Frontiers in research metrics and analytics最新文献

Purpose: The purpose of this article is to investigate particular aspects of the STEM job market in the US. In particular, we ask: could the possession of high performance computing (HPC) skills enhance the chances of a person getting a job and/or increase starting salaries for people receiving an undergraduate or graduate degree and entering the technical workforce (rather than academia)? We also estimate the value to the US economy of practical experience offered to US students through training about HPC and the opportunity to use HPC systems funded by the National Science Foundation (NSF) and accessible nationally.

Methods: Interviews and surveys of employers of graduates in STEM fields were used to gauge demand for STEM graduates with practical HPC experience and the salary increase that can be associated with the possession of such skills. We used data from the XSEDE project to determine how many undergraduate and graduate students it enabled to acquire practical proficiency with HPC.

Results: People with such skills who had completed an undergraduate or graduate degree received an initial median hiring salary of approximately 7%-15% more than those with the same degrees who did not possess such skills. XSEDE added approximately $10 million or more per year to the US economy through the practical educational opportunities it offered.

Discussion: Practical hands-on experience provided by the US federal government, as well as many universities and colleges in the US, holds value for students as they enter the workforce.

Conclusion: Practical training in HPC during the course of undergraduate and graduate programs has the potential to produce positive individual labor market outcomes (i.e., salary boosts, signing bonuses) as well as to help address the shortage of STEM workers in the private sector of the US.

Introduction: The emergence of artificial intelligence (AI) has revolutionised higher education teaching and learning. AI has the power to analyse large amounts of data and make intelligent predictions thus changing the whole teaching and learning processes. However, such a rise has led to institutions questioning the morality of these applications. The changes have left librarians and educators worried about the major ethical questions surrounding privacy, equality of information, protection of intellectual property, cheating, misinformation and job security. Libraries have always been concerned about ethics and many go out of their way to make sure communities are educated about the ethical question. However, the emergence of artificial intelligence has caught them unaware.

Methods: This research investigates the preparedness of higher education librarians to support the ethical use of information within the higher and tertiary education fraternity. A qualitative approach was used for this study. Interviews were done with thirty purposively selected librarians and academics from universities in Zimbabwe.

Results: Findings indicated that many university libraries in Zimbabwe are still at the adoption stage of artificial intelligence. It was also found that institutions and libraries are not yet prepared for AI use and are still crafting policies on the use of AI.

Discussion: Libraries seem prepared to adopt AI. They are also prepared to offer training on how to protect intellectual property but have serious challenges in issues of transparency, data security, plagiarism detection and concerns about job losses. However, with no major ethical policies having been crafted on AI use, it becomes challenging for libraries to full adopt its usage.

Patent analytics is crucial for understanding innovation dynamics and technological trends. However, a comprehensive overview of this rapidly evolving field is lacking. This study presents a data-driven analysis of patent research, employing citation network analysis to categorize and examine research clusters. Here, we show that patent research is characterized by interconnected themes spanning fundamental patent systems, indicator development, methodological advancements, intellectual property management practices, and diverse applications. We reveal central research areas in patent strategies, technological impact, and patent citation research while identifying emerging focuses on environmental sustainability and corporate innovation. The integration of advanced analytical techniques, including AI and machine learning, is observed across various domains. This study provides insights for researchers and practitioners, highlighting opportunities for cross-disciplinary collaboration and future research directions.

Big Data communication researchers have highlighted the need for qualitative analysis of online science conversations to better understand their meaning. However, a scholarly gap exists in exploring how qualitative methods can be applied to small data regarding micro-bloggers' communications about science articles. While social media attention assists with article dissemination, qualitative research into the associated microblogging practices remains limited. To address these gaps, this study explores how qualitative analysis can enhance science communication studies on microblogging articles. Calls for such qualitative approaches are supported by a practical example: an interdisciplinary team applied mixed methods to better understand the promotion of an unorthodox but popular science article on Twitter over a 2-year period. While Big Data studies typically identify patterns in microbloggers' activities from large data sets, this study demonstrates the value of integrating qualitative analysis to deepen understanding of these interactions. In this study, a small data set was analyzed using NVivo™ by a pragmatist and MAXQDA™ by a statistician. The pragmatist's multimodal content analysis found that health professionals shared links to the article, with its popularity tied to its role as a communication event within a longstanding debate in the health sciences. Dissident professionals used this article to support an emergent paradigm. The analysis also uncovered practices, such as language localization, where a title was translated from English to Spanish to reach broader audiences. A semantic network analysis confirmed that terms used by the article's tweeters strongly aligned with its content, and the discussion was notably pro-social. Meta-inferences were then drawn by integrating the findings from the two methods. These flagged the significance of contextualizing the sharing of a health science article in relation to tweeters' professional identities and their stances on health-related issues. In addition, meta-critiques highlighted challenges in preparing accurate tweet data and analyzing them using qualitative data analysis software. These findings highlight the valuable contributions that qualitative research can make to research involving microblogging data in science communication. Future research could critique this approach or further explore the microblogging of key articles within important scientific debates.

US national expert advisory bodies related to science, technology, and innovation (STI) policy have a wide range of missions, governing structures, operational practices, cultures, and impact on federal policymaking. This paper offers an analytical framework for assessing the autonomy, function, and influence of the President's Council of Advisors on Science and Technology (PCAST), a federal advisory committee consisting of 30 elite scientists, engineers, and industry leaders appointed by and advising the president. We demonstrate that PCAST carries both a strong instrumental advisory role, providing substantive advice to White House STI policy development, and a significant symbolic advisory role, offering visible public support to presidential decisions and initiatives related to STI. However, we find that the council's engagement with either or both roles has shifted depending on its available resources, the policy agenda of the administration it serves, the level of presidential attention, and the priorities of council leadership. The paper concludes with recommendations to guide future PCASTs in fulfilling their mission and appropriately influencing US national STI policy.

This paper discusses how harmful practices such as child marriage and female genital mutilation/cutting (FGM/C) can be effectively explored through feminist methodologies that center the lived experiences of girls and young women affected by these issues. Eliminating harmful practices, which are rooted in gender inequality and have myriad life-course consequences for those who experience them, has become a global priority in recent years. However, dominant conceptualizations of the drivers and consequences of child marriage and FGM/C often fail to adequately engage with or reflect adolescent girls' own nuanced experiences and perceptions. A feminist epistemology underlines the need for research methods that can uncover and address dynamics of power and inequality, as well as the complexities of voice and agency surrounding these practices, both of which perpetuate harmful practices and marginalize the voices of those who are most affected. The paper discusses adaptations to two key sets of methodological tools used with adolescent girls in research on FGM/C in Ethiopia and on child marriage in Bangladesh, Ethiopia, Jordan, and Lebanon as part of the Gender and Adolescence: Global Evidence (GAGE) longitudinal study. The purpose of these tools was to address and shift power inequalities, both within the research process and in girls' lives more widely. The Social Network Hexagon, Marriage Chain, and Marriage Decision-Making Pairs tools were used to explore child marriage decision-making processes and dynamics and outcomes for adolescent girls. A vignette-based discussion on FGM/C and child marriage and a version of a Social Network Hexagon tool were used to improve understanding of adolescents' social networks and the extent to which these shape their options for change. We find that context-specific adaptations to the tools, determined through ongoing reflexive dialogue with local researchers, were key to creating space for deep reflection and engagement by girls. Exploring the wider structural and social dynamics that enable and constrain girls' agency and decision-making around harmful practices was also key. It enabled insights into the complex ways in which gender- and age-based social norms are exercised within girls' socio-ecological contexts, as well as possible entry points for change.

This paper proposes a novel framework for evaluating research performance in university rankings, utilizing journal citation-based metrics and scholarly output instead of traditional article citation metrics. Through correlation analysis, we compare the proposed metrics with article citation metrics used by prominent ranking systems (THE and QS) and demonstrate significantly higher correlations with established rankings (QS, THE, and ARWU). The proposed metrics exhibit robustness over time and offer a fairer evaluation by emphasizing objective performance and mitigating citation biases. This framework provides institutions with a more accurate benchmarking tool to inform strategic decisions and resource allocation. While acknowledging potential limitations in data availability and the challenge of achieving global consensus, this study contributes to the ongoing discourse on university rankings by advocating for a more equitable and robust evaluation system by balancing diverse metrics and offering more standardized measures.

This study explores and elucidates the phenomenon of indifference in theorizing within management research in Iran, highlighting the causal conditions and implications of this indifference on both the academic and practical landscapes of management. Using a qualitative grounded theory methodology, this study synthesized the data collected through interviews with management faculty members from various Iranian universities. Purposive sampling was employed to select participants until theoretical saturation was achieved with 29 interviews. The data were analyzed using ATLAS.ti software, enabling the construction of a paradigm model to explain the observed phenomena. The study identified multiple causal conditions contributing to indifference in theorizing, including individual, educational, cultural, economic, social, political, and systemic factors. These factors collectively foster a climate of scientific isolation, hindering the development of management theories and affecting both educators and students. The outcomes of this indifference manifest as a reduction in theoretical innovation and diminished engagement with management theory among academics and practitioners. Indifference, as a key concept in the presented model, represents a type of scientific silence, indicating the unwillingness or inability of researchers to create new and effective theories in the field of management. This research contributes to the field by providing a detailed model of the dynamics underlying indifference in theorizing within management studies in Iran, a topic that has received limited attention in the existing literature. The study's findings emphasize the need for systemic changes to overcome barriers to theorizing and suggest pathways for revitalizing theoretical contributions in management research.

Qualitative research is widely embraced in the social sciences and education. Among the different traditional, modern, and community-oriented qualitative methodologies, we have drawn on our experiences to adopt seven qualitative methodologies: auto/ethnography, narrative inquiry, participatory action research, ethnography, case study, grounded theory, and phenomenology. Despite the abundance of literature on qualitative methodologies, there is still a need for a more focused exploration of participant selection procedures in qualitative studies. This article examines the discourse around participant selection procedures within these seven methodologies, highlighting their unique nuances and differences. It offers practical insights and guidelines for novice and experienced researchers and graduate and postgraduate students to enhance their understanding of participant selection procedures, and some thinking points for consideration. Drawing from our experiences, we aim to provide a useful resource that encourages thoughtful consideration of participant selection in qualitative studies.

This article examines the landscape of Science, Technology, and Innovation policies in Central America, focusing on Nicaragua, Guatemala, Honduras, and El Salvador. These nations face significant challenges in leveraging STI for sustainable development, including financial constraints and limited resources. Additionally, Central America struggles with systemic issues such as corruption, violence, and high levels of emigration, further complicating efforts to advance STI. A workshop organized by Georgetown University's Science Technology and International Affairs program brought together scholars to discuss STI policies, resulting in key recommendations. The article highlights critical challenges, including over-reliance on state funding, stagnant researcher numbers, and the pressing need for research diversification. It emphasizes the importance of youth engagement, leadership, and resilience in shaping effective STI policies. Recommendations include investing in science education, establishing governmental scientific advisory bodies, promoting research diversity, and addressing climate change through STI strategies. The findings provide valuable insights for scholars, policymakers, and international organizations working with less developed nations globally.