Quantitative Studies Of Science Research Articles

The gendered structure of science does not transpire in an experimental vacuum

Abstract An article recently published in Quantitative Science Studies proposed an apparently elegant solution to go past the alleged limits of “observational approaches” and “simple statistical associations” when it comes to the study of gender disparities in scientific funding (Cruz-Castro & Sanz-Menéndez, 2023, p. 594). A randomized experiment, it was claimed, would finally allow us to “measure the effects of a cause,” that is “the effect of the gender of the principal investigator (PI) on the score of a research funding application” (Cruz-Castro & Sanz-Menéndez, 2023, p. 594). And the finding of this trial was as clear as its formulation: there was no indication whatsoever that women’s applications had been evaluated differently than that of men. Peer Review https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/qss_c_00300

Uncovering the potential of Twitch as a source for social media metrics

The social live streaming service Twitch was launched in 2008 as Justin.tv, rebranded as Twitch Interactive in 2011, and acquired by Amazon in 2014. Although launched originally as a portal to broadcast videogames, Twitch currently hosts a wide range of content, including science and technology channels. Yet, despite growing interest in this online video sharing platform, Twitch’s potential for the study of science videos has been underexploited to date. This paper seeks to go some way to remedying this by studying the potential of Twitch as a data source for social media academic metrics. To do so, a scientometrics-inspired framework (the OBA framework) is proposed to integrate the analysis of Twitch, science videos and research organizations under a common conceptual space. Then, a science-related Twitch channel — National Aeronautics and Space Administration (NASA) — is used as a case study. We analyse 197 videos published by NASA between March 2017 and December 2022, as well as 51,935 clips created from NASA videos. Data were collected from the official Twitch API, which is also analysed to identify the units and metrics available and the channel’s performance in retrospective quantitative studies (i.e., non-live broadcasts). The results show that Twitch allows in-depth metric analyses of science videos to be undertaken, facilitating identification of both the activity and output-level impact of a scientific organization such as NASA. However, the Twitch API presents a few constraints, due, in the main, to the limited availability of many metrics that are restricted in time range, quantity, accuracy, or access, and which as such limit comprehensive retrospective studies. Despite these technical limitations, it is estimated that Twitch offers considerable potential for the study of science-related activity. The OBA model proposed facilitates the analysis of the activity of specific scientific agents (not only organizations but journals or other aggregates) under a conceptual framework based on approaches applied in quantitative studies of science.

Analysis of publication activity and priority subject areas of research in medicine in the Russian Federation

Introduction. Scientometric analysis is one of the progressive methods and key tools for quantitative and qualitative study of science, identification of priorities and trends of its development. 
 The purpose of the study is a scientometric study of Russia’s report activity in the field of medicine and determination of the priority subject issues of research in this area.
 Material and methods. The study was conducted using SciVal, according to scientometric indicators characterizing the number of publications in various categories and their citation for a three-year period (2019–2021) for the Russian Federation with the reference values for the world.
 Results. The main scientometric indicators (in number and share) characterizing the dynamics in Russia’s publication activity in medical sciences in 2019–2021 are considered and analyzed. A comparative analysis of the TOP five subject areas for 4 scientometric indicators for the world and the Russian Federation is carried out.
 Limitations. The research materials are limited to the results of the data uploading as of a specific date, as well as the selected time period.
 Conclusion. In the field of medicine, Russia is characterized by a steady growth and positive trend in the majority of the selected scientometric indicators. The leading subject areas of the Russian research are general medicine, public health, surgery, oncology, cardiology, immunology and allergology, clinical neurology. The scientometric analysis fully confirms the subject areas of the Russian scientific medical research to fully correspond to both domestic priority areas of medical science development specified in various regulatory documents and the world trends.

The rise of responsible metrics as a professional reform movement: A collective action frames account

Abstract Recent years have seen a rise in awareness around “responsible metrics” and calls for research assessment reforms internationally. Yet within the field of quantitative science studies and in research policy contexts, concerns about the limitations of evaluative bibliometrics are almost as old as the tools themselves. Given that many of the concerns articulated in recent reform movements go back decades, why has momentum for change grown only in the past 10 years? In this paper, we draw on analytical insights from the sociology of social movements on collective action frames to chart the emergence, development, and expansion of “responsible metrics” as a professional reform movement. Through reviewing important texts that have shaped reform efforts, we argue that hitherto, three framings have underpinned the responsible metrics reform agenda: the metrics skepticism framing, the professional-expert framing, and the reflexivity framing. We suggest that although these three framings have coexisted within the responsible metrics movement to date, cohabitation between these framings may not last indefinitely, especially as the responsible metrics movement extends into wider research assessment reform movements.

The notion of dominant terminology in bibliometric research

Abstract In this opinion paper, we introduce the expressions of dominant terminology and dominant term in the quantitative studies of science in analogy to the notion of dominant design in product development and innovation.

What are you reading? From core journals to trendy journals in the Library and Information Science (LIS) field

In this study, we present an objective, replicable methodology to identify trendy journals in any consolidated discipline. Trendy journals are those most read by authors who are currently publishing within the scope of the discipline. Trendy journal lists differ from consolidated lists of top core journals; the latter are very stable over time, mainly reflecting reputational factors, whereas the former reveal current influences not yet captured by studies based on bibliometric indicators or expert surveys. We apply our methodology to identify trendy journals among 167 titles indexed in the Web of Science category of the Information Science & Library Science (LIS) research area. Our list of trendy journals represents the most influential journals nowadays in the LIS discipline, challenging to some extent the core LIS journal list and journal category lists ordered by citations (e.g., by the Journal Impact Factor). Our results show that Scientometrics is the journal that bears the most influence on current production when not corrected for journal size and that Quantitative Science Studies—a small, relatively new journal not yet assigned a Journal Impact Factor nor present on any list of core LIS journals—is the journal that has shown the most significant recent influence when controlling for size.

The challenges of scientometric studies of predatory publishing

This issue of Quantitative Science Studies features the article “Predatory publishing in Scopus: Evidence on cross-country differences,” coauthored by Vít Macháček and Martin Srholec. Based on the Scopus database, this article studies how likely different countries are to publish in so-called predatory journals. Journals suspected to be predatory are identified using the well-known (and controversial) list of potentially predatory publishers and journals compiled by former librarian Jeffrey Beall.The article by Macháček and Srholec has a special history. Originally published in the journal Scientometrics (Macháček & Srholec, 2021), the article was retracted by the Editor-in-Chief following a complaint from the publisher Frontiers and a subsequent postpublication peer-review process (Anonymous, 2022). Two reasons were provided by the Editor-in-Chief of Scientometrics for the retraction: lack of a control group and focus on four publication languages (Arabic, English, French, and Spanish). The retraction led to considerable controversy (Oransky, 2021). The authors disagreed with the retraction (Srholec, 2022), and a substantial number of members of the Distinguished Reviewers Board of Scientometrics and recipients of the Derek de Solla Price Medal expressed their concerns in a letter (Abramo, Boyack et al., 2022; see also the editorial by Zhang, 2022). We also signed this letter.Following the retraction by Scientometrics, Macháček and Srholec reclaimed the copyright of their article, enabling them to submit their work elsewhere. They decided to submit their article to Quantitative Science Studies. As editors of Quantitative Science Studies, we do not agree with the arguments provided by Scientometrics for retracting the article, but we requested that Macháček and Srholec address some weaknesses that we identified in their article. In particular, we felt that the limitations of Beall’s list needed to be emphasized more strongly and that there was a need to better explain how suspected predatory journals may end up being indexed in the Scopus database. Macháček and Srholec addressed these issues by making a number of improvements to their article. Based on our editorial assessment, these improvements were sufficient to meet the standards of Quantitative Science Studies, and we therefore decided to accept the article for publication in the journal. Although the article published in Quantitative Science Studies is different from the article originally published in Scientometrics, we emphasize that the changes made do not relate to the reasons provided for retracting the article.We acknowledge that there are different views on predatory publishing in general, and on Beall’s list in particular. We therefore invite anyone who wishes to comment on the article by Macháček and Srholec to submit their views to Quantitative Science Studies. Commentaries should have a length of at most 1500 words. They will be considered for publication in a future issue of the journal.

Scientometric portrait of Professor Wolfgang Glänzel, an expert in the field of scientometrics

Professor Wolfgang Glänzel, an outstanding and leading professor at the University of Leuven (KU Leuven) in Belgium, received the international Derek John de Solla Price Award for remarkable contributions to the quantitative studies of science in 1999. During his 37yearsof scientific career, 276articles have been individually or collaboratively indexed with his name in Web of Science. Thirty five out of 276 papers were single authored by Glänzel, and the other 241 ones were collaborative works. Glänzel’s highest level of scientific productivity with 122 documents was during the years 2008 to 2017, when he was 53 to 62 years old. Scientometrics was his preferred journal. Glänzel has mainly collaborated with researchers from Hungary and Belgium, specifically some of the KU Leuven and the Hungarian Academy of Sciences. For instance, outstanding researchers including Schubert, Thijs, Braun and Zhang are part his authorship teams. Professor Glänzel has done considerable work in areas such as hybrid clustering, text mining, citation analysis, bibliometric analysis, scientometric indicators, altmetrics, and others.

Large number placements on a bounded number line: The importance of explanations

AbstractUnderstanding large number data is essential for making sense of real‐world problems. For the research reported here, our intent was to find connections between quantitative cognitive science studies and our prior qualitative study about participants' understanding of the relative size of large numbers. While all 23 cognitive science research studies that we reviewed focused only on participants' placements of large numbers on number lines, our study focused on preservice teachers' (PSTs; n = 128) strategies – placements and explanations for their placements – of one billion on a number line bounded by zero and one trillion. Our intent was to answer the following question: What are the connections between three plausible placements substantiated by cognitive scientists – linear; log‐linear; and segmented linear – of large numbers on number line tasks and the nine strategies identified in our qualitative study? We highlight exemplars from the nine PSTs' strategies to show connections between the three plausible placements. In doing so, we illustrate that asking participants to place large numbers on number lines only gives a partial picture of their understanding. Their explanations expand the placements by revealing inconsistencies among the placements and explanations. Implications for future research are also discussed.

New trends in scientific knowledge graphs and research impact assessment

New trends in scientific knowledge graphs and research impact assessment

Quantitative Studies of Science in Germany

Quantitative Studies of Science in Germany

The data paper as a sociolinguistic epistemic object: A content analysis on the rhetorical moves used in data paper abstracts

AbstractThe data paper is an emerging academic genre that focuses on the description of research data objects. However, there is a lack of empirical knowledge about this rising genre in quantitative science studies, particularly from the perspective of its linguistic features. To fill this gap, this research aims to offer a first quantitative examination of which rhetorical moves—rhetorical units performing a coherent narrative function—are used in data paper abstracts, as well as how these moves are used. To this end, we developed a new classification scheme for rhetorical moves in data paper abstracts by expanding a well‐received system that focuses on English‐language research article abstracts. We used this expanded scheme to classify and analyze rhetorical moves used in two flagship data journals, Scientific Data and Data in Brief. We found that data papers exhibit a combination of introduction, method, results, and discussion‐ and data‐oriented moves and that the usage differences between the journals can be largely explained by journal policies concerning abstract and paper structure. This research offers a novel examination of how the data paper, a data‐oriented knowledge representation, is composed, which greatly contributes to a deeper understanding of research data and its publication in the scholarly communication system.

The reinstrumentalization of theDiagnostic and Statistical Manual of Mental Disorders(DSM) in psychological publications: A citation context analysis

AbstractResearch instruments play significant roles in the construction of scientific knowledge, even though we have only acquired very limited knowledge about their life cycles from quantitative studies. This paper aims to address this gap by quantitatively examining the citation contexts of an exemplary research instrument, the Diagnostic and Statistical Manual of Mental Disorders (DSM), in full-text psychological publications. We investigated the relationship between the citation contexts of the DSM and its status as a valid instrument being used and described by psychological researchers. We specifically focused on how this relationship has changed over the DSM’s citation histories, especially through the temporal framework of its versions. We found that a new version of the DSM is increasingly regarded as a valid instrument after its publication; this is reflected in various key citation contexts, such as the use of hedges, attention markers, and the verb profile in sentences where the DSM is cited. We call this process the reinstrumentalization of the DSM in the space of scientific publications. Our findings bridge an important gap between quantitative and qualitative science studies and shed light on an aspect of the social process of scientific instrument development that is not addressed by the current qualitative literature.

Link-based approach to study scientific software usage: the case of VOSviewer

Scientific software is a fundamental player in modern science, participating in all stages of scientific knowledge production. Software occasionally supports the development of trivial tasks, while at other instances it determines procedures, methods, protocols, results, or conclusions related with the scientific work. The growing relevance of scientific software as a research product with value of its own has triggered the development of quantitative science studies of scientific software. The main objective of this study is to illustrate a link-based webometric approach to characterize the online mentions to scientific software across different analytical frameworks. To do this, the bibliometric software VOSviewer is used as a case study. Considering VOSviewer’s official website as a baseline, online mentions to this website were counted in three different analytical frameworks: academic literature via Google Scholar (988 mentioning publications), webpages via Majestic (1,330 mentioning websites), and tweets via Twitter (267 mentioning tweets). Google scholar mentions shows how VOSviewer is used as a research resource, whilst mentions in webpages and tweets show the interest on VOSviewer’s website from an informational and a conversational point of view. Results evidence that URL mentions can be used to gather all sorts of online impacts related to non-traditional research objects, like software, thus expanding the analytical scientometric toolset by incorporating a novel digital dimension.

Quantitative and Qualitative Studies of Science and Technology in Latin America

Quantitative and Qualitative Studies of Science and Technology in Latin America

Quantitative and qualitative studies of science and technology in Latin America

Quantitative and qualitative studies of science and technology in Latin America

Against method: Exploding the boundary between qualitative and quantitative studies of science

Quantitative and qualitative studies of science have historically played radically different roles with opposing epistemological commitments. Using large-scale text analysis, we see that qualitative studies generate and value new theory, especially regarding the complex social and political contexts of scientific action, while quantitative approaches confirm existing theory and evaluate the performance of scientific institutions. Large-scale digital data and emerging computational methods could allow us to refigure these positions, turning qualitative artifacts into quantitative patterns into qualitative insights across many scales, heralding a new era of theory development, engagement, and relevance for scientists, policy-makers, and society.

Quantitative science studies should be framed with middle-range theories and concepts from the social sciences

This paper argues that quantitative science studies should frame their data and analyses with middle-range sociological theories and concepts. We illustrate this argument with reference to the “sociology of professions,” a middle-range theoretical framework developed by Chicago sociologist Andrew Abbott. Using this framework, we counter the claim that the use of bibliometric indicators in research assessment is pervasive in all advanced economies. Rather, our comparison between the Netherlands and Italy reveals major differences in the national design of bibliometric research assessment: The Netherlands follows a model of bibliometric professionalism, whereas Italy follows a centralized bureaucratic model that co-opts academic elites. We conclude that applying the sociology of professions framework to a broader set of countries would be worthwhile, allowing the emerging bibliometric profession to be charted in a comprehensive, and preferably quantitative, fashion. We also briefly discuss other sociological middle-range concepts that could potentially guide empirical analyses in quantitative science studies.

The impact of J. D. Bernal’s thoughts in the science of science upon China: Implications for today’s quantitative studies of science

John Desmond Bernal (1901–1970) was one of the most eminent scientists in molecular biology and is also regarded as the founding father of the science of science. His book The social function of science laid the theoretical foundations for the discipline. In this article, we summarize four chief characteristics of his ideas in the science of science: the sociohistorical perspective, theoretical models, qualitative and quantitative approaches, and studies of science planning and policy. China has constantly reformed its scientific and technological system based on research evidence of the science of science. Therefore, we analyze the impact of Bernal’s science-of-science thoughts on the development of China’s science of science, and discuss how they might be usefully taken still further in quantitative studies of science.

Past as prologue: Approaches to the study of confirmation in science

In the 1970s, quantitative science studies were being pursued by sociologists, historians, and information scientists. Philosophers were part of this discussion, but their role would diminish as sociology of science asserted itself. An antiscience bias within the sociology of science became evident in the late 1970s, which split the science studies community, notably causing the “citationists” to go their own way. The main point of contention was whether science was a rational, evidence-based activity. To reverse the antiscience trend, it will be necessary to revive philosophical models of science, such as Bayesian confirmation theory or explanatory coherence models, where theory-experiment agreement plays a decisive role. A case study from the history of science is used to illustrate these models, and bibliometric and text-based methods are proposed as a source of data to test these models.