The British Academy is the United Kingdom's national academy for the humanities and the social sciences.It was established in 1902 and received its royal charter in the same year. It is now a fellowship of more than 1,000 leading scholars spanning all disciplines across the humanities and social sciences and a funding body for research projects across the United Kingdom. The academy is a self-governing and independent registered charity, based at 10–11 Carlton House Terrace in London.The British Academy is funded with an annual grant from the Department for Business, Innovation and Skills (BIS). In 2014/15 the British Academy's total income was £33,100,000, including £27,000,000 from BIS. £32,900,000 was distributed during the year in research grants, awards and charitable activities.
Large-scale research and technology infrastructure investment decisions should be evidence-informed, yet the long-term, economy-wide effects of these investments remain difficult to establish. The evaluation literature has identified the constraints: attribution is hard, comparison groups are rarely available, and the interval between investment and measurable effect often exceeds the evaluation window. What has been missing is not recognition of these problems but settings in which they can be overcome. This contribution brings together two academic studies—one macroeconomic, one microeconomic—in which the historical variation setting permits credible causal estimates of the returns to public research. Neither settles the general question of what public research returns; each shows what becomes measurable when the identification problem is solved, and in both cases, what becomes visible complicates a prevailing assumption, demonstrating the value in complementing policy-led evaluations with those from academia. Four policy implications follow: (i) economic effects depend on the type of knowledge produced, the composition of expenditure, and the industrial context, so evidence from one programme may not transfer to another; (ii) where mission-oriented investment is expected to generate wider economic spillovers, that expectation should be evidenced rather than assumed; (iii) in the case examined here, the spillovers that justify public investment were weaker for applied, mission-directed research than the basic-research rationale would predict; and (iv) the value of research infrastructure includes not only financial cost but the time and knowledge embodied in tools and equipment.
ABSTRACT The main goal of this review paper is to systematically investigate the vital role of Artificial Intelligence (AI) in enabling the design, operation, and optimization of next‐generation energy systems, including smart grids, predictive maintenance, and decentralized frameworks. These energy systems are often enhanced through their tight integration with the Internet of Things (IoT) and blockchain technology. Such innovations provide substantial techno‐economic and environmental benefits by reducing carbon emissions, improving operational efficiency, and promoting greater energy equity. To support these objectives with a solid analytical foundation, the study employs a political, environmental, social, and technological framework to evaluate the most influential AI‐driven applications and adoption drivers in the energy sector. Ultimately, the study highlights how ongoing interdisciplinary and cross‐regional research efforts, especially between Asia and Europe, are accelerating the development, scalability, and real‐world deployment of smart and sustainable energy solutions, while also identifying key technical, ethical, and regulatory challenges that must be addressed for large‐scale implementation.
Indigenous participatory rights, as set out in the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), are collective rights for Indigenous Peoples to have a say in decisions affecting them - something these communities are envisaged as doing "through their own representative institutions" (Article 19). However, the conditions of group representation are not clearly spelled out in the UNDRIP or in commentaries on its provisions. Our article addresses this in two inter-connected ways. First, we distinguish genuine spokesperson speech from three other kinds of representative speech (speaking about the group, speaking as a group member, and speaking in behalf of a group). Second, we identify two minimal conditions of genuine spokesperson speech: that the spokesperson be authorised by the group in whose name they speak, and that the spokesperson speaks for the group willingly and knowingly. While relatively simple in theory, each of these conditions throws up a number of questions, such as who gets to authorise a spokesperson and how individuals might be compelled into acting as spokesperson. We conclude the paper by turning briefly to the issue of how states and the law ought to better ensure that Indigenous Peoples are able to have a say through their proper spokespersons.
Although the role of international organizations in the diffusion of education policy is widely acknowledged, their role in the articulation of policy ideas remains comparatively underresearched. This article addresses this gap through a case study on the role of the OECD in the construction of the School Autonomy with Accountability policy model-a governance approach that grants schools greater decision-making capacity in exchange for more intensive monitoring mechanisms. Informed by a combination of interviews and documentary analysis, our article shows that the construction of the model within the OECD has followed different stages, with the model enjoying varying levels of visibility, contestation, and universalist ambition in each of them. The article shows that model construction is an erratic process affected by the interplay of different forms of expertise and hierarchies, and it cautions against totalizing narratives that portray international organizations as coherent all-powerful entities.
