embeddings were more suitable for this task, when measured against the performance of traditional text embedding techniques. When comparing expert evaluations of clustering algorithms, semi-supervised clustering's coherence ratings were approximately 25% higher than those from standard unsupervised clustering, with a negligible effect on cluster distinctiveness scores. The best cluster results were achieved by implementing a strategy for selection that equitably balanced considerations of internal and external validity. 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.