The systematic search conducted for this dataset was rigorous, adhering to established guidelines for evidence synthesis in environmental management. The researchers utilized a transparent methodology outlined by the ROSES flow diagram for systematic maps, ensuring that the selection process was reproducible and unbiased. An online search was performed across six major databases, including Web of Science, Scopus, Agricola, AGRIS, Dimensions, and Livivo. The search strategy focused on English-language, peer-reviewed publications, using specific search strings that combined terms related to participatory or collaborative modelling with various agricultural contexts. This included a wide range of agricultural activities such as farming, cultivation, husbandry, viticulture, horticulture, and hydroponics, as well as specific crops like wheat, rye, oats, rice, and various livestock categories. The breadth of the search ensured that the dataset captured a diverse array of agricultural settings and modelling approaches.

The screening process involved multiple stages to ensure the quality and relevance of the included studies. Initially, duplicates were automatically removed using EndNote, followed by a manual screening of titles and abstracts in Rayyan. Researchers then downloaded the full texts of the remaining publications for a detailed review. This meticulous process resulted in the inclusion of 78 case studies, while 110 papers were filtered out during the full-text analysis, and 857 were excluded based on title and abstract screening. The inclusion criteria were strictly defined, focusing on methods and context to ensure that only studies genuinely employing participatory modelling methods in agri-environmental research were selected. This rigorous filtering process highlights the commitment to accuracy and relevance in the dataset, providing a reliable foundation for subsequent analysis.

The dataset itself is extensive, comprising an Excel spreadsheet with 58 columns of numeric and text data that describe each study in both qualitative and quantitative ways. Each of the 78 case studies is characterized by its main goals, the specific participatory modelling methods used, the stakeholders involved, and their contributions to the project. Additionally, the dataset includes key metadata such as publication type, year, study location, funding source, project duration, and outcomes beyond peer-reviewed publications. This level of detail allows for a nuanced understanding of the participatory modelling landscape, revealing patterns and associations that might otherwise remain hidden. The data also includes bibliographic information for each publication, facilitating further research and citation. The inclusion of metadata such as funding organizations and study duration provides valuable context for researchers and institutions aiming to expand their research portfolios or evaluate the feasibility of similar projects.

One of the key findings from the dataset is the identification of clusters and associations between different participatory modelling methods and their corresponding goals. The data reveals that certain methods are more dominant than others, and specific combinations of methods are frequently used to achieve particular project objectives. For instance, system dynamics, agent-based modelling, companion modelling, and causal loop diagramming are among the methods that are commonly stated in the publications. However, some methods, such as informing or contributing to a numerical model or numerical model prototyping, were derived from their descriptions in the publications rather than being explicitly named. This distinction is important for understanding the diversity of approaches used in participatory modelling and for identifying areas where further research is needed. The dataset also highlights the dominant role of researchers in this type of participatory research, suggesting that while stakeholders are involved, the direction and scope of the modelling process are often led by academic experts.

The dataset also points out the absence of participatory modelling in certain areas of agricultural production, such as hydroponic farming and viticulture. This gap in the literature suggests that these sectors may not be fully leveraging the benefits of participatory approaches, potentially missing out on opportunities for improved sustainability and stakeholder engagement. The findings have implications for researchers, institutions, and grant agencies, as they provide a clear picture of where participatory modelling is being applied and where it is not. For researchers, this information can guide future studies into underexplored areas, while for institutions, it can inform decisions about expanding their research capabilities. Grant agencies can use this data to evaluate the rigidity and relevance of research proposals involving participatory modelling, ensuring that funding is directed toward projects that address significant gaps in the field.

The value of the dataset extends beyond its immediate findings, as it provides a comprehensive foundation for the related research article and for future studies. The data can be analyzed both quantitatively and qualitatively, offering multiple avenues for exploration. For example, researchers can link methods, goals, and stakeholder involvement with other metadata to uncover new patterns and insights. The dataset also allows for comparisons between agri-environmental research and other areas, providing a broader context for understanding the role of participatory modelling in different fields. The inclusion of data not used in the related research article, such as the relationship between methods and stakeholder involvement, provides a basis for future research that can further refine and expand the understanding of participatory modelling in agri-environmental contexts.

Limitations of the dataset include the exclusion of grey literature and the potential for missing publications that mentioned specific participatory modelling methods in their titles, abstracts, or keywords but did not explicitly state that they applied a participatory modelling approach. The search strategy, which used umbrella terms like “participatory model*,” may have overlooked studies that employed specific methods without using these broader terms. Additionally, the dataset does not evaluate the success of the case studies or question the authors’ choice of methods, meaning that it does not provide a judgment on whether a particular method or set of methods is suited to achieve the goals of the studies they were used with. These limitations highlight the need for further research to validate the findings and to explore the effectiveness of different participatory modelling approaches in achieving their intended outcomes.

In conclusion, this systematic mapping dataset offers a valuable resource for understanding the use of participatory modelling methods in agri-environmental research. By providing a detailed overview of 78 case studies, the dataset reveals patterns in method usage, stakeholder involvement, and project goals, while also identifying gaps in the current literature. The findings have significant implications for researchers, institutions, and grant agencies, as they provide a clear picture of the current state of participatory modelling in the field and suggest areas for future exploration. As the field of agroecology living lab research continues to grow, this dataset will serve as a foundational tool for advancing the practice of participatory modelling and for promoting more inclusive and effective approaches to agri-environmental research.

Subject of Research: Systematic mapping of participatory modelling methods in agri-environmental research

Article Title: The Use of Participatory Modelling Methods in Agri-Environmental Research – A Systematic Mapping Dataset

Article References: Klemm, T. (2024). The Use of Participatory Modelling Methods in Agri-Environmental Research – A Systematic Mapping Dataset. One Ecosystem, 9, Article e133158. https://doi.org/10.3897/oneeco.9.e133158

Image Credits: AI Generated

DOI: 10.3897/oneeco.9.e133158

Keywords: participatory modelling, agri-environmental research, agroecology, systematic mapping, stakeholder engagement, transdisciplinary research, living labs, sustainable agriculture, modelling methods, research dataset, Participatory, Modelling

The consortium in question was assembled to investigate the upstream determinants of non-communicable disease in urban settings, drawing on 57 academic staff across six universities and spanning thirteen disciplinary areas grouped under the UK’s three main research councils: economic and social sciences, engineering and physical sciences, and medical research, plus a professional services team. From 2019 to 2025, a dedicated research-on-research sub-team conducted 63 semi-structured interviews with 39 consortium members in three rounds, timed in Years 2, 3 and 5 of the programme. Those transcripts, normally the raw material for slow, expert-led qualitative analysis, became the test bed for a very different kind of scrutiny.

The researchers adopted what they call a dual approach. The first strand used co-word clustering, an NLP technique that groups words appearing together across texts, to identify emergent themes in the full interview transcripts. The second strand was more targeted: the team built a dictionary of 245 tokens deemed to represent transdisciplinary language, extracted from foundational project documents including the peer-reviewed programme protocol, and then tracked how those words were used over time and across disciplinary boundaries. The dictionary was split into tokens describing the upstream problem under investigation, the mid-downstream built environment and health outcomes, and the research problem itself, that is, the challenge of actually running such a complex collaboration.

The co-word clustering produced eleven initial clusters, refined down to nine coherent themes, ranging from new large-scale research approaches for real-world problems to local government case studies, health and decision-making, mission and integration, shared understandings, project structure, and urban development systems. Yet despite the apparent richness of these themes, the technique yielded no clear findings about how transdisciplinary understanding developed. The authors are candid about this: the themes could be described and tentatively interpreted, but whether those interpretations were accurate or merely what they call wishful thinking remained uncertain, particularly given the low volume of data and the wide variation in the number of tokens within each cluster.

The vocabulary analysis told a far more compelling story. In the first interview round, almost half of the 245 transdisciplinary tokens were not used by any of the disciplinary groups, and most of the rest were used by only one, two or three of the four groups rather than all of them. Over the six years, however, a clear convergence emerged. Overall use of the transdisciplinary vocabulary declined, but the words that remained in circulation became more widely shared. By the end, 135 words were used by at least one discipline, 40 by all four, and the trajectory pointed towards a shared lexicon of roughly 15 to 25 percent of the original dictionary. In other words, the team did not adopt more jargon as it matured; it shed most of it, converging on a small set of useful, jargon-free terms.

The disciplinary breakdown added intriguing nuance. Economic and social scientists used the greatest diversity of transdisciplinary vocabulary in the first round, across by far the widest range of interviews, at 45 percent across 15 interviews, falling to 30 percent and then 23 percent in later rounds. Public health researchers used the second most, followed by engineers, with professional services staff using the least, and none at all in the first round. That ordering is striking because the engineers were arguably the group most familiar with the vocabulary from the outset, having led the systems science and research-on-research work. One explanation offered is that the engineers focused on process-oriented systems analysis rather than the wider research themes; another is that, being most fluent, they simply expressed the same ideas in different words.

Perhaps the most consequential finding is about time. It took the consortium essentially the full six years to develop its shared vocabulary, and the convergence accelerated only towards the end of that timeline. The authors note that the team once spent six months of considerable discussion simply agreeing what the word health meant. For funders and research leaders, the implication is uncomfortable but valuable: the development of shared understanding in large, newly formed transdisciplinary teams may not be easily short-cut. It is a matter of exposure and accumulated interaction, and expectations of rapid conceptual alignment should be managed accordingly. The extensive early management activity in this consortium, including co-developing a glossary, adopting mission-orientation, and building shared conceptual mental models, may have helped, but it may also have attempted to fast-track a process that could not be forced.

The study is equally instructive about the limits of NLP itself. The approach was labour intensive, combining automated analysis with manual, expert-led contextual interpretation, and the authors judge that it could not have provided rapid course corrections during the live programme. Interviewer words were included in the data, interview questions varied between rounds, the consortium restructured between phases, and normalisation across unevenly sized disciplinary groups posed non-trivial challenges. Any confident use of such methods, the authors argue, would require a dedicated validation exercise, ideally involving the interview participants themselves, along with minimum thresholds for token numbers and theme coherence.

Still, the authors see genuine promise. If datasets are larger, better formatted, and analysed with more efficient scaling, NLP could surface patterns that traditional qualitative analysis misses, and its semi-automated nature may reduce researcher bias. The clearest lesson, that shared language in transdisciplinary science takes years rather than months to emerge, and that less jargon ultimately proves more useful, is one that any team hoping to solve complex global challenges would do well to hear before the funding clock starts ticking.

Subject of Research: Using natural language processing to assess the development of shared transdisciplinary understanding in a large research consortium

Article Title: Using Natural Language Processing (NLP) to assess changes in transdisciplinary understandings across a large research consortium

Article References: Black, D., Gopsill, J., Rosenberg, G., Silvonen, T., Kukreja, A., & Hicks, B. (2026). Using Natural Language Processing (NLP) to assess changes in transdisciplinary understandings across a large research consortium. PLOS Sustainability and Transformation, 5(10), e0000222. https://doi.org/10.1371/journal.pstr.0000222

Image Credits: AI Generated

DOI: 10.1371/journal.pstr.0000222

Keywords: natural language processing, transdisciplinary research, interdisciplinary collaboration, research-on-research, co-word clustering, shared vocabulary, research consortium, team science, urban health, research evaluation, qualitative interviews, PLOS Sustainability and Transformation

Antimicrobial resistance, or AMR, is widely described by scientists and policymakers as one of the most pressing global challenges of the coming decades, and it is formally categorised as a ‘One Health’ problem because the forces driving it cut across human, animal and environmental health. Aquatic environments occupy a particularly awkward position in this picture. Water is an exceptional medium for the movement of bacteria and the genetic elements that carry resistance between them, and aquaculture systems both depend on and continuously interact with the rivers, canals and groundwater around them. When antimicrobial compounds enter pond water, whether through deliberate treatment or residual shedding, selective pressure favours bacteria that survive, and resistance genes can circulate through sediment, water columns and microbial communities in ways that are difficult to monitor and even harder to reverse. Professor Crumlish’s team argues that understanding these dynamics in a real production environment is essential to designing interventions that actually work.

Vietnam’s pangasius sector offers what the researchers describe as an ideal natural laboratory. Pangasius catfish farming is one of the world’s most important freshwater aquaculture industries by volume and export value, and its intensification over recent decades has been accompanied by growing recognition of AMR issues in the freshwater environments that host production. Intensive systems concentrate fish at high densities, which raises disease pressure, and when bacterial outbreaks strike, farmers frequently turn to antimicrobials as a first line of defence. The Stirling-led project will examine the causes and complexity behind resistance in these systems, but it will go a step further by also investigating the social and economic barriers that prevent alternative disease-management approaches from being adopted in the first place. That dual focus, on both the biology and the behaviour surrounding antibiotic use, is what the team describes as the study’s defining transdisciplinary character.

Professor Crumlish has been candid about the practical realities that drive antibiotic reliance on farms. When antibiotics stop working effectively in aquaculture, particularly in freshwater systems in Southeast Asia, farmers often have few alternatives available to them, yet they continue to trust antibiotic products even when those products are no longer effective. The result, she explains, is rapid development of resistance that can spill over into human, environmental and animal health, a pattern she identifies as a major concern. Rather than simply documenting the problem, the project has been designed to produce a novel research roadmap and a practical framework that can be adapted and applied in other countries facing similar challenges, an ambition that reflects the global nature of aquaculture and the shared biology of the resistance mechanisms involved.

The methodology at the heart of the project is co-creation. Over the next four years, researchers will work directly with farmers, policymakers, industry leaders and other stakeholders to ensure that any interventions they develop are both scientifically robust and realistically implementable. Alongside colleagues Dr Darren Green and Dr Noel Juvigny-Khenafou from Stirling’s Institute of Aquaculture, Professor Crumlish will collaborate with Dr Andrew Hoyle from the School of Computing, Data and Mathematical Sciences, Dr Saihong Li from the School of Communication, and Dr Till Stowasser from Stirling Business School. The inclusion of social scientists, data scientists and business researchers from the outset, rather than as an afterthought, is intended to surface the economic incentives, communication gaps and decision-making habits that determine whether a technically sound alternative to antibiotics ever reaches the pond.

The new grant builds directly on a body of previous research at Stirling investigating novel fish vaccines, including a recent trial conducted at the university’s National Aquaculture Technology and Innovation Hub, known as NATIH. Vaccination is widely regarded as one of the most promising tools for reducing antimicrobial dependence in finfish aquaculture, because preventing bacterial disease in the first place removes the need for therapeutic treatment. The transdisciplinary project will draw on data generated by these vaccine studies and share the findings with stakeholders as raw material for co-developing viable solutions and promoting better antibiotic stewardship across freshwater aquaculture. In effect, the team hopes to convert laboratory and trial-scale advances into a system-level change in how disease is managed on working farms.

The work will be carried out in partnership with the University of Glasgow, the University of Sydney, Can Tho University and Vietnam National University, a consortium that pairs UK and Australian research strength in microbiology, epidemiology and aquatic disease with Vietnamese institutions embedded in the regions where pangasius is actually farmed. This geographic and institutional spread matters for a problem of this kind. Resistance genes do not respect farm boundaries or national borders, and the conditions that shape antibiotic use, from extension services to market pressures, are locally specific. By grounding the research in Vietnamese production systems while connecting it to international expertise, the consortium aims to produce findings that are both locally actionable and globally transferable.

The funding envelope surrounding the project signals how seriously UK funders now treat the intersection of infection biology and food production. The £54 million programme, coordinated through UK Research and Innovation, is designed to prepare for future epidemics, tackle antimicrobial resistance and accelerate the development of next-generation animal vaccines. Professor Anne Ferguson-Smith, UKRI’s Executive Champion for Tackling Infections and Executive Chair of the Biotechnology and Biological Sciences Research Council, said the investment reflects UKRI’s central role in delivering government priorities and its long-standing commitment to convening partners across government to fund vital One Health research into human, animal and plant health. By pooling expertise from across the UK and global research and innovation ecosystem, she argued, related infectious disease challenges can be tackled in a more coordinated way, getting ahead of emerging biological threats and helping to protect people, animals, plants and the environment both domestically and internationally, advancing knowledge, improving lives and driving growth.

Professor Lucy Chappell, Chief Scientific Adviser at the Department of Health and Social Care and Chief Executive Officer of the National Institute for Health and Care Research, framed the investment in similarly interconnected terms. In a world where human, animal and environmental health are inherently linked and interdependent, she noted, diseases do not respect borders, and countries must work together to address their greatest health threats. Taking a One Health approach and bringing together experts from the UK and around the world, she said, allows threats to be identified earlier, strengthens resilience and delivers better health outcomes for the public. For the pangasius project specifically, that framing translates into a concrete ambition: within 48 months, to understand how resistance emerges in one of the world’s largest freshwater aquaculture industries, to map its impacts on production, and to chart a credible, farmer-endorsed path toward more sustainable disease management.

The stakes extend well beyond Vietnam. Aquaculture is among the fastest-growing food production sectors on the planet, and freshwater systems in Asia supply a substantial share of global fish consumption. If resistance renders existing antibiotics ineffective in these systems while alternatives remain out of economic or practical reach, the consequences will ripple through food security, rural livelihoods and public health simultaneously. What the Stirling-led consortium is proposing is essentially a test case for whether the aquaculture industry can decouple intensification from antimicrobial dependence, not through top-down regulation alone but through solutions built with the people who will have to use them. If the roadmap that emerges proves adaptable to other countries and other species, as the team intends, the humble catfish ponds of the Mekong Delta may end up shaping how the world manages infection far beyond their own waters.

Subject of Research: Antimicrobial resistance in Vietnamese pangasius catfish aquaculture

Article Title: University of Stirling secures £2.4M grant for major aquaculture project

Article References: University of Stirling secures £2.4M grant for major aquaculture project. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: antimicrobial resistance, aquaculture, pangasius catfish, Vietnam, One Health, University of Stirling, UKRI, fish vaccines, antibiotic stewardship, freshwater farming, Institute of Aquaculture, transdisciplinary research

The technical machinery behind the study is as important as its findings. Bibliometrics and scientometrics treat the scientific literature itself as a dataset: every paper becomes a node in a network, every citation a directed edge, every co-authorship a bond between institutions and nations. By systematically extracting these relationships and visualizing them with tools such as co-authorship mapping, the researchers could measure not only how much has been published about sustainability in higher education but who produces it, who cites it, and how tightly — or loosely — the global research community is woven together. This approach follows well-established methodological guidance in the field, including frameworks for conducting rigorous bibliometric reviews and the principles laid out in the Leiden Manifesto for responsible research metrics, which caution against reducing science to raw counts alone.

What the analysis found is a field that has expanded almost continuously since its modest beginnings in the mid-1970s. The early literature, emerging in the wake of the environmental movement and the concept of sustainable development, was sparse and largely concentrated in North America and Western Europe. Over subsequent decades, publication volumes climbed steadily, with particularly sharp acceleration after the United Nations launched its Decade of Education for Sustainable Development and, later, the 2030 Agenda and its seventeen Sustainable Development Goals. Universities responded to these policy signals by embedding sustainability into curricula, research agendas and institutional commitments, generating a corresponding wave of scholarly output that examined everything from key competencies for sustainable development to the greening of campus operations and the integration of the goals into formative academic offerings.

Yet the geography of this growth is deeply lopsided. Developed countries serve as the key drivers of scientific production in the field, accounting for the lion’s share of publications, citations and institutional leadership. Researchers in wealthy nations dominate the most-cited journals, convene the major conferences, and set the intellectual agenda for how sustainability should be taught. By contrast, the study identifies significant barriers limiting the participation of developing countries — most notably the scarcity of research funding and the lack of international cooperation. These constraints do not merely reduce publication counts; they adversely affect the global impact of scholarship produced in the Global South, where many of the most acute sustainability challenges — from climate vulnerability to biodiversity loss to energy poverty — are experienced most directly.

Perhaps the most technically revealing component of the study is its co-authorship network analysis, which exposes significant fragmentation in collaboration among researchers from different regions. In network terms, the global research community on sustainability in higher education is not a densely connected web but an archipelago of clusters, with strong ties within regions and institutions but comparatively weak bridges across them. This fragmentation matters for a very practical reason: sustainability is inherently a transdisciplinary enterprise, requiring the integration of insights from engineering, ecology, economics, pedagogy and the social sciences. When researchers from different regions and disciplines rarely co-publish, transdisciplinary approaches struggle to take root, and the field risks reproducing the same siloed thinking that sustainability education is meant to overcome.

The study also delivers a timely assessment of how the COVID-19 pandemic reshaped sustainability education. When campuses closed in 2020, universities were forced to migrate hands-on, experiential learning — a cornerstone of education for sustainable development — into digital environments. The analysis highlights the rapid adoption of hybrid pedagogical models that combine digital tools with practical approaches, a shift that began as emergency improvisation and has since evolved into a durable feature of the pedagogical landscape. Researchers who had long championed real-world learning opportunities, in which students move from the classroom into communities and workplaces to tackle live sustainability problems, found themselves redesigning these experiences for screens. The pandemic thus functioned as an unplanned stress test, accelerating digital transformation in ways that would otherwise have taken years.

The regional perspectives in the study are particularly valuable because they come from a research team rooted in Latin America and Europe rather than the traditional centers of bibliometric research in North America and Northern Europe. Latin American universities have been actively mapping their sustainability initiatives, from institutional declarations to curricular reforms, and scholarship from the region has documented both encouraging progress and persistent obstacles, including limited funding, heavy teaching loads and weak institutional incentives for sustainability research. Chilean universities, for example, have been the subject of bibliometric analyses of social responsibility, and Colombian institutions have been studied for holistic integration of sustainability. The new study situates these regional efforts within the global picture, showing how they connect — or fail to connect — to the wider network.

The authors close with recommendations aimed at strengthening international collaboration and consolidating regional research networks. Concretely, this means designing funding instruments that explicitly support North-South and South-South partnerships, reducing the administrative and financial barriers that keep researchers in developing countries out of international consortia, and building regional networks that can aggregate critical mass before plugging into global structures. It also means investing in the research infrastructure of the Global South — journal access, bibliometric visibility, open publishing pathways — so that locally generated knowledge about sustainability education can circulate globally rather than remaining invisible to citation indices, which are known to underrepresent journals from developing regions.

The stakes of these reforms could hardly be higher. Higher education institutions are widely regarded as critical actors in creating a sustainable future: they train the professionals who will design climate policy, manage ecosystems and transform industries, and they produce much of the research on which those decisions depend. If the knowledge base for sustainability education remains concentrated in a handful of wealthy countries, the solutions it generates will be shaped by a narrow band of experience and may fit poorly in the contexts that need them most. Conversely, a genuinely connected, well-funded and transdisciplinary global research community could accelerate the flow of good practice from wherever it emerges to wherever it is needed. The new analysis provides both a warning about the current state of the network and a quantitative roadmap for weaving it together.

Subject of Research: Bibliometric and scientometric analysis of global scientific production, collaboration networks and regional disparities in sustainability research within higher education since 1975.

Article Title: Global patterns in higher education and sustainability research: trends, collaboration networks and regional perspectives

Article References: Gunckel, T., Rubio, A., Guiu, R. F., & Moraga, H. (2026). Global patterns in higher education and sustainability research: trends, collaboration networks and regional perspectives. Journal of Environmental Studies and Sciences. https://doi.org/10.1007/s13412-026-01138-4

Image Credits: AI Generated

DOI: 10.1007/s13412-026-01138-4

Keywords: sustainability, higher education, bibliometric analysis, scientometrics, co-authorship networks, Sustainable Development Goals, international collaboration, developing countries, research funding, COVID-19, hybrid pedagogy, transdisciplinary research

The article, the product of a consensus workshop at an international meeting of the Organization for the Study of Sex Differences in May 2019 and a subsequent expert meeting in Ottawa sponsored by the Institute of Gender and Health of the Canadian Institutes of Health Research, brings together a strikingly interdisciplinary authorship. Neuroscientists, physiologists, historians of science, internists, nephrologists, nurses, social workers, epidemiologists, and implementation scientists, led by co-first authors Gillian Einstein of the University of Toronto and Louise Pilote of McGill University, along with senior author Cara Tannenbaum of the Université de Montréal, collectively propose a name and a vision for what they call Sex and Gender Science. They describe it as a transdisciplinary, integrative, bio-social-medical field that combines diverse methods to investigate how sex and gender dynamically interact to shape disease outcomes, illness experiences, and the very conduct of science itself.

The conceptual core of the proposal rests on the claim that sex and gender are interactional and deeply interwoven. Within sex, the authors situate hormonal, genetic, physiological, and morphological processes and characteristics, from chromosomal complements and gonadal steroid fluctuations to organ-level physiology and morphology. Within gender, they include roles, relations, norms, institutional imperatives, and identities, along with their downstream consequences for behavior, environment, access to resources, and exposure to stress. Crucially, the authors argue, these domains are not merely additive; they operate on each other. Gendered expectations influence hormonal and physiological responses, while biological traits shape how institutions and individuals respond to a person. In this framing, gender literally gets under the skin, while sex expresses itself inescapably through social worlds.

Concrete clinical examples illustrate the stakes. Acute coronary syndrome presents differently across patients in ways that reflect both vascular biology and gendered patterns of symptom recognition, care-seeking, and triage in emergency departments. In Alzheimer’s disease, two-thirds of affected individuals are women, and research discussed in the article points to interactions between reproductive histories, such as surgical menopause, stress physiology involving corticotropin-releasing factor, and gendered lifecourse exposures, rather than a single biological cause. In nephrology, sex differences in kidney physiology intersect with gendered differences in access to dialysis, transplantation, and medication adherence. Even occupational health reflects the interplay, as shown by analyses of personal protective equipment designed around male body norms during the COVID-19 pandemic, where ill-fitting gear compromised the safety of women in frontline roles. The authors also cite emerging concerns about automatic gender recognition technologies and gendered patterns of cannabis use disorder as domains where simplistic binary assumptions fail patients and obscure mechanisms.

Methodologically, Sex and Gender Science is defined by its refusal to choose between reductionist and constructionist approaches. The authors assume complexity, question established stereotypes and binaries, and support evolving methods that can capture interactional effects over time. That means experimental work in animal models attentive to sex as a biological variable can be paired with qualitative and quantitative human studies of gendered environments; intersectional epidemiology can be integrated with endocrine and genetic measurement; and implementation science can test whether sex- and gender-informed findings actually change clinical practice. The transdisciplinary ambition is deliberate: rather than creating another silo, the field aims to weave together the humanities, social sciences, and biomedical sciences, drawing on decades of feminist scholarship, gender studies, and basic biology that have until now developed along separate tracks.

The historical context for this synthesis is instructive. Biomedical research long treated male bodies as the default experimental subject, from clinical trials to preclinical animal studies, on the grounds that hormonal cycles made female subjects inconveniently variable. Landmark policy changes in the United States, Canada, and Europe over the past three decades required the inclusion of women in clinical research and the accounting for sex as a biological variable in grant applications. Simultaneously, scholars in gender and health demonstrated that social positions assigned by gender produce measurable health inequities, from differential exposure to violence and occupational hazards to differences in healthcare access and treatment. What was missing, the authors argue, was a systematic framework linking these two streams, so that researchers could ask not simply whether men and women differ, but how biological and social variables interact to produce particular outcomes in particular individuals.

The consensus process behind the article gives its claims unusual weight. By convening basic scientists who study sexually dimorphic neural circuits and stress pathways alongside clinicians, historians, and social scientists, the meeting produced a shared vocabulary and a shared commitment. The resulting highlights, as stated by the authors, include forging new ways of knowing about wellness, health, and disease; assuming complexity and questioning binaries; providing a more comprehensive picture of human health when sex and gender are studied together; and starting from the particularity of individuals with the ultimate goal of improving the well-being of all. That final point is significant politically as well as scientifically: the field explicitly encompasses transgender and gender-diverse populations, recognizing that gender identity itself interacts with biology in ways that mainstream medicine has historically ignored or pathologized.

For clinical practice, the implications are immediate. Diagnostic criteria, drug dosing, device design, and screening schedules built on averages derived from unrepresentative populations can be reexamined through the interactional lens that Sex and Gender Science provides. A patient is never just a sex and never just a gender; each person embodies a unique configuration of hormonal milieu, genetic background, organ physiology, gendered labor and caregiving burdens, institutional exposure, and identity. Precision medicine that ignores either domain is, on this argument, not precise at all. The authors point to the growth of national organizations, such as the Canadian Organization for Sex and Gender, and to curriculum reform in medical schools as evidence that institutional infrastructure is beginning to catch up with the science.

The article also acknowledges open questions and future directions. Measuring gender as rigorously as sex is measured remains an active methodological challenge, with validated instruments still evolving. Distinguishing interaction effects from confounding in observational data requires statistical sophistication and large, diverse cohorts. And the field must navigate political controversies surrounding sex and gender discourse without retreating from empirical evidence. The authors frame these challenges as generative rather than paralyzing, arguing that the very friction of integrating methods across disciplines produces better science, sharper questions, and more honest uncertainty. They call for funding structures, training programs, and publication venues that reward transdisciplinary work rather than penalizing it in favor of narrow, single-domain studies.

If Sex and Gender Science succeeds on its own terms, the payoff could be a medicine that finally matches the complexity of the patients it serves: one in which a heart attack, a dementia diagnosis, a kidney transplant, or a workplace injury is understood through the full entanglement of chromosomes, hormones, organs, identities, relationships, and institutions that shaped it. The article’s message to researchers is blunt in its simplicity. It is not either sex or gender; it is both, together. After decades of separation, the biological and the social are being brought back into a single scientific frame, and the authors argue that the health of everyone stands to gain from what this emerging field discovers next.

Subject of Research: Sex and Gender Science, an emerging transdisciplinary field integrating biological sex and social gender in health research

Article Title: Sex & Gender Science: integrating the social with the biological

Article References: Einstein, G., Pilote, L., De Vries, G., Richardson, S., Forger, N., Perović, M., Ahmed, S., Bauer, G., Graham, I. D., Greaves, L., Klinge, I., Logie, C. H., McKay, D., McMurtry, M. S., Oliffe, J. L., & Tannenbaum, C. (2026). Sex & Gender Science: integrating the social with the biological. Biology of Sex Differences. https://doi.org/10.1186/s13293-026-00977-8

Image Credits: AI Generated

DOI: 10.1186/s13293-026-00977-8

Keywords: sex and gender science, biological sex, gender and health, transdisciplinary research, Biology of Sex Differences, health inequities, sex differences, gender identity, precision medicine, Alzheimer's disease, cardiovascular disease, Canadian Institutes of Health Research