The researchers began with a comprehensive search of the Scopus database to retrieve relevant studies published up to 2025. They then performed keyword co-occurrence analysis using VOSviewer software to identify patterns and relationships among the terms in the retrieved literature. This bibliometric approach maps the conceptual structure of publications rather than directly testing the biological effects of a specific environmental stressor, conservation measure or management intervention.

Across the analyzed periods, concepts associated with ecosystem behavior and dynamics varied over time. The authors categorized the changing patterns into five principal streams: Biological Conservation; Ecosystem Services; Resilience and Adaptive Management; Restoration and Rehabilitation with Biological Technologies; and Integrated Sustainability and Health. The result is a historical view of how research emphasis and connections among terms evolved within the study’s 25-year analytical scope. It does not demonstrate that ecosystems improved, declined or responded consistently to stress, because the analysis concerns the published research record rather than direct ecological outcomes.

The study’s scope and method also define its limitations. It characterizes the distribution and evolution of concepts in a corpus retrieved from one bibliographic database, and the five streams represent the clusters detected through keyword co-occurrence analysis rather than a complete account of ecosystem science. The available research summary reports no measured effect sizes, field results or policy effects. Its central finding is that the literature on ecosystem behavior and dynamics under environmental stress developed into five recognizable conceptual streams between 2000 and 2025, with concepts and their relationships shifting across successive five-year intervals.

Subject of Research: Bibliometric mapping of research on ecosystem responses to environmental stress

Article Title: The concept of ecosystem behavior and dynamics in response to environmental stressors: a bibliometric analysis

Article References: Safardoust, A., Tatina, S., & Ghazinoory, S. (2026). The concept of ecosystem behavior and dynamics in response to environmental stressors: a bibliometric analysis. Journal of Environmental Studies and Sciences. https://doi.org/10.1007/s13412-026-01153-5

Image Credits: AI Generated

DOI: 10.1007/s13412-026-01153-5

Keywords: ecosystem dynamics, environmental stress, bibliometric analysis, Scopus, keyword co-occurrence, VOSviewer, ecosystem services, ecological resilience, adaptive management, conservation, concept, ecosystem

Researchers used Biblioshiny and VOSviewer to examine publication output, citation impact, active research domains and patterns of international collaboration. Their mapping found substantial intellectual connectivity across the literature, but the international collaboration network was centered on North–North and North–South connections. International collaboration accounted for 19.42% of the analyzed articles.

The abstract reports fluctuations in annual publication output and states that the pattern was responsive to the global context. Citation patterns were described as intricate, while research productivity remained dominated by the Global North despite growing participation from the Global South. The authors characterized the overall mapping as evidence of the relevance of civil society scholarship and said that the field requires more inclusive collaboration and deeper contextual research.

This report is based on the study’s published abstract rather than the full subscription article. The available evidence supports the scope, methods and main descriptive findings of the Scopus analysis, but it does not provide the article-level results, sensitivity analyses, journal coverage details, classification procedures or other methodological details needed for a fuller assessment of the study’s limitations. The analysis measures patterns in Scopus-indexed civil society research from 2019 through 2024; it does not itself establish changes in civil society activity or outcomes in society.

Subject of Research: Bibliometric analysis of global civil society research published in Scopus from 2019 to 2024.

Article Title: Bibliometric analysis of civil society: trends and developments from 2019-2024

Article References: Nalle, E. S., & Sugito (2026). Bibliometric analysis of civil society: trends and developments from 2019-2024. SN Social Sciences, 6(9), Article 377. https://doi.org/10.1007/s43545-026-01652-w

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01652-w

Keywords: civil society, bibliometric analysis, Scopus, Biblioshiny, VOSviewer, international collaboration, Global North, Global South, democracy, human rights, governance, NGOs

The researchers searched Scopus on March 4, 2026, with a structured query combining “artificial intelligence,” “AI,” “machine learning” and “deep learning” with terms covering sustainability, water management, water conservation, water use, water supply and hydrology. The initial search returned 5,215 records. Following title-and-abstract screening, 1,935 entries were excluded, leaving 3,280 articles for analysis. The 2015–2025 window was intended to capture a period of rapid development in AI, big-data analytics, cloud computing and Internet of Things-enabled environmental monitoring, while ending with the most recent complete publication year available at the time of data collection.

Only English-language research articles were eligible. Reviews, book chapters, short surveys, notes, books and retracted papers were excluded. The authors acknowledged that restricting the language and publication format could omit influential work, while dependence on the chosen search terms could miss relevant studies that used different terminology. The review was also limited to Scopus and did not search sources such as Web of Science or Google Scholar.

VOSviewer version 1.6.20 was used to construct bibliometric maps and visualize annual publication and citation trends, co-authorship, keyword co-occurrence and co-citation relationships. Publication and citation indicators, together with h-index and g-index measures, were used to assess research output and citation impact. These measures do not independently establish scientific quality, practical effectiveness or whether AI systems outperform conventional water-management approaches.

The 3,280 articles were distributed across 26 subject categories. Environmental science accounted for 36% of the corpus, while Earth and Planetary Sciences, engineering and Agricultural and Biological Sciences each represented 9%; computer science represented 6%. The articles appeared in 710 journals, led by Science of the Total Environment with 207 publications, followed by Water with 154 and the Journal of Environmental Management with 151.

China was the largest national contributor, with 1,033 publications, or 31.4% of the corpus. The United States followed with 560 publications, representing 17.0%; India had 460, or 14.0%; Iran had 296, or 9.0%; and Saudi Arabia had 194, or 5.91%. The publications came from 134 countries and regions, and the review’s collaboration analysis associated Chinese researchers with more than 45% of the field’s co-authored output. The discussion links China’s publication lead to investment in AI and environmental monitoring, national research programs, research infrastructure and collaboration among universities, research institutes and industry.

Government and institutional funding was also prominent. The National Natural Science Foundation of China was associated with 531 publications, followed by China’s National Key Research and Development Program with 199. The U.S. National Science Foundation funded 80 articles and the European Commission 53, while the Fundamental Research Funds of Central Universities, Chinese Academy of Sciences and National Research Foundation of Korea were associated with 55, 52 and 39 publications, respectively. The U.S. Geological Survey was associated with 37 publications, the China Postdoctoral Science Foundation with 36, and Brazil’s Conselho Nacional de Desenvolvimento Científico e Tecnológico with 35.

Among 7,671 contributing research centers, the University of Chinese Academy of Sciences in Beijing led with 56 articles, followed by Beijing Normal University with 33. The corpus included 14,348 authors. Zaher Mundher Yaseen was the most prolific with 21 articles, followed by Sani Isah Abba and Ahmed Elbeltagi with 18 each and Ozgur Kisi with 15. A total of 139 authors had co-authored at least five papers, and these authors were distributed across 11 collaboration clusters.

Keyword analysis identified 22,646 distinct terms. Machine learning, water management, water supply and water quality were among the most frequent, while artificial intelligence, environmental monitoring and prediction also appeared prominently. The main themes included water-quality prediction, hydrological modelling, environmental monitoring and decision-support systems. Co-citation analysis identified random forests, neural networks and boosting algorithms as foundational machine-learning methods. Applications described in the reviewed literature included forecasting pollutants in surface and groundwater, modelling rainfall-runoff, evapotranspiration, groundwater levels and river flow, and analyzing wastewater-treatment operations for aeration control and energy use. These were reported applications in the literature, not systems directly tested by the bibliometric review.

The authors identified hybrid models combining machine learning with physics-based approaches, explainable artificial intelligence, integration with Internet of Things sensors, cloud computing and digital twins, and improved data quality and standardization as future research directions. They also noted that many water-management studies use small datasets, which may limit the applicability of machine-learning models. Because the review depended on Scopus coverage, English-language research articles and selected search terms, its maps describe a bounded bibliometric corpus rather than the complete global evidence base.

Subject of Research: Bibliometric analysis of artificial intelligence research for sustainable water management

Article Title: Mapping the knowledge structure and evolution of artificial intelligence for water reuse and sustainable water management

Article References: Kumar, N., Nagar, M. R., Dharsandia, I., Tiwari, A., Mishra, S. K., & Kumar, M. (2026). Mapping the knowledge structure and evolution of artificial intelligence for water reuse and sustainable water management. Discover Artificial Intelligence, 6(1), Article 1442. https://doi.org/10.1007/s44163-026-02389-4

Image Credits: AI Generated

DOI: 10.1007/s44163-026-02389-4

Keywords: artificial intelligence, sustainable water management, bibliometric analysis, machine learning, water quality prediction, hydrological modelling, wastewater treatment, research collaboration, Scopus, VOSviewer, Mapping, knowledge

The team, led by Ishrat Ayub Sofi of the Department of Library and Information Science at the University of Kashmir, together with Yasir Rashid Lone, Taseef Ayub and Shabir Ahmad Ganaie, analysed 77 open-access articles on plagiarism drawn from the Web of Science database, restricting the corpus to outputs from reputed academic publishers. The choice of an open-access subset is significant: it means the map reflects literature that any researcher, educator or policymaker anywhere in the world can actually read, rather than a body of work locked behind paywalls. The study was supported by a fellowship from the Indian Council of Social Science Research, which funds Sofi’s doctoral research.

Technically, the analysis relied on two of the most widely used bibliometric tools in the field. Biblioshiny, the graphical interface of the Bibliometrix R package, was used to compute descriptive statistics on the corpus, including annual scientific production, author productivity, source impact, and keyword co-occurrence. VOSviewer, a network visualisation tool developed at Leiden University, was used to construct and render a bibliographic coupling network, in which two articles are linked when they cite the same references. The stronger the overlap in cited literature, the closer two papers sit in the map, allowing the researchers to identify clusters of work that share an intellectual foundation even if their authors have never cited one another directly.

Bibliographic coupling differs from the better-known co-citation analysis in an important way. Because it links newly published papers through their shared reference lists, it is particularly sensitive to recent research fronts: a cluster of tightly coupled 2024 and 2025 papers signals an active conversation happening right now. This makes the method well suited to the study’s central question, which is not merely how much plagiarism research exists, but where the field’s intellectual energy is currently concentrated and which themes are gaining momentum.

The headline finding is that contemporary publications on plagiarism are more impactful than earlier ones. In bibliometric terms, the study found that recent articles in the corpus outperform older publications on impact measures, suggesting that the field is not simply accumulating more papers but producing work that resonates more strongly with the research community. That pattern is consistent with a maturing discipline: as the literature on a topic grows, later studies can build on established concepts, validated instruments and prior findings, producing papers that are better positioned to attract citations.

Where is this work being published? The analysis identified BMC Medical Education and Heliyon as the top sources preferred for plagiarism research. Both are large open-access journals, and their prominence points to something structurally important about the field. BMC Medical Education sits at the intersection of medical training and research ethics, while Heliyon is a multidisciplinary mega-journal. The dominance of these two venues suggests that much of the most visible plagiarism research is being produced by educators and researchers concerned with academic integrity in training contexts, and that the topic resists confinement to any single disciplinary journal.

Geographically, the study found that China and the United States lead in terms of research impact. This is a notable pairing, because the two countries approach the problem from different institutional contexts. The United States has a long tradition of honour codes and academic integrity offices, while Chinese institutions have in recent years intensified scrutiny of research misconduct amid national efforts to raise the quality and reputation of domestic science. That research from both systems ranks highest in impact indicates that concerns about textual reuse, credit and originality are genuinely global, and that the most influential studies draw on evidence from multiple educational and cultural settings.

The keyword and thematic analysis revealed a field that is increasingly collaborative and multidisciplinary. Plagiarism research now draws on library and information science, higher education studies, psychology, ethics, and computing. Recent work cited in the study spans surveys of biomedical researchers’ perceptions of plagiarism across Europe and China, longitudinal experiments on how plagiarism awareness efforts shape students’ ethical judgement and behaviour, and investigations of the antecedents of plagiarism using the extended theory of planned behaviour, a psychological framework that models intentions as products of attitudes, social norms and perceived control. The presence of such theory-driven work alongside detection-tool reviews and bibliometric self-studies illustrates the breadth the field has achieved.

The timing of this map is not accidental. The research community is confronting a new and destabilising variable: generative artificial intelligence. Tools that can produce fluent original-seeming text on demand have complicated the very definition of plagiarism, which historically centred on copying human-authored sources without attribution. Recent studies on the ethics of generative AI in social science research, cited in the new analysis, reflect a growing recognition that institutional policies built around text-matching software may be inadequate for a world in which the boundary between assistance and authorship is blurred. The bibliometric evidence of rising impact and expanding themes suggests the field is actively reorienting itself toward these questions, and future bibliographic coupling maps are likely to show AI-related clusters growing alongside the traditional detection and education clusters.

For educators, the study offers a reference point for locating the most influential work on academic integrity interventions; for policymakers, it identifies the countries, journals and themes where evidence is strongest; and for researchers, it exposes both the crowded centres and the underexplored margins of the literature. The authors position the work as a valuable tool for understanding how plagiarism research has progressed and where it is likely to develop. Its deeper message may be the most important one: plagiarism is no longer just a disciplinary problem to be caught by software, but a legitimate object of scientific inquiry, one whose study is now organised, measurable and growing. As long as the incentives of academic publishing reward volume and novelty, the demand for rigorous research on why people plagiarise, how to detect it, and how to prevent it will only intensify, and maps like this one will be essential for navigating the terrain.

Subject of Research: Bibliometric mapping of the global plagiarism research literature

Article Title: Mapping the intellectual terrain of plagiarism research: a bibliometric deep dive of academia reputed publishers

Article References: Sofi, I. A., Lone, Y. R., Ayub, T., & Ganaie, S. A. (2026). Mapping the intellectual terrain of plagiarism research: a bibliometric deep dive of academia reputed publishers. SN Social Sciences, 6(9), Article 384. https://doi.org/10.1007/s43545-026-01684-2

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01684-2

Keywords: plagiarism, bibliometrics, scientometrics, Biblioshiny, VOSviewer, Web of Science, academic integrity, research ethics, higher education, open access, generative AI, research misconduct

The study, conducted by Abroto Abroto, Maemonah Maemonah, and Imam Machali of Sunan Kalijaga State Islamic University in Yogyakarta, Indonesia, analyzed 547 peer-reviewed journal articles indexed in the Scopus database between 2018 and 2025. Using a rigorous screening process modeled on the PRISMA framework, the researchers began with 1,366 records and filtered them down to journal articles published in English, removing duplicates and conference papers along the way. They then applied performance analysis and science mapping techniques with the VOSviewer software, tracing collaboration networks, co-citation patterns, and keyword co-occurrences to reconstruct the intellectual architecture of a field that barely existed less than a decade ago.

The headline finding is growth. In 2018, only 23 articles on AI in primary education appeared in the database. By 2025, that figure had climbed to 132, the peak of an exponential curve that shows no sign of flattening. The corpus involved 1,876 distinct authors, an average of 3.7 researchers per paper, and stretched across 27 subject areas. Social sciences led the way with 429 articles, or 41.7 percent of the total, followed by computer science at 18.9 percent and psychology at 6.2 percent. That distribution alone tells a story: this is a field born at the intersection of pedagogy and technology, but one that is still searching for a disciplinary home.

Perhaps the most striking structural insight comes from the journals themselves. Of the 293 outlets that published at least one relevant article, nearly 69 percent published only a single paper on the topic. Just 16 journals, about 5.5 percent, published five or more. The field, in other words, is scattered across a vast landscape of periodicals, with only a small core of specialized venues. Among these, Computers and Education stood out as the most influential, amassing 914 citations, an H-index of 12, and elite bibliometric scores, while Sustainability published the largest raw number of articles. Most of the leading journals carried Q1 rankings, suggesting that despite its youth, the research is flowing disproportionately through high-impact channels.

Geographically, the map is strikingly lopsided. Spain dominates both productivity and citation impact, with the Universidad de Sevilla topping the institutional table at six publications, followed by the Universitat de València, Abai Kazakh National Pedagogical University, the Universidad de Granada, and the Universidad de Murcia. Not a single institution from North America, Africa, or most of the developing world appears among the top ten. Yet 111 countries contributed to the literature overall, with emerging contributors such as Indonesia and Taiwan gaining ground. The authors attribute the imbalance to disparities in research capacity, funding, and policy priorities, and warn that it raises uncomfortable questions about whose classrooms the current evidence base actually describes.

Individual researchers tell a similar story of concentrated influence. Raúl Cózar-Gutiérrez and José Antonio González-Calero of Spain emerged as the most productive authors, each with seven articles and 182 citations, while Tebogo Moloi and Dare Mhlanga topped the global citation rankings with 283 citations from a single collaborative paper. The lesson, the study notes, is that influence in this field is driven less by volume than by a handful of exceptionally resonant contributions, many of which focus on teacher readiness and the pedagogical implications of AI in primary contexts.

The thematic analysis is where the study delivers its most consequential findings. Keyword co-occurrence mapping of 1,669 unique author keywords revealed three major clusters. The first, centered on educational technology, teacher training, and digital competence, represents the institutional and pedagogical foundations of the field. The second groups artificial intelligence with augmented reality, e-learning, and computer-aided instruction, capturing the push toward intelligent, immersive, and personalized learning systems. The third, a green cluster of humanistic and developmental themes including curriculum, learning, and child development, sits conspicuously at the periphery of the network. Even more telling is what is missing: keywords related to ethics, data privacy, child protection, algorithmic bias, and students’ psychological well-being are largely absent from the dominant thematic structure altogether.

The longitudinal analysis deepens that concern. Between 2018 and 2020, research focused on general digital technology integration, with AI barely visible as a standalone concept. From 2021 to 2022, a transitional phase shaped partly by the COVID-19 pandemic’s forced digitization, themes multiplied and attention shifted to institutional adaptation and teacher readiness. Since 2023, the field has consolidated dramatically, narrowing to a handful of concentrated themes: artificial intelligence, personalized learning, and assessment. That convergence signals maturity and an application-oriented agenda, but the authors caution that it also reflects a field racing toward implementation while ethical and regulatory frameworks lag far behind, a pattern the pandemic era already demonstrated can accelerate adoption without building safeguards.

Why does this gap matter so much for primary education specifically? Young children are uniquely vulnerable to the risks that AI systems introduce: their data privacy can be compromised before they can understand what data is, algorithmic decisions can shape their learning opportunities in ways they cannot contest, and heavy reliance on digital tools may affect developing attention, social skills, and motivation. The study argues that effective AI integration at this level remains fundamentally teacher-mediated, and that professional development must therefore extend beyond technical training to instructional design, critical evaluation of AI-supported learning, and responsible data practices. Policy, meanwhile, needs clear guidelines on privacy, transparency, equity, and child protection before deployment, not after problems emerge.

The researchers are candid about their limitations, noting that reliance on a single database, the exclusion of conference literature, and the absence of local citation analysis all constrain the picture, and that fast-moving developments like generative AI and large language models may not yet be fully captured in the index. Still, their conclusions are hard to dismiss. AI in primary education has completed a remarkable journey from peripheral curiosity to consolidated research domain in under a decade, but it has done so while treating the children at its center largely as subjects of effectiveness studies rather than as developing humans whose rights, well-being, and long-term futures deserve equal scientific scrutiny. The next phase of the field, the authors suggest, must be built on ethically grounded, pedagogically informed, and developmentally appropriate foundations, because the stakes of getting it wrong are measured not in citation counts but in childhoods.

Subject of Research: Bibliometric mapping of artificial intelligence research trends in primary education

Article Title: Mapping artificial intelligence research in primary education: a bibliometric study

Article References: Abroto, A., Maemonah, M., & Machali, I. (2026). Mapping artificial intelligence research in primary education: a bibliometric study. Discover Education, 5(1), Article 824. https://doi.org/10.1007/s44217-026-02012-9

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02012-9

Keywords: artificial intelligence, primary education, bibliometrics, personalized learning, educational technology, ethics, child development, teacher training, VOSviewer, Scopus, thematic evolution, data privacy

The technical machinery behind the study is worth understanding, because bibliometrics is a discipline with its own rigor. The authors conducted a scientometric analysis using standardized search strategies across two of the largest biomedical literature databases, then applied PRISMA-style screening principles to isolate publications genuinely relevant to traditional and complementary medicine in cancer supportive care. For the mapping and visualization work, they used VOSviewer, a widely adopted software tool that constructs networks from bibliographic data and clusters them algorithmically. Co-authorship networks revealed patterns of collaboration between researchers and institutions; country-level analysis exposed the geography of output and citation; keyword co-occurrence mapping grouped the vocabulary of thousands of abstracts into thematic clusters; and citation structure analysis identified which works the field treats as foundational. Each of these lenses captures a different dimension of scientific activity, and together they turn an undifferentiated pile of nearly six thousand papers into an interpretable map.

The temporal trends tell a clear story of acceleration. Research output showed only modest growth during the early 2000s, a period when complementary medicine was still largely treated with skepticism in mainstream oncology journals. After 2010, the field entered a phase of sustained expansion, and the peak of activity arrived between 2020 and 2024. That late surge coincides with several converging forces: the maturation of integrative oncology as a recognized subspecialty, the publication of clinical practice guidelines endorsing evidence-based integrative therapies during and after breast cancer treatment by the Society for Integrative Oncology and their endorsement by the American Society of Clinical Oncology, and the World Health Organization’s escalating institutional commitment to traditional medicine, including its global traditional medicine centre and the Global Traditional Medicine Strategy 2025–2034. The pandemic years also intensified interest in supportive care broadly, as clinicians confronted the symptom burden of patients who could not easily access conventional services.

Geographically, the analysis confirmed what many observers suspected but had never quantified at this scale. The United States emerged as the dominant contributor across every metric examined: publication volume, citation impact, and international collaboration. China and the United Kingdom followed as the next most influential producers. This concentration matters because the modalities under study, from Traditional Chinese Medicine and Ayurveda to Unani, Kampo, Jamu, traditional Korean medicine, naturopathy, and anthroposophic medicine, are rooted in regions and health systems that do not map neatly onto the Anglo-American research establishment. The authors found that collaboration networks were globally distributed but regionally concentrated, with limited cross-regional integration. In practical terms, Asian research communities studying traditional medicine systems often publish and collaborate within their own regional clusters, while North American and European groups form largely separate networks, and the bridges between them remain thin.

The thematic analysis may be the most revealing part of the study. Keyword clustering showed a strong patient-centered orientation across the literature, with quality of life, symptom management, and supportive care outcomes forming the gravitational center of the field. This is a significant departure from earlier eras of complementary medicine research, which often fixated on whether herbal preparations could shrink tumors or extend survival, questions where the evidence remained weak and controversy ran high. The modern literature instead asks how these modalities help patients live better through treatment: managing cancer-related fatigue, chemotherapy-induced nausea, pain, anxiety, sleep disturbance, and the diffuse distress of survivorship. The keyword clusters also highlighted the growing embedding of traditional and complementary medicine modalities within the framework of integrative oncology, where they are studied as adjuncts to, rather than alternatives for, conventional treatment.

Why does this shift toward patient-centered outcomes matter scientifically? Part of the answer lies in the epidemiology of cancer itself. Global cancer statistics from the GLOBOCAN 2022 estimates document tens of millions of new cases annually across 185 countries, and as survival improves, the population of people living with and beyond cancer grows correspondingly. Surveys reviewed in the study’s supporting literature indicate that a substantial proportion of cancer patients use complementary and alternative medicine, with meta-analytic evidence showing especially high prevalence in Asian countries and documented decade-over-decade increases in places like Jordan. When large numbers of patients are already using these therapies, often without telling their oncologists, the scientific and clinical imperative becomes harm reduction and evidence-informed integration rather than prohibition. Quality of life data themselves carry prognostic weight, with prior literature linking quality of life measures to survival outcomes, which gives symptom-focused research a legitimacy that extends beyond comfort alone.

The study’s authors were candid about the field’s weaknesses, and their conclusions read as both a progress report and a warning. Fragmented collaboration networks mean that findings generated in one region may not be replicated, critiqued, or even noticed in another, slowing the accumulation of reliable evidence. Uneven geographic representation raises the possibility that traditional medicine systems with deep regional roots, such as the AYUSH systems of India or the herbal traditions of Indonesia and Japan, are underrepresented in the high-impact literature relative to their actual clinical use. Methodological variability is perhaps the most consequential problem: when studies of acupuncture, herbal medicine, yoga, or mind-body interventions use inconsistent outcome measures, comparator arms, and quality standards, systematic reviewers and guideline developers struggle to synthesize the evidence into clinical recommendations. The authors explicitly call for stronger international collaboration and well-designed clinical studies to support the evidence-informed integration of traditional and complementary medicine within supportive oncology.

There is also a structural dimension to the findings that extends beyond medicine into science policy. The acknowledgment section of the paper credits the library of the Central Council for Research in Ayurvedic Sciences under India’s Ministry of AYUSH, a detail that illustrates how national governments are now investing institutional resources in traditional medicine research infrastructure. The WHO’s strategy documents signal that this is a coordinated global project, not a fringe movement. For bibliometricians, the study demonstrates the continuing utility of network visualization tools like VOSviewer for auditing an entire field’s health, identifying orphan topics that lack attention, and exposing collaboration gaps that funding agencies could target. For clinicians, it offers reassurance that the literature they might consult on supportive care is growing rapidly, alongside a caution that its geographic and methodological foundations remain uneven.

The broader takeaway is that traditional and complementary medicine in cancer care has crossed a threshold. What was once a scattered collection of small studies, often published in specialized journals and read by a self-selected audience, has become a substantial, measurable, and internationally active research domain with a defined patient-centered agenda. The 5,770 publications analyzed here represent twenty-five years of accumulating effort to ease the symptom burden of cancer treatment using every tool available, from ginger’s well-documented anti-nausea pharmacology to structured mind-body programs. Whether the next decade of that effort produces the rigorous, cross-regional, methodologically consistent evidence base that the field’s own mapping says it needs will depend on whether researchers in Boston, Beijing, London, and Patiala can finally start reading, citing, and building on each other’s work.

Subject of Research: Bibliometric mapping of global research trends in traditional and complementary medicine for cancer supportive care

Article Title: Global research trends in traditional and complementary medicine for cancer supportive care: a bibliometric analysis (2000–2025)

Article References: Gajarmal, A., S., M., & Baheti, S. (2026). Global research trends in traditional and complementary medicine for cancer supportive care: a bibliometric analysis (2000–2025). Supportive Care in Cancer, 34(10), Article 958. https://doi.org/10.1007/s00520-026-11207-7

Image Credits: AI Generated

DOI: 10.1007/s00520-026-11207-7

Keywords: traditional and complementary medicine, cancer supportive care, integrative oncology, bibliometric analysis, quality of life, symptom management, VOSviewer, PubMed, Scopus, international collaboration, Traditional Chinese Medicine, Ayurveda

The research team scoured the Scopus database, one of the largest curated indexes of peer-reviewed literature, for publications on refugee and forced displacement issues in Southeast Asia published between 1975 and 2025. Using a structured search strategy paired with an explicit screening protocol against pre-defined inclusion and exclusion criteria, the authors filtered out records that were only peripherally related to the topic. The final corpus comprised 1,110 publications, a dataset spanning half a century of scholarship on asylum seekers, internally displaced persons, and stateless populations. The analysis was conducted using a combination of bibliometric software: BiblioMagika for data processing, OpenRefine for cleaning and standardising records, and VOSviewer for constructing and visualising co-occurrence networks of author keywords.

Bibliometric analysis is a quantitative science-mapping technique that treats publications, citations, and keywords as data points rather than reading their content in depth. Performance indicators, such as annual publication counts, citation totals, and the productivity of individual authors and countries, describe the volume and impact of a field. Co-occurrence mapping, by contrast, reveals its conceptual anatomy: when two keywords appear together in the same article more often than chance would predict, they are drawn closer together in a network diagram, and dense clusters of connected terms expose the thematic pillars around which a discipline organises itself. This dual approach allowed the researchers to chart both the growth trajectory of Southeast Asian refugee scholarship and the intellectual architecture underpinning it.

The headline finding concerns timing. Publication output remained modest for decades but rose markedly from the 2010s onward, a surge that coincides with the intensifying international visibility of the Rohingya crisis after 2012, when sectarian violence in Rakhine State triggered renewed displacement and drew sustained global media attention. The authors are careful about what this correlation means. Because their data are descriptive, they interpret the association as suggestive rather than causal; the analysis cannot demonstrate that the Rohingya emergency itself drove the increase in publications, only that the two trends unfolded in parallel. Even so, the pattern is striking: a humanitarian catastrophe that unfolded largely within the region appears to have been accompanied by an expansion of the academic literature documenting and analysing displacement.

Equally revealing is what the performance indicators show about who produces this knowledge. Research output is concentrated among a limited group of author affiliations and contributing countries, indicating uneven participation in the indexed literature. This concentration matters for reasons that go beyond bibliometric curiosity. Scholarship on displacement is often produced by institutions far from the displacement itself, and the new study’s evidence of a narrow base of productive affiliations raises familiar questions about whose perspectives shape the research agenda, who has access to publication channels, and how the priorities of international journals interact with the concerns of local communities, host governments, and displaced people themselves.

The thematic mapping is where the study delivers its richest technical contribution. Aggregate author-keyword co-occurrence analysis identified nine coexisting thematic areas. The first cluster concerns refugee health and trauma, a lineage that stretches back to some of the earliest and most highly cited works in the corpus, including studies of trauma and survival among Burmese political dissidents in Thailand published in the mid-1990s and research on the functional health of Cambodians living in border camps. A second cluster addresses Rohingya statelessness and rights, while a third examines legal precarity and access to health services, reflecting the peculiar limbo in which most refugees in Southeast Asia live, since many states in the region are not parties to the 1951 Refugee Convention or its 1967 Protocol.

The remaining clusters extend the map across the full breadth of the displacement experience. One area covers asylum governance in the maritime corridor, evoking the irregular boat movements through the Andaman Sea and the policy responses they provoke. Another addresses camp-based displacement and identity, drawing on decades of research along the Thailand-Myanmar border. A sixth cluster concerns internal displacement, conflict, and disasters, encompassing both war-driven displacement and the upheaval caused by events such as the Aceh tsunami. Two further areas focus on women, children, and reproductive health, including studies of menstrual hygiene management challenges facing displaced girls and women, and on the international protection architecture itself, including legal scholarship on how politics shaped the outcome of the 1967 Protocol. The ninth cluster examines protracted displacement and education, including barriers to higher education faced by Burmese refugees in Thailand.

Together, these clusters suggest clear priorities for future research. The authors argue that the patterns point toward comparative studies that span multiple countries and displacement contexts, longitudinal designs that track displaced populations and policy changes over time, and greater methodological diversity across the field. They are equally candid about the limits of their own analysis: the keyword co-occurrence data do not establish how themes changed over time, and studies that fall below the keyword occurrence threshold are invisible to the network. The reliance on a single database, Scopus, also means that grey literature, non-English publications, and work in regional journals not indexed by Scopus remain outside the picture, a constraint the authors acknowledge given licensing restrictions that prevent public sharing of the raw bibliographic records.

The timing of this mapping exercise could hardly be more consequential. UNHCR’s Global Trends reporting continues to document record levels of forced displacement worldwide, and Southeast Asia remains both a source and a destination region for people fleeing persecution, conflict, and disaster. Recent legal scholarship, cited in the study, analyses Thailand’s national screening mechanism as a case of partial acculturation to international refugee law, illustrating how host states in the region are incrementally, and unevenly, building domestic structures for managing asylum. A consolidated evidence base of the kind this study provides gives policymakers, humanitarian agencies, and researchers a shared map of what is known, and just as importantly, of where the gaps lie.

What makes the study notable within bibliometrics itself is its methodological transparency. The authors describe a structured search strategy, an explicit screening protocol, and a documented pipeline through BiblioMagika, OpenRefine, and VOSviewer, with derived datasets available from the corresponding author upon reasonable request. No custom code was developed, and the study involved no human participants, requiring no ethical approval. By systematically mapping the knowledge structure of refugee and forced displacement scholarship in Southeast Asia, the team has converted five decades of scattered publications into an organised intellectual geography, one that future studies of regional migration governance and protection regimes can navigate, interrogate, and extend as the forces that displace people across the region continue to evolve.

Subject of Research: Bibliometric mapping of refugee and forced displacement research in Southeast Asia from 1975 to 2025

Article Title: Refugee and forced displacement research in Southeast Asia (1975–2025): a bibliometric analysis of trends and future directions

Article References: Muis, A. M. R. A., Hajimin, M. N. H. H., & Paulus, A. A. (2026). Refugee and forced displacement research in Southeast Asia (1975–2025): a bibliometric analysis of trends and future directions. SN Social Sciences, 6(10), Article 542. https://doi.org/10.1007/s43545-026-01855-1

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01855-1

Keywords: refugee studies, forced displacement, Southeast Asia, bibliometric analysis, Rohingya, statelessness, internal displacement, asylum governance, refugee health, VOSviewer, Scopus, migration governance

The scale of the analysis required a rigorous screening pipeline. The researchers began with 2,359 records retrieved from Scopus on December 27, 2025, using a query that matched the terms artificial intelligence or AI against inclusive education in titles, keywords and abstracts. Filtering to the 2021–2025 window left 2,286 documents, restricting the language to English reduced the pool to 2,246, and manual screening for topical relevance ultimately retained 1,655 documents. The final corpus spanned six document types: 542 journal articles, 454 conference papers, 449 book chapters, 105 reviews, 83 books and 22 conference reviews. Scopus was chosen deliberately, the authors note, because it offers roughly 20 percent greater citation coverage than Web of Science, making it well suited to mapping a young, fast-moving, multidisciplinary field.

Two complementary software tools powered the analysis. Bibliometrix, an R package built for quantitative science mapping, was used to identify the most relevant authors, institutional affiliations, corresponding-author countries and most-cited nations. VOSviewer, a free network-visualization program, was deployed to chart bibliographic coupling among sources, countries and authors, revealing the hidden intellectual architecture of the field. Together, the tools allowed the team to move beyond simple publication counts and reconstruct how ideas, citations and collaborations flow through the research landscape of AI for inclusive education.

Citation analysis identified the field’s intellectual anchors. The most highly cited work, by Chen and colleagues on AI student assistants and chatbot design for classroom success, accumulated 431 citations, while Southworth and colleagues’ framework for embedding AI literacy across higher education curricula followed with 389. The most-cited studies clustered around a recognizable set of themes: AI literacy, adaptive learning systems, generative artificial intelligence, chatbot-assisted learning, personalized learning environments, ethical governance and institutional policy frameworks. Since 2023, the authors found, academic curiosity has pivoted sharply toward generative AI, with ChatGPT and large language models dominating the high-citation literature and raising parallel questions about assessment, curriculum design and responsible use.

The subject-area breakdown underscores how fundamentally interdisciplinary this field has become. Computer Science leads with approximately 26.6 percent of publications, followed closely by Social Science at 25.6 percent, a pairing the authors read as evidence that technological development and pedagogical, equity-oriented perspectives are advancing in tandem. Engineering contributes 9.9 percent, while Business, Management and Accounting (4.9 percent), Mathematics (4.8 percent) and Medicine (4.2 percent) add moderate but meaningful weight. Smaller shares come from Arts and Humanities, Economics, Decision Sciences and Psychology, with other fields accounting for 12.2 percent. No single discipline owns the topic, and the authors argue that successful real-world implementation will demand coordinated effort across all of them.

Geographically, the field is strikingly concentrated. The United States, India and China emerged as the leading producers, with India and the United States each contributing around 580 and 566 documents respectively, followed by Indonesia with 204 and China with 201. The United States also dominates citation impact with 1,892 citations, ahead of China with 667 and the United Kingdom with 602. At the institutional level, Inti International University tops the list with 16 publications, followed by King Faisal University with 11, while Qatar University, the University of California and the University of Florida contributed nine each. On authorship, Asrifan A leads with 12 articles, most of them published in 2025, with Bozkurt A, Chen Y, Li J and Gupta S tied at eight publications each.

Bibliographic coupling networks added a structural dimension to these rankings. Source-level analysis revealed five clusters, with Lecture Notes in Computer Science showing the highest link strength at 119, followed by Frontiers in Education at 73 and the International Journal of Learning, Teaching and Educational Research at 69. Country-level coupling produced six clusters, with the United States again leading at 4,897 link strengths across 300 documents, followed by India at 4,644 and the United Kingdom at 2,746. Author-level networks formed three main clusters, anchored respectively by Asrifan, Acosta-Vargas and Compitiello; Dimitriadis and Laverde; and Roe, Al Shahrani and Jemni. Asrifan recorded the highest individual link strength at 198, with Bozkurt close behind at 177 alongside 102 citations.

Beneath the growth curves, the study exposes significant gaps. The most-cited research disproportionately targets higher education, universities, undergraduate learners and institutional policy, while disability-centered inclusive education, school-level settings and primary learners receive comparatively little attention. Geographically, technologically advanced nations dominate the citation landscape while developing regions remain underexplored. Long-term instructional analyses are scarce, with most studies examining only short-term learner engagement, and socio-cultural impacts of AI integration remain inadequately investigated. The authors also observe a shift in the field’s center of gravity: from performance-focused adaptation toward equity-centered adaptation, echoing the United Nations Sustainable Development Goal 4 on quality education, though they caution that inclusion-related themes are still unevenly integrated across research clusters.

The study’s limitations deserve equal attention. It relies solely on Scopus, excluding relevant work indexed in Web of Science, ERIC, Google Scholar and regional databases. Only English-language publications were included, omitting meaningful contributions from non-English-speaking contexts. The 2021–2025 window cannot capture foundational earlier work, and bibliometric methods inherently privilege quantity and citation popularity over qualitative depth, meaning highly cited studies are not always the highest quality. Narrow search terms built around artificial intelligence, AI and inclusive education may also have missed related literature using alternative vocabulary, and rapidly evolving recent developments may not yet appear in citation databases.

For educators, researchers and policymakers, the message is clear. Generative AI tools, chatbots, intelligent tutoring systems and adaptive learning platforms hold genuine potential to personalize instruction, boost engagement and widen access for learners with diverse needs and abilities. But realizing that potential, the authors conclude, depends on pedagogical design, teacher involvement and theoretical grounding in equity and participation rather than technology alone. They call for system-wide AI literacy frameworks, adaptive governance structures addressing ethics, assessment integrity and data protection, and sustained investment in digital infrastructure so that AI-assisted pedagogies complement rather than replace human teaching. As publication output continues its steep climb, the field’s challenge is no longer generating interest in AI for inclusive education, but ensuring that interest translates into fair, ethical and globally balanced practice.

Subject of Research: Bibliometric analysis of global research trends in artificial intelligence for inclusive education from 2021 to 2025

Article Title: A bibliometric study of publication trends and intellectual structure in artificial intelligence for inclusive education

Article References: Baro, K., Das, B., Basumatary, S., & Mochahary, D. (2026). A bibliometric study of publication trends and intellectual structure in artificial intelligence for inclusive education. Discover Education, 5(1), Article 995. https://doi.org/10.1007/s44217-026-01794-2

Image Credits: AI Generated

DOI: 10.1007/s44217-026-01794-2

Keywords: artificial intelligence, inclusive education, bibliometrics, generative AI, adaptive learning, chatbots, personalized learning, AI literacy, Scopus, VOSviewer, educational technology, research trends

The study, led by Smail Kannaoui of Ibn Tofail University in Morocco together with colleagues at the Regional Center for Teaching and Training Professions in Rabat, followed the PRISMA 2020 reporting standards and used the network visualization software VOSviewer to construct keyword co-occurrence networks, country collaboration maps, and journal co-citation graphs. The researchers began with a raw Scopus search that returned 10,259 records, then applied automatic filters for publication year, document type, source type, language, open access status, and subject area, reducing the set to 779 records. Every remaining record was screened by title and abstract to confirm genuine relevance to biology, geology, environmental science, or life and earth sciences education. The decision to restrict the corpus to open-access publications was deliberate: it ensured that all analyzed full texts were freely verifiable by any reader, though the authors acknowledge that this may have excluded relevant subscription-based research.

The publication curve tells a striking story. After a slow start, annual output reached 40 papers before nearly doubling to 75 in 2023. Then came explosive growth: 207 publications in 2024 and 378 in 2025, the two most productive years in the entire dataset. The authors are careful to note that a bibliometric design cannot establish a causal link, but the timing of the acceleration, coinciding with the widespread emergence of generative AI tools such as ChatGPT, is consistent with a broader reorientation of research priorities toward generative AI across the discipline. They also flag a cautionary note: growth this rapid raises questions about sustainability and about the risk of a trend effect that could influence the quality and depth of contributions.

Geographically, the field is dominated by the United States, which produced 168 documents, roughly 28.2 percent of the cumulative output of the top ten countries. The United Kingdom follows with 64 papers and China with 56. Spanish-speaking and German-speaking countries contributed 48 and 43 documents respectively, while Turkey and Australia published 38 and 37. India, Saudi Arabia, and Malaysia round out the top ten with 31, 26, and 25 publications, a significant presence of South Asian and Middle Eastern institutions in the research domain. The co-authorship network places the United States at an extremely central position with strong connections to many other countries, and Germany occupies a clear intermediary role within Europe. The clustering pattern reveals distinct geographic groupings, including a Middle Eastern-Asian cluster of Saudi Arabia, Turkey, Jordan, and South Korea; a European-Latin American cluster spanning Spain, Italy, Brazil, Mexico, and Colombia; and a Southeast Asian cluster of Malaysia and Indonesia.

Funding data reinforce the picture of American leadership. The National Science Foundation tops the list of sponsors with 16 funded publications, followed by the National Natural Science Foundation of China with 10. Three organizations funded eight articles each: Germany’s Federal Ministry of Education and Research, Taiwan’s Ministry of Science and Technology, and the National Institutes of Health. The United Kingdom Research and Innovation funded seven papers, while the European Commission and Tecnológico de Estudios Superiores each accounted for six. At the institutional level, Tecnológico de Monterrey in Mexico leads with 10 publications, followed by the University of Johannesburg, the University of Hong Kong, the University of Oulu, and the University of Georgia with nine each, and Stanford University, Carnegie Mellon University, the Chinese University of Hong Kong, Sultan Qaboos University, and University College London with eight apiece.

The disciplinary distribution shows a field that is multidisciplinary but uneven. Social Sciences account for the largest share of publications at 45.9 percent, reflecting the educational and societal dimensions of the research, while Computer Science contributes 15.5 percent, representing its technological side. Together the two fields make up 61.4 percent of the corpus. Environmental Science follows at 5.0 percent, then Psychology at 4.7 percent, Engineering at 4.2 percent, and Medicine at 4.0 percent. At the journal level, Computers and Education: Artificial Intelligence, published by Elsevier, stands out for influence, contributing 22 articles to the corpus in 2025 alone, while Sustainability, published by MDPI, ranks first among the top sources in overall productivity and citation totals across its entire multidisciplinary output. The authors caution that this editorial concentration on a few dissemination channels could signal an emerging structuring of the field with a narrow base.

Individual researchers also show a concentration of influence. Dragan Gašević of Monash University in Australia ranks as the most prolific author with 700 articles, 24,733 citations, and an h-index of 77. Kenneth R. Koedinger follows with 412 publications and an h-index of 70, and Sanna Järvelä of the University of Oulu has 240 publications, 13,464 citations, and an h-index of 62. The authors interpret these figures as evidence that a core group of highly experienced scholars anchors the field, even as newer contributors from emerging academic contexts, particularly developing countries, join the conversation. They note, however, that citation-based indicators are time-dependent and may favor older publications and established researchers, so comparisons should be read as indicative rather than definitive.

Perhaps the most consequential finding lies in the thematic structure. Keyword co-occurrence analysis with a minimum threshold of five occurrences produced five clusters. The largest, containing 428 keywords or 54.9 percent, centers on AI tools and generative technology, including machine learning and large language models. The second, with 133 keywords, focuses on teaching, learning, and higher education. But the third cluster, dedicated to science education and biology and geology specifically, contains only 40 keywords, or 5.1 percent, and sits isolated from the dominant AI cluster. This separation, the authors argue, demonstrates that there has been limited integration of generative AI into science teaching, and it constitutes the study’s core original contribution: a systematic disciplinary gap. Life and earth sciences differ epistemologically from general science subjects because they rest on observational methods, field study, practical experiments, ecology, and geologic time scales, all of which pose unique teaching challenges that demand discipline-specific AI solutions rather than generic ones.

The temporal overlay analysis sharpens this narrative into a five-stage trajectory. Early keywords such as machine learning, deep learning, and e-learning cluster around 2023.4 in average publication year, while newer terms including generative AI, large language model, AI literacy, academic integrity, and ChatGPT gather around 2024.7 to 2024.9, showing how completely the research agenda has pivoted since ChatGPT appeared in late 2022. Bibliographic coupling confirms the same arc: a foundational phase from 2015 to 2020, a growth phase of machine learning and e-learning from 2021 to 2022, a transition to generative AI in 2023, a dense ChatGPT-era cluster in 2024 marked by rapid idea exchange among research groups, and an emerging 2025 cluster devoted to AI literacy and ethics. That final cluster, smallest but strategically vital, signals a shift from asking how AI can be implemented to asking when and under what circumstances it should be, a question that carries special weight in the life sciences, where truthfulness, verifiability, and scrutiny of evidence are foundational epistemological values that careless use of generative AI could undermine.

The authors draw three principal implications from their mapping. First, discipline-specific empirical studies are needed, including longitudinal research on how AI-based instruction affects learning outcomes in biology, geology, and environmental sciences, moving beyond the prevailing higher-education orientation of the literature. Second, life and earth sciences teachers need training that goes beyond operational competence to include evaluating AI-generated content against scientific evidence standards, since prior work has shown that teacher acceptance of AI depends on self-efficacy, anxiety, and perceived usefulness, and that adoption varies markedly across scientific fields. Third, the lack of collaboration between AI experts, science educators, and cognitive psychologists represents a structural deficit that funders and journal editors should consciously address. The study has limitations worth noting: it draws on a single database, Scopus, and restricts itself to open-access and English-language materials, which may narrow its geographic and linguistic scope and exclude valuable work in Arabic, French, or Spanish. Still, as a first systematic map of AI in life and earth sciences education, the analysis makes one thing clear: a rapidly expanding, generative-AI-centered research field is racing ahead, while the disciplines that study life itself, and the deep time of the Earth, are still waiting for their turn.

Subject of Research: Bibliometric analysis of artificial intelligence research trends in life and earth sciences education from 2015 to 2025

Article Title: Artificial intelligence in science education with a focus on life and earth sciences a bibliometric analysis of global research trends from 2015 to 2025

Article References: Kannaoui, S., Elwahab, F., El Houda Derkaoui, N., Brhadda, N., Loukili, A., & Ziri, R. (2026). Artificial intelligence in science education with a focus on life and earth sciences a bibliometric analysis of global research trends from 2015 to 2025. Discover Education, 5(1), Article 1002. https://doi.org/10.1007/s44217-026-02208-z

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02208-z

Keywords: artificial intelligence, science education, bibliometrics, biology education, geology education, generative AI, ChatGPT, large language models, AI literacy, Scopus, VOSviewer, research trends

The methodological backbone of the study is the PRISMA protocol, the standardized reporting framework that governs systematic reviews in health and social science research. PRISMA requires researchers to define explicit search strategies, apply transparent inclusion and exclusion criteria, and document every step by which a large pool of candidate records is narrowed to a final analytic sample. Following this discipline, Tiwari and Kumari identified 303 publications spanning the period from 2013 to 2024. The choice of starting year is not arbitrary: 2013 follows closely on the heels of the Millennium Development Goals era and captures the period in which the international community was negotiating the successor framework that would become the SDGs, adopted in 2015. The corpus therefore reflects the intellectual build-up to, and the decade of implementation of, the current global development agenda.

To analyze the 303 papers, the authors turned to bibliometric science, a field that applies quantitative methods to the structure of scholarly communication. Their principal instrument was VOSviewer, a widely used software package for constructing and visualizing bibliometric networks. VOSviewer builds maps in which individual publications, keywords, or countries appear as nodes, and the strength of the relationships between them, whether through co-citation, keyword co-occurrence, or collaboration, determines their proximity. Clusters of densely connected nodes reveal thematic communities that might otherwise remain invisible when the literature is scattered across economics, public health, education, management, agriculture, and engineering journals. The authors complemented these network visualizations with analyses in Excel, tracking publication counts over time and the geographic distribution of contributions.

The temporal picture that emerges is one of steady acceleration. Research output on women’s equity, inclusion, and the SDGs increased markedly after 2013, a trend the authors link to the growing policy salience of the gender goal as the 2030 deadline approaches. This is consistent with a broader pattern in sustainability science: as target dates near, funding bodies, governments, and journals channel attention toward the goals that remain furthest from achievement, and SDG 5 is widely regarded as one of the most off-track. The review suggests that the scholarly community has responded, though not uniformly across regions or disciplines.

Geographically, the analysis identified the United States, the United Kingdom, and India as the leading contributors to the literature. That trio is revealing. The two Anglophone powers reflect the concentration of research infrastructure, funding, and publication venues in the global North, while India’s prominence underscores both the scale of the gender challenges it faces and the strength of its social science research community. The authors’ finding that contributions are unevenly distributed echoes a persistent critique of development research: the countries where gender-based disparities are often most acute are frequently not the ones generating the bulk of the peer-reviewed evidence. Redressing that imbalance, the review implies, is itself a matter of research equity.

Thematically, the network analysis surfaced several distinct but interlocking clusters. Gender equality forms the conceptual core, surrounded by clusters on leadership, health, education, and socio-economic empowerment. The leadership cluster draws on a substantial corporate governance literature examining how women’s representation on boards and in senior management relates to firm performance and to environmental, social, and governance outcomes. Studies of Italian listed companies, for example, have probed the link between board diversity and sustainability disclosure, while work on small and medium-sized enterprises has asked whether women in management positions strengthen relational and environmental management practices. The consistent message of this strand is that diversity is not merely a compliance metric but a variable with measurable organizational consequences.

The health and education clusters tell a complementary story about human capital. Research on academic medicine has documented how institutions attempt to address gender disparities in recruitment, promotion, and retention, and how crises such as the COVID-19 pandemic threatened to reverse hard-won gains by disproportionately burdening women faculty. In education, studies range from interventions that break habitual gender bias in hiring of science faculty, to analyses of how schooling creates social change for lower-caste girls in rural India, to programs like Girls4STEM that aim to widen the pipeline into science, technology, engineering, and mathematics careers. A related body of work examines counterspaces, the supportive environments that help women of color persist in STEM higher education despite marginalization. Together these studies frame gender equity in education not as a standalone concern but as a prerequisite for the skilled, diverse workforce that sustainable development requires.

The socio-economic empowerment cluster extends the analysis into agriculture, finance, and entrepreneurship, domains where the SDGs’ ambitions meet everyday livelihoods. Field studies from Kenya have asked whether there are systematic gender differences in the adoption of sustainable agricultural intensification practices, while research from Malawi and Tanzania has documented the discriminatory effects of gender disparities in access to improved seeds and fertilizer at the plot level. A feminist political ecology perspective applied to wheat farming in Morocco and Uzbekistan shows how innovation systems themselves can embed gendered power relations. On the financial side, recent work examines whether digital financial services can deliver the autonomy and equality promised under SDG 5, a question of growing urgency as mobile money spreads across the developing world. Entrepreneurship research, including prior bibliometric analyses of women’s entrepreneurship in the SDG framework, positions women-led enterprises as engines of both income generation and community-level change.

What unifies these clusters, the review argues, is their interconnectedness in the architecture of the SDGs. Gender equality is not merely one goal among seventeen; it functions as a cross-cutting enabler whose achievement conditions progress on poverty reduction, health, education, decent work, and reduced inequalities. Earlier scholarship, including Nobel laureate Esther Duflo’s influential analysis of the two-way relationship between women’s empowerment and economic development, and Naila Kabeer’s critical work on the Millennium Development Goals, laid the conceptual groundwork for this view. The bibliometric evidence now shows that the research community has internalized it, with keyword networks binding empowerment, participation, and sustainability into a single conversation. The practical corollary, the authors emphasize, is that policies and programs must integrate gender perspectives deliberately, because doing so reduces disparities, enhances participation, and improves outcomes across education, health, and economic growth simultaneously.

The review also serves as a map of what remains unknown. By exposing the fragmentation of the literature across disciplines and regions, it identifies gaps that future studies should fill: stronger representation of research from the global South, deeper integration of the thematic clusters that bibliometrics reveals only as separate islands, and more work connecting micro-level interventions to macro-level SDG indicators. For policymakers, the message is that the evidence base for gender-inclusive sustainable development has matured enough to inform design, but remains uneven enough to demand investment. For researchers, the co-occurrence maps offer a starting point for collaboration across the very disciplinary boundaries that have kept the field disjointed. As the 2030 deadline looms, the study suggests that closing the gap between what is known about women’s contributions to sustainable development and what is done with that knowledge may be one of the most consequential tasks in the final stretch of the global goals.

Subject of Research: A bibliometric review of research on women's contributions to equity, inclusion, and the Sustainable Development Goals

Article Title: The role of women’s contributions to equity, inclusion, and Sustainable Development Goals: a bibliometric review

Article References: Tiwari, M., & Kumari, A. (2026). The role of women’s contributions to equity, inclusion, and Sustainable Development Goals: a bibliometric review. SN Social Sciences, 6(10), Article 441. https://doi.org/10.1007/s43545-026-01737-6

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01737-6

Keywords: gender equality, SDG 5, sustainable development goals, bibliometric analysis, women's empowerment, equity and inclusion, VOSviewer, PRISMA, STEM education, women in leadership, socio-economic empowerment, global health and education