Frontiers in research metrics and analytics最新文献

This article appreciates decolonization in education, positing bicultural pedagogy as peace pedagogy. It will encapsulate peace education, peace pedagogy, colonization, Indigenous rediscovery, and Indigenization of the curriculum (biculturalism) and then turn to the transformative practice of decolonization in education. The paper seeks to propose a conceptual bridging facet from five core Māori values: wairuatanga, manaakitanga, kotahitanga, whanaungatanga, and rangatiratanga, to Indigenous pedagogy and, finally, to peace pedagogy. The alignment of Indigenous pedagogy and peace pedagogy is an attempt to evaluate the potential of bicultural peace pedagogy as a decolonizing education. The paper finds congruence between Western peace pedagogy and several gaps related to practice and cultural goals. To assist other non-Indigenous knowledge workers (termed Pākehā in Aotearoa/New Zealand) in decolonizing education, this paper has sought to elevate aspects of peace culture that align with Indigenous practices/values.

Introduction: The current study explored the influence of Chat Generative Pre-Trained Transformer (ChatGPT) on the concepts, parameters, policies, and practices of creativity and plagiarism in academic and research writing.

Methods: Data were collected from 10 researchers from 10 different countries (Australia, China, the UK, Brazil, Pakistan, Bangladesh, Iran, Nigeria, Trinidad and Tobago, and Turkiye) using semi-structured interviews. NVivo was employed for data analysis.

Results: Based on the responses, five themes about the influence of ChatGPT on academic and research writing were generated, i.e., opportunity, human assistance, thought-provoking, time-saving, and negative attitude. Although the researchers were mostly positive about it, some feared it would degrade their writing skills and lead to plagiarism. Many of them believed that ChatGPT would redefine the concepts, parameters, and practices of creativity and plagiarism.

Discussion: Creativity may no longer be restricted to the ability to write, but also to use ChatGPT or other large language models (LLMs) to write creatively. Some suggested that machine-generated text might be accepted as the new norm; however, using it without proper acknowledgment would be considered plagiarism. The researchers recommended allowing ChatGPT for academic and research writing; however, they strongly advised it to be regulated with limited use and proper acknowledgment.

Introduction: Indigenous communities globally are inequitably affected by non-communicable diseases such as cancer and coronary artery disease. Increased focus on personalized medicine approaches for the treatment of these diseases offers opportunities to improve the health of Indigenous people. Conversely, poorly implemented approaches pose increased risk of further exacerbating current inequities in health outcomes for Indigenous peoples. The advancement of modern biology techniques, such as three-dimensional (3D) in vitro models and next generation sequencing (NGS) technologies, have enhanced our understanding of disease mechanisms and individualized treatment responses. However, current representation of Indigenous peoples in these datasets is lacking. It is crucial that there is appropriate and ethical representation of Indigenous peoples in generated datasets to ensure these technologies can be used to maximize the benefit of personalized medicine for Indigenous peoples.

Methods: This project discusses the use of 3D tumor organoids and single cell/nucleus RNA sequencing to study cancer treatment responses and explore immune cell roles in coronary artery disease. Using key pillars from currently available Indigenous bioethics frameworks, strategies were developed for the use of Māori participant samples for live tissue and sequencing studies. These were based on extensive collaborations with local Māori community, scientific leaders, clinical experts, and international collaborators from the Broad Institute of MIT and Harvard. Issues surrounding the use of live tissue, genomic data, sending samples overseas and Indigenous data sovereignty were discussed.

Results: This paper illustrates a real-world example of how collaboration with community and the incorporation of Indigenous worldviews can be applied to molecular biology studies in a practical and culturally responsive manner, ensuring fair and equitable representation of Indigenous peoples in modern scientific data.

This study aimed to measure the consistency of the impact of scientific production, weighted by authorship, of Italian scientists in two academic disciplines (AD) of Exercise and Sports Sciences (ESS) from 2017 to 2022, with a specific focus on the subfield "Sport Sciences", using topic-specific keywords. Through the Scopus database, the scientific products of Italian ESS scientists associated with each keyword were identified. Subsequently, total and relative metric parameters from 2017 to 2022 were collected, including the total and relative number of citations. To evaluate the impact of the publications, the total and relative h-index were calculated, and weighted by considering different categories of authorship. Specific weights were attributed to each category: single author, first author, last author and co-author, following the classifications already in use on Scopus for each author. The trends of total and relative metrics, including citations and h-index, from 2017 to 2022 were analyzed using Spearman's correlation. Non-parametric linear regression analysis was used for the predictive analysis of these trends. Among the 83 identified ESS scientists, a detailed analysis revealed that 31.3% were full professors, 42.1% associate professors, and 26.6% researchers. Less than half of these scientists were directly affiliated with ESS. Despite minority representation, significant positive correlations emerge between total and relative citations from 2017 to 2022 (r = 0.687) and between the weighted total h-index and the weighted relative h-index (r = 0.965). Significant trends emerge in the metric parameters of the same scientists when analyzed separately by AD. The regression results indicate that variations in total citations and the weighted total and relative h-index can predict or explain the observed changes in 2017-2022 (p < 0.05). This result suggests that the production and impact of research in the field of ESS follow the same general trend as production and impact in the specific subfield.

Introduction: In today's era, conducting nursing research is crucial for the advancement of the nursing profession. Scientific publications in clinical research aim to improve patient care outcomes and foster a sense of importance for nurses within the healthcare team. However, clinical nurses often fall behind due to factors such as limited familiarity, attitudes toward research, and encountered barriers.

Objectives: This study was conducted to assess the knowledge, attitude, and perceived barriers regarding scientific research publications among clinical nurses at tertiary care hospitals in western Rajasthan.

Methodology: A cross-sectional descriptive study was conducted among the clinical nurses. The participants were assessed for their knowledge, attitude, and perceived barriers regarding scientific research publications through a self-administered questionnaire.

Results: The study revealed that 92% of the participants lacked sufficient knowledge about scientific research publications and 78.3% experienced moderate perceived barriers. Pearson's correlation coefficient indicated a weak positive correlation (r = 0.143, p = 0.007) between knowledge and attitude and a significant negative correlation (r = -0.143, p = 0.012) between knowledge and perceived barriers. However, multiple linear regression analysis showed no significant relationship among the clinical nurses in terms of knowledge, attitude, and perceived barriers toward scientific research publications.

Conclusion: This study on clinical nurses revealed that the majority had insufficient knowledge about scientific research, while over half had neutral attitudes toward research publications. In addition, a significant portion of the clinical nurses reported experiencing moderate perceived barriers.

This article presents a perspective on the impact of algorithmic bias on information fairness and trust in artificial intelligence (AI) systems within the African context. The author's personal experiences and observations, combined with relevant literature, formed the basis of this article. The authors demonstrate why algorithm bias poses a substantial challenge in Africa, particularly regarding fairness and the integrity of AI applications. This perspective underscores the urgent need to address biases that compromise the fairness of information dissemination and undermine public trust. The authors advocate for the implementation of strategies that promote inclusivity, enhance cultural sensitivity, and actively engage local communities in the development of AI systems. By prioritizing ethical practices and transparency, stakeholders can mitigate the risks associated with bias, thereby fostering trust and ensuring equitable access to technology. Additionally, the article explores the potential consequences of inaction, including exacerbated social disparities, diminished confidence in public institutions, and economic stagnation. Ultimately, this work argues for a collaborative approach to AI that positions Africa as a leader in responsible development, ensuring that technology serves as a catalyst for sustainable development and social justice.

Debates on intellectual property rights and open source frequently stem from the business sector and higher education, where goals are typically oriented toward profit, academic status, credit, and/or reputation. What happens if we reconsider the ethics of intellectual property rights and open source when our driving motivation is advancing women's health and rights? How does this prioritization complicate our assumptions of copyright and open access? How can we embark on a journey that validates the complex realities of multiple stakeholders who have good intent, but do not always consider the unintended impacts and the broader power dynamics at play? This paper explores the tensions and nuances of sharing methodologies that aim to transform harmful gender norms in an ecosystem that does not always consider the complex challenges behind intellectual property and open-source material. As a thought-collective dedicated to using a feminist approach to unpack and promote the principles of ethical, effective, and sustainable scale, we hope to underscore how the current research and debates on intellectual property rights and open-source material have good aims but may also fall short in encompassing the realities of gendered social norms change in and with communities around the world. We conclude with key recommendations for donors, researchers, International Development Corporations, International Non-Governmental Organizations, and those interested in using or adapting dynamic, gender transformative materials created by others.

In this study, we analyze the changes over time in the complexity and structure of words used in article titles and the connections between articles in citation networks, focusing on the topic of artificial intelligence (AI) up to 2020. By measuring unpredictability in word usage and changes in the connections between articles, we gain insights into shifts in research focus and diversity of themes. Our investigation reveals correspondence between fluctuations in word complexity and changes in the structure of citation networks, highlighting links between thematic evolution and network dynamics. This approach not only enhances our understanding of scientific progress but also may help in anticipating emerging fields and fostering innovation, providing a quantitative lens for studying scientific domains beyond AI.

An increasingly popular form of collaboration involves forming partnerships among researchers, educators, and community members to improve or transform education systems through research inquiry. However, not all partnerships are successful. The field needs valid, reliable, and useful measures to help with assessing progress toward partnership goals. In this community case study, we present a participatory, mixed-methods approach for creating measures to assess the progress of education research-practice partnerships (RPPs). The case illustrates a novel approach to measurement design, driven by perspectives and feedback of over 300 members of 80 partnerships. As a result, the measures align with the values and practices of the very collaborations the measures were intended to assess.

Patents are essential for transferring scientific discoveries to meaningful products that benefit societies. While the academic community focuses on the number of citations to rank scholarly works according to their "scientific merit," the number of citations is unrelated to the relevance for patentable innovation. To explore associations between patents and scholarly works in publicly available patent data, we propose to utilize statistical methods that are commonly used in biology to determine gene-disease associations. We illustrate their usage on patents related to biotechnological trends of high relevance for food safety and ecology, namely the CRISPR-based gene editing technology (>60,000 patents) and cyanobacterial biotechnology (>33,000 patents). Innovation trends are found through their unexpected large changes of patent numbers in a time-series analysis. From the total set of scholarly works referenced by all investigated patents (~254,000 publications), we identified ~1,000 scholarly works that are statistical significantly over-represented in the references of patents from changing innovation trends that concern immunology, agricultural plant genomics, and biotechnological engineering methods. The detected associations are consistent with the technical requirements of the respective innovations. In summary, the presented data-driven analysis workflow can identify scholarly works that were required for changes in innovation trends, and, therefore, is of interest for researches that would like to evaluate the relevance of publications beyond the number of citations.