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Making agriculture sustainable is a global challenge. In the European Union (EU), the Common Agricultural Policy (CAP) is failing with respect to biodiversity, climate, soil, land degradation as well as socio‐economic challenges. The European Commission's proposal for a CAP post‐2020 provides a scope for enhanced sustainability. However, it also allows Member States to choose low‐ambition implementation pathways. It therefore remains essential to address citizens' demands for sustainable agriculture and rectify systemic weaknesses in the CAP, using the full breadth of available scientific evidence and knowledge. Concerned about current attempts to dilute the environmental ambition of the future CAP, and the lack of concrete proposals for improving the CAP in the draft of the European Green Deal, we call on the European Parliament, Council and Commission to adopt 10 urgent action points for delivering sustainable food production, biodiversity conservation and climate mitigation. Knowledge is available to help moving towards evidence‐based, sustainable European agriculture that can benefit people, nature and their joint futures. The statements made in this article have the broad support of the scientific community, as expressed by above 3,600 signatories to the preprint version of this manuscript. The list can be found here (https://doi.org/10.5281/zenodo.3685632). A free Plain Language Summary can be found within the Supporting Information of this article. A free Plain Language Summary can be found within the Supporting Information of this article.

Context: Health inequalities are systematic differences in health among social groups that are caused by unequal exposure to—and distributions of—the social determinants of health (SDH). They are persistent between and within countries despite action to reduce them. Advocacy is a means of promoting policies that improve health equity, but the literature on how to do so effectively is dispersed. The aim of this review is to synthesize the evidence in the academic and gray literature and to provide a body of knowledge for advocates to draw on to inform their efforts. Methods: This article is a systematic review of the academic literature and a fixed-length systematic search of the gray literature. After applying our inclusion criteria, we analyzed our findings according to our predefined dimensions of advocacy for health equity. Last, we synthesized our findings and made a critical appraisal of the literature. Findings: The policy world is complex, and scientific evidence is unlikely to be conclusive in making decisions. Timely qualitative, interdisciplinary, and mixed-methods research may be valuable in advocacy efforts. The potential impact of evidence can be increased by \"packaging\" it as part of knowledge transfer and translation. Increased contact between researchers and policymakers could improve the uptake of research in policy processes. Researchers can play a role in advocacy efforts, although health professionals and disadvantaged people, who have direct contact with or experience of hardship, can be particularly persuasive in advocacy efforts. Different types of advocacy messages can accompany evidence, but messages should be tailored to advocacy target. Several barriers hamper advocacy efforts. The most frequently cited in the academic literature are the current political and economic zeitgeist and related public opinion, which tend to blame disadvantaged people for their ill health, even though biomedical approaches to health and political short-termism also act as barriers. These barriers could be tackled through long-term actions to raise public awareness and understanding of the SDH and through training of health professionals in advocacy. Advocates need to take advantage of \"windows of opportunity,\" which open and close quickly, and demonstrate expertise and credibility. Conclusions: This article brings together for the first time evidence from the academic and the gray literature and provides a building block for efforts to advocate for health equity. Evidence regarding many of the dimensions is scant, and additional research is merited, particularly concerning the applicability of findings outside the English-speaking world. Advocacy organizations have a central role in advocating for health equity, given the challenges bridging the worlds of civil society, research, and policy.

Based on an ethnography of the international Safe Motherhood Initiative (SMI), this article charts the rise of evidence-based advocacy (EBA), a term global-level maternal health advocates have used to indicate the use of scientific evidence to bolster the SMI's authority in the global health arena. EBA represents a shift in the SMI's priorities and tactics over the past two decades, from a call to promote poor women's health on the grounds of feminism and social justice (entailing broadscale action) to the enumeration of much more narrowly defined practices to avert maternal deaths whose outcomes and cost effectiveness can be measured and evaluated. Though linked to the growth of an audit- and business-oriented ethos, we draw from anthropological theory of global forms to argue that EBA–or \"playing the numbers game\"–profoundly affects nearly every facet of evidence production, bringing about ambivalent reactions and a contested technocratic narrowing of the SMI's policy agenda.

[Purpose/Significance] The formulation of evidence-based science and technology policy critically relies on the timely and accurate provision of relevant, high-quality evidence. However, current evidence recommendation practices often suffer from significant limitations in both accuracy and efficiency, hindering the scientific rigor and intelligent application of evidence within the policy-making process. These shortcomings hinder policymakers' ability to leverage the most pertinent research and data, potentially leading to suboptimal decisions. Addressing this critical gap, this research proposes a novel knowledge graph-based evidence recommendation method. The primary objective is to substantially enhance the scientific foundation and intelligent capabilities of evidence utilization during policy formulation. This method aims to empower policymakers by providing more reliable, contextually relevant, and efficiently retrieved data support. Ultimately this will foster more robust, transparent, and demonstrably effective science and technology policies grounded in comprehensive research insights. [Method/Process] To achieve these objectives, this study systematically constructs a domain-specific knowledge graph meticulously centered on the intricate citation relationships between policy documents and academic research papers. This graph serves as the foundational semantic network representing entities (policies, articles, topics, authors, institute etc.) and their multifaceted interconnections. Most importantly, we introduce and adapt the Knowledge Graph Attention Network (KGAT) algorithm n an innovative way. Leveraging KGAT's sophisticated graph attention mechanisms, our model effectively captures and learns complex, high-order semantic relationships between policy requirements (represented as queries or specific nodes) and potential evidence sources (research paper nodes). This deep relational understanding enables nuanced evidence relevance scoring and personalized recommendation. To rigorously validate the proposed method's practical efficacy and performance, we conducted an extensive empirical study within the specific domain of agricultural science and technology policy. Furthermore, to demonstrate real-world applicability and provide a tangible tool for policymakers, we designed and implemented a fully functional Evidence Intelligent Recommendation System (EIRS). This system seamlessly integrates the core KG-based recommendation engine and incorporates advanced intelligent analysis capabilities. Significantly, EIRS supports an end-to-end workflow initiated by natural language policy questions posed by users, enabling intuitive interaction and precise, demand-driven evidence retrieval and recommendation. [Results/Conclusions] Experimental results, conducted on real-world datasets within the agricultural science and technology policy domain, demonstrate the superior performance of the proposed KGAT-based recommendation method. It consistently outperforms several state-of-the-art baseline algorithms across multiple key evaluation metrics, including precision, recall, normalized discounted cumulative gain (NDCG), and mean reciprocal rank (MRR). This quantitatively confirms its significantly stronger recommendation capability. In addition to quantitative metrics, the model inherently offers enhanced explainability due to the transparent nature of the knowledge graph structure and the attention weights learned by KGAT, allowing for insights into why specific evidence is recommended, based on its semantic connections to the policy query. Concurrently, the implemented EIRS has proven to be highly effective in practice. It efficiently identifies and recommends evidence resources exhibiting a strong match with complex policy requirements expressed in natural language. The system's successful deployment underscores its potential to tangibly augment the scientific underpinning of science and technology policy development. By effectively bridging the gap between vast research knowledge and specific policy needs through intelligent, accurate, and explainable recommendations, this research provides a novel, practical pathway towards realizing truly intelligent and rigorously evidence-based policy formulation processes. The methodology and system prototype offer a valuable and adaptable framework for various policy domains beyond the presented case study.

Universities are one of few institutions positioned to address a critical challenge facing the United States—the drift toward hyperpartisan and interest-driven politics. To build better public policymaking, many policymakers have called for the rigorous research and dispassionate analysis that universities are well positioned to supply. To improve communication between knowledge producers and policy consumers, a framework is applied that specifies the types of conceptual and logistical knowledge that honest knowledge brokers need: know-why (action is required), know-about (barriers to research utilization in policymaking), know-what (policy issue is timely and research is relevant), know-who (to target), and know-how (to effectively communicate research to policymakers). The experiences learned from the long-standing Wisconsin Family Impact Seminars are used to describe the potential payoff when universities communicate high-quality, nonpartisan research to policymakers. The article elaborates on best practices to leverage the deliberately dispassionate and disproportionately powerful contributions that universities can make to policymaking.

Retractions warn users against relying on problematic evidence. Until recently, it has not been possible to systematically examine the influence of retracted research on policy literature. Here, we use three databases to measure the extent of the phenomenon and explore what it might tell us about the users of such evidence. We identify policy-relevant documents that cite retracted research, we review and categorize the nature of citations, and we interview policy document authors. Overall, we find that 2.3% of retracted research is policy-cited. This seems higher than one might have expected, similar even to some notable benchmarks for “normal” nonretracted research that is policy-cited. The phenomenon is also multifaceted. First, certain types of retracted research (those with errors, types 1 and 4) are more likely to be policy-cited than other types (those without errors, types 2 and 3). Second, although some policy-relevant documents cite retracted research negatively, positive citations are twice as common and frequently occur after retraction. Third, certain types of policy organizations appear better at identifying problematic research and are perhaps more discerning when selecting and evaluating research.

This article documents a debate between the two authors on the issue of microplastics in the environment. It is sparked by a viewpoint published by G. Allen Burton, who argues that the risk of microplastics is overrated. The authors have started debating this notion on Twitter, but the format has quickly turned out to be too cumbersome to exchange arguments. It is thus decided to continue the conversation by exchanging letters published as preprints in roughly four‐week intervals. In these contributions, a broad range of relevant issues are touched upon, including the differences in risk conceptions, risk communication in the attention economy, risk assessment in situations of scientific uncertainty, the need to test proper hypotheses, the problem of prioritizing environmental issues, the costs of action and inaction, the application of the precautionary principle or a strictly evidence‐based approach for policy‐making and, eventually, larger issues related to the Anthropocene. In hindsight, it is felt that this debate is rewarding because it made possible expressing and reflecting on the values and opinions in ways otherwise impossible in social media and standard scientific articles. Borne out of an argument over the environmental risks of microplastics on Twitter, the authors exchange their views on risk conceptions and communication in the attention economy, risk assessment and scientific uncertainty, hypothesis testing, prioritizing environmental issues, the costs of (in)action, the precautionary principle in decision‐making and, eventually, larger Anthropocene issues.

It is easy to show that the UK Government rarely conducts ‘evidence-based policymaking’, but not to describe a politically feasible use of evidence in Westminster politics. Rather, we need to understand developments from a policymaker’s perspective before we can offer advice to which they will pay attention. ‘Policy-based evidence’ (PBE) is a dramatic political slogan, not a way to promote pragmatic discussion. We need to do more than declare PBE if we seek to influence the relationship between evidence and policymaking. To produce more meaningful categories we need clearer criteria which take into account the need to combine evidence, values, and political judgement. To that end, I synthesise policy theories to identify the limits to the use of evidence in policy, and case studies of ‘families policies’ to show how governments use evidence politically.

The Australian Government's 5‐year Threatened Species Strategy contains four priority action areas and associated targets. Here, we argue that the well‐publicized target to cull 2 million feral cats has a weak scientific basis because: (1) reliable estimates of Australia's cat population size did not exist when the target was set; (2) it is extremely difficult to measure progress (numbers of cats killed) in an accurate, reliable way; and, most importantly, (3) the cull target is not explicitly linked to direct conservation outcomes (e.g., measured increases in threatened species populations). These limitations mean that the cull target fails to meet what would be considered best practice for pest management. The focus on killing cats runs the risk of distracting attention away from other threats to biodiversity, most prominent of which is widespread, ongoing habitat loss, which has been largely overlooked in the Threatened Species Strategy. The culling target is a highly visible symbol of a broader campaign around feral cat research and management in Australia, rather than a direct indicator of conservation action and success. We are concerned that progress toward the 2 million target could be misinterpreted as progress toward conserving threatened species, when the link between the two is not clear.

Factors associated with acute malnutrition are complex and wide‐ranging particularly in developing countries. In Mozambique, contextual factors associated to children acute malnutrition are yet to be fully investigated and the evidences used to better inform prevention programme. The objective of this study is to identify key factors associated with acute malnutrition among 6‐ to 59‐month‐old children living in nine districts in rural Mozambique assessed in the 2018 seasonal nutrition assessment. We analysed Standardized Monitoring and Assessment for Relief and Transition (SMART) nutrition survey data of 1,116 children from three districts and rapid nutrition assessment (RNA) data of 3,884 children from six districts of Mozambique. We used a multiple logistic regression analysis to respond to the research question. Experiencing diarrhoea [odds ratio (OR) = 4.54; P = 0.001] was the only variable associated with acute malnutrition from the SMART survey dataset, whereas in the RNA, fever (OR = 3.0; P = 0.000) access to sanitation (OR = 0.118; P = 0.037), experiencing shock in the household (OR = 0.5; P = 0.020), diarrhoea (OR = 2.41; P = 0.001) and cough (OR = 1.75; P = 0.030) were the variables with significant association to acute malnutrition. We believe that the findings were influenced by the proportion of acute malnutrition in each survey type. Study findings confirm the association between acute malnutrition and child's health outcomes that are generally linked to poor living conditions and independent effects of shocks. This highlights the need for policy and programme to implement integrated, cross‐sectoral approaches to tackling child acute malnutrition, particularly addressing community level conditions such as water and sanitation.