Effective regulation is essential for preventing the establishment of new invasive plants and managing the environmental, social, and economic impacts of those already established. Invasive plants are regulated by jurisdictions at a variety of local, regional, national, and international levels. Enhanced coordination of policy and regulations has been identified as a key strategy for addressing the impacts of invasive species (IPBES 2023; Pluess et al. 2012); however, coordination between jurisdictions, and even within jurisdictions, is not always considered. To review regulatory coordination in Australia, we compiled a comprehensive dataset of noxious weeds (defined as invasive plants and potentially invasive plants with controls specified in regulation) in each Australian jurisdiction (i.e., State or Territory). We found that jurisdictions on average shared c. 67% (SD = 15%) of noxious weed listings. Neighbouring jurisdictions were not more similar than separated jurisdictions in their noxious weed listings. There were significant differences in the biogeographic native ranges of noxious weeds between jurisdictions, with species native to temperate Asia being most frequently listed overall. The predominant likely entry pathway for noxious weeds in Australia was the ornamental trade. Listings were primarily dedicated to proactive control, prohibiting the cultivation of noxious weeds to avoid their naturalisation. There were 415 noxious weeds regulated in a harmonious manner across jurisdictions. However, there were 327 noxious weeds regulated by jurisdictions in a discordant manner, potentially leaving neighbouring jurisdictions vulnerable to invasion. We suggest jurisdictions reassess the regulation of these 327 discordant noxious weeds in Australia and utilise a national taxonomic standard to avoid problematic synonyms. Improved cohesion of policies could be achieved through wider adoption of existing regulatory systems and co-development of regulations between government and industry.

Reducing inequalities in preconception health and care is critical to improving the health and life chances of current and future generations. A hybrid workshop was held at the 2023 UK Preconception Early and Mid-Career Researchers (EMCR) Network conference to co-develop recommendations on ways to address inequalities in preconception health and care. The workshop engaged multi-disciplinary professionals across diverse career stages and people with lived experience (total n = 69). Interactive discussions explored barriers to achieving optimal preconception health, driving influences of inequalities and recommendations. The Socio-Ecological Model framed the identified themes, with recommendations structured at interpersonal (e.g. community engagement), institutional (e.g. integration of preconception care within existing services) and environmental/societal levels (e.g. education in schools). The co-developed recommendations provide a framework for addressing inequalities in preconception health, emphasising the importance of a whole-systems approach. Further research and evidence-based interventions are now needed to advance the advocacy and implementation of our recommendations.

Over recent decades it has consistently been shown that disabled adults in the UK fare worse in the labour market and have lower levels of wellbeing than non-disabled adults. However, this is in part due to the selection into dis-ability of those with existing socio-economic disadvantages. In this article, we use panel data from the combined British Household Panel Survey and Understanding Society, covering the 27 years from 1991 to 2018, to distinguish between the effect of selection, the effect of dis-ability onset and the effect of dis-ability duration on a range of labour market and wellbeing outcomes. We show that there is important selection both into dis-ability and into longer experience of dis-ability on the basis of observable characteristics. We also show the importance of controlling for time-invariant unobservable individual characteristics that similarly affect selection into dis-ability and duration of dis-ability. Even after controlling for both forms of selection, we find significant negative effects of dis-ability onset and duration, and offer policy solutions to address them.

To address the global challenge of plastic waste, 175 UN Member States are negotiating a legally binding instrument, the Plastic Treaty, aimed at ending plastic pollution. This ambitious framework, targeting both terrestrial and marine sources, is being developed through Intergovernmental Negotiating Committee meetings scheduled to conclude by 2025. Amidst uncertainties and power dynamics influencing state positions, this research identifies 10 critical, yet unresolved, points within the treaty negotiations (i.e., the scope of the treaty, equity and differentiation, involvement of non-state actors, integration with existing agreements, standards and specifications, trade implications, monitoring and reporting, responsibility and historical contributions, binding vs. non-binding commitments, and financing and technology transfer). The findings suggest potential compromises in the treaty’s environmental provisions, influenced by domestic interests and international power disparities. As negotiations progress, the imperative for cooperation and decisive action against plastic pollution becomes increasingly pressing, challenging member states to prioritize global environmental integrity over national interests.

Iron toxicity is one of the constraints limiting rice production in Africa. This study used a randomized controlled trial to assess the impact of an iron toxicity-tolerant variety, named ARICA 6, on different outcomes and investment in modern inputs by smallholder farmers. Two rounds of data were collected from 520 rice-farming households in Guinea. Results showed that the use of ARICA 6 increased rice yield by 330 kg ha−1 and net income by US$ 120 ha−1. However, adoption of improved variety may not be enough to crowd in investment in modern inputs because farmers face other constraints.

College student food insecurity (FI) is a public health concern. Programming and policies to support students have expanded but utilisation is often limited. The aim of this study was to summarise the barriers to accessing college FI programming guided by the social ecological model (SEM) framework. A scoping review of peer-reviewed literature included an electronic search conducted in MEDLINE, ERIC, and PubMed databases, with a secondary search in Google Scholar. Of the 138 articles identified, 18 articles met eligibility criteria and were included. Articles primarily encompassed organisational (17/18) level barriers, followed by individual (15/18), relationship (15/18), community (9/18), and policy (6/18) levels. Individual barriers included seven themes: Knowledge of Process, Awareness, Limited Time or Schedules, Personal Transportation, Internal Stigma, Perception of Need, and Type of Student. Four relationship barriers were identified: External Stigma, Comparing Need, Limited Availability Causes Negative Perceptions, and Staff. Ten barrier themes comprised the organisational level: Application Process, Operational Process, Location, Hours of Operation, Food Quality, Food Quantity, Food Desirability or Variety of Food, Marketing Materials, Awareness of the Program, and COVID-19 Restrictions. Two barrier themes were identified at the community level, Public Transportation and Awareness of SNAP, while one barrier theme, SNAP Eligibility and Process, encompassed the policy level. Higher education stakeholders should seek to overcome these barriers to the use of food programmes as a means to address the issue of college FI. This review offers recommendations to overcome these barriers at each SEM level.

In our ever digitalising society, our engagement with the online world has significant potential to have a negative impact on our mental health. Although the roles of public health and psychiatry are debated, clinicians are in a strategic position to assess usage and intervene, to prevent harms from problematic engagement with the internet.

We use Benford's law to examine the non-random elements of health care costs. We find that as health care expenditures increase, the conformity to the expected distribution of naturally occurring numbers worsens, indicating a tendency towards inefficient treatment. Government insurers follow Benford's law better than private insurers indicating more efficient treatment. Surprisingly, self-insured patients suffer the most from non-clinical cost factors. We suggest that cost saving efforts to reduce non-clinical expenses should be focused on more severe, costly encounters. Doing so focuses cost reduction efforts on less than 10% of encounters that constitute over 70% of dollars spent on health care treatment.

Russell and Burch’s 1959 original definitions of the 3Rs (replacement, reduction and refinement) are widely used today as standards for the ethical use of non-human animals in research, although they have a number of limitations. Authors and institutions around the world have addressed some of these, coming up in certain cases with more accurate, functional, and up-to-date definitions. However, not only do there still remain limitations needing to be addressed, but some that have been addressed resulted in discrepancies, contradictions, and general confusion as to how best apply the 3Rs in practice. In order to clarify the meaning of the 3Rs and enable more optimal implementation of these principles in animal experimentation, this article provides a theoretical discussion for revised definitions of the original 3Rs via examination of some of their main limitations and inconsistencies. First, we offer up the original definitions as presented in the context of Russell and Burch’s book The Principles of Humane Experimental Technique. Then, we examine the main limitations and present clear specifications and requirements for such revised definitions. After presenting our revised definitions, we conclude with various implications for animal welfare within the context of experimentation.

In recent years, China’s strong commitment to the political agenda of ecological civilisation has increased the presence of environmental education (EE) in the policy arena. Using the waste classification policy as an example, this research explores the implementation of EE policy in two Chinese primary schools. Through the use of a policy enactment framework, the findings reveal that contextual factors such as school enrolment, infrastructure and external influences from the District Bureau greatly influence the schools’ policy capacity. By exploring the internal policy flow and school artefacts, it was found that although the waste classification policy was enacted similarly in the selected primary schools, the outcomes differed significantly. These variations highlight the complexities and challenges of implementing an EE policy under ecological civilisation and contribute to the understanding of the tension between localised adaptations and the nationally politicised EE policy mandates.

The beef industry is facing increasing pressure to adopt sustainable practices, driven by environmental, economic, and social concerns. Designing effective policies that satisfy industry demands while aligning with public interests is a complex challenge. Using a nationally representative survey of 3,001 U.S. residents, we employ a best–worst scaling approach to assess preferences for nine beef sustainability policies. Results reveal consumers prioritize affordability of beef products and welfare of cattle as most important sustainability policies. Conversely, policies addressing greenhouse gas emissions from cattle production are least important, with less than 6% of respondents preferring them.

In the three years since the law on adult deceased organ donation consent in England changed to include an opt-out system, there has been no discernible change to donation rates. The lack of a positive impact on donation rates was predicted by many of those who took part in debates before and during the passage of the Bill through Parliament. This invites the question as to why England moved to an opt-out system for organ donation despite equivocal evidence of likely benefit and opposition from expert health professional organisations. To address this question qualitative analyses of Parliamentary debates on organ donation was undertaken. This revealed a shift from a dominant position, which gave primacy to the evidence of likely effects, towards a more normative position where a deemed consent option was viewed as the ‘correct thing to do’ and the limited and conflicting evidence viewed in a positive light. By 2017, following Wales's move to an opt-out system, together with continued lobbying for similar changes for England by professional and patient groups, alongside sustained public popularity for organ donation, the balance of opinion had shifted towards a system where deemed consent would become the default position for most English adults

The purpose of this paper is to answer the research question: How may methods of Benefit–Cost Analysis (BCA) influence policy decision-makers? The new research is a continuation of the previous research, and it is updated with new data and new examples. As it is well-known by BCA experts and practitioners, BCA is a relatively simple and widely used technique for deciding whether to make a change. BCA is very important in political and governmental decisions. Governments are policy creators, and Governments are usually formed of politicians. How much do experts inside Governments influence the policymakers? Do politicians allow enough experts to influence policymaking? The research regarding the work of the Croatian Government’s Office for Legislation and its Unit for the system and coordination of the Assessment of the Effects of Regulations (Unit) showed that the analysis of that Unit was not very good in some very important laws. These laws were changed very often because in practice was seen that the application of some laws was not good, and had caused some problems for the citizens, caused legal uncertainty for them, and in some cases had caused a lot of damage.

Common approaches for improving the mental health of the population in general and of vulnerable groups in particular include policies to address social determinants and the expansion of professional health services. Both approaches have substantial limitations in practice. A more promising option is actions that utilize resources that either already exist or can easily be generated in local communities. Examples are provided for various local initiatives with the potential to facilitate helpful interactions and relationships that are likely to benefit the mental health of significant parts of the population. Developing and implementing such initiatives is a challenge to communities, while their evaluation may require innovative methods in research.

In the burgeoning landscape of African smart cities, education stands as a cornerstone for sustainable development and unlocking future potential. Accurate student performance prediction holds immense social importance, enabling early intervention, improved learning outcomes, and equitable access to quality education, aligning with sustainable development goals. Traditional models often falter in Africa due to imbalanced datasets and irrelevant features. This research leverages machine learning in Nigerian classrooms to predict underperforming students. Techniques like synthetic minority oversampling, edited nearest neighbors, and the Boruta algorithm for feature selection, alongside genetic algorithms for efficiency, enhance model performance. The ensemble models achieve AUCs of 90–99.7%, effectively separating low-performing and high-performing students. Implemented via Streamlit and Heroku, these models support real-time, data-driven decisions, enhancing early intervention, personalized learning, and informing policy and public service design. This ensures equitable education and a brighter future across Africa. By leveraging ML, this research empowers universities to support struggling students, optimize educational costs, and promote inclusive development, fostering data-driven decision-making and resource allocation optimization. Ultimately, this research paves the way for a future where data empowers education within African smart cities, unlocking the full potential of data-driven solutions and ensuring equitable educational opportunities across the continent.