Lessons from World Bank Research on Financial Crises

The benefits of financial development and globalization have come with continuing fragility in financial sectors. Periodic crises have had real but heterogeneous welfare impacts and not just for poor people; indeed, some of the conditions that foster deep and persistent poverty, such as lack of connectivity to markets, have provided a degree of protection for the poor. Past crises have also had longer-term impacts for some of those affected, most notably through the nutrition and schooling of children in poor families. As in other areas of policy, effective responses to a crisis require sound data and must take account of incentives and behavior. An important lesson from past experience is that the short-term responses to a crisis -- macroeconomic stabilization, trade policies, financial sector policies and social -- cannot ignore longer-term implications for both economic development and vulnerability to future crises.Financial crisis; macroeconomic response; social protection; poverty; safety nets

Raising irrigation productivity and releasing water for intersectoral needs (RIPARWIN): RIPARWIN final technical report

River basinsHydrologyRiver basin managementRiver basin developmentDevelopment projectsWater allocationIrrigation waterProductivityIrrigation managementRiceTanzaniaGreat Ruaha River BasinUsangu River Basin

Academic motherhood and fieldwork: Juggling time, emotions and competing demands

The idea and practice of going ‘into the field’ to conduct research and gather data is a deeply rooted aspect of Geography as a discipline. For global North Development Geographers, amongst others, this usually entails travelling to, and spending periods of time in, often far-flung parts of the global South. Forging a successful academic career as a Development Geographer in the UK, is therefore to some extent predicated on mobility. This paper aims to critically engage with the gendered aspects of this expected mobility, focusing on the challenges and time constraints that are apparent when conducting overseas fieldwork as a mother, unaccompanied by her children. The paper emphasises the emotion work that is entailed in balancing the competing demands of overseas fieldwork and mothering, and begins to think through the implications of these challenges in terms of the types of knowledge we produce, as well as in relation to gender equality within the academy

Aerodynamics of aero-engine installation

This paper describes current progress in the development of methods to assess aero-engine airframe installation effects. The aerodynamic characteristics of isolated intakes, a typical transonic transport aircraft as well as a combination of a through-flow nacelle and aircraft configuration have been evaluated. The validation task for an isolated engine nacelle is carried out with concern for the accuracy in the assessment of intake performance descriptors such as mass flow capture ratio and drag rise Mach number. The necessary mesh and modelling requirements to simulate the nacelle aerodynamics are determined. Furthermore, the validation of the numerical model for the aircraft is performed as an extension of work that has been carried out under previous drag prediction research programmes. The validation of the aircraft model has been extended to include the geometry with through flow nacelles. Finally, the assessment of the mutual impact of the through flow nacelle and aircraft aerodynamics was performed. The drag and lift coefficient breakdown has been presented in order to identify the component sources of the drag associated with the engine installation. The paper concludes with an assessment of installation drag for through-flow nacelles and the determination of aerodynamic interference between the nacelle and the aircraft

Redefining Simulation Fidelity for Healthcare Education

Background. Fidelity - an intrinsic property of simulation is crucial to simulation design and to educational effectiveness. Yet the term fidelity is inconsistently used, which makes it difficult to draw inferences from current literature and translate research into practice. Aim. In this article, we attempt to bring some clarity to the term simulation fidelity in healthcare education. Method. We are opposed to the notion that high-fidelity simulation requires complete and faithful replication of reality, and instead argue for an accurate representation of real-world cues and stimuli. We address a number of issues surrounding the term fidelity and how it is currently used in the literature. Result. In recognising the limitations of current methods of describing fidelity in the literature, we propose an alternative 3-dimensional framework for fidelity along the axes of the patient, clinical scenario, and healthcare facilities as a means for more precise and practical positioning of current healthcare simulation activities. Conclusion. All aspects of fidelity significantly hinge on the learners’ perceived realism of the context of the learning episode as opposed to any one particular element such as the technology used.Peer reviewe

Evidence-informed health policy: are we beginning to get there at last

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

The Federal Big Data Research and Development Strategic Plan

This document was developed through the contributions of the NITRD Big Data SSG members and staff. A special thanks and appreciation to the core team of editors, writers, and reviewers: Lida Beninson (NSF), Quincy Brown (NSF), Elizabeth Burrows (NSF), Dana Hunter (NSF), Craig Jolley (USAID), Meredith Lee (DHS), Nishal Mohan (NSF), Chloe Poston (NSF), Renata Rawlings-Goss (NSF), Carly Robinson (DOE Science), Alejandro Suarez (NSF), Martin Wiener (NSF), and Fen Zhao (NSF). A national Big Data1 innovation ecosystem is essential to enabling knowledge discovery from and confident action informed by the vast resource of new and diverse datasets that are rapidly becoming available in nearly every aspect of life. Big Data has the potential to radically improve the lives of all Americans. It is now possible to combine disparate, dynamic, and distributed datasets and enable everything from predicting the future behavior of complex systems to precise medical treatments, smart energy usage, and focused educational curricula. Government agency research and public-private partnerships, together with the education and training of future data scientists, will enable applications that directly benefit society and the economy of the Nation. To derive the greatest benefits from the many, rich sources of Big Data, the Administration announced a “Big Data Research and Development Initiative” on March 29, 2012.2 Dr. John P. Holdren, Assistant to the President for Science and Technology and Director of the Office of Science and Technology Policy, stated that the initiative “promises to transform our ability to use Big Data for scientific discovery, environmental and biomedical research, education, and national security.” The Federal Big Data Research and Development Strategic Plan (Plan) builds upon the promise and excitement of the myriad applications enabled by Big Data with the objective of guiding Federal agencies as they develop and expand their individual mission-driven programs and investments related to Big Data. The Plan is based on inputs from a series of Federal agency and public activities, and a shared vision: We envision a Big Data innovation ecosystem in which the ability to analyze, extract information from, and make decisions and discoveries based upon large, diverse, and real-time datasets enables new capabilities for Federal agencies and the Nation at large; accelerates the process of scientific discovery and innovation; leads to new fields of research and new areas of inquiry that would otherwise be impossible; educates the next generation of 21st century scientists and engineers; and promotes new economic growth. The Plan is built around seven strategies that represent key areas of importance for Big Data research and development (R&D). Priorities listed within each strategy highlight the intended outcomes that can be addressed by the missions and research funding of NITRD agencies. These include advancing human understanding in all branches of science, medicine, and security; ensuring the Nation’s continued leadership in research and development; and enhancing the Nation’s ability to address pressing societal and environmental issues facing the Nation and the world through research and development

The Federal Big Data Research and Development Strategic Plan

This document was developed through the contributions of the NITRD Big Data SSG members and staff. A special thanks and appreciation to the core team of editors, writers, and reviewers: Lida Beninson (NSF), Quincy Brown (NSF), Elizabeth Burrows (NSF), Dana Hunter (NSF), Craig Jolley (USAID), Meredith Lee (DHS), Nishal Mohan (NSF), Chloe Poston (NSF), Renata Rawlings-Goss (NSF), Carly Robinson (DOE Science), Alejandro Suarez (NSF), Martin Wiener (NSF), and Fen Zhao (NSF). A national Big Data1 innovation ecosystem is essential to enabling knowledge discovery from and confident action informed by the vast resource of new and diverse datasets that are rapidly becoming available in nearly every aspect of life. Big Data has the potential to radically improve the lives of all Americans. It is now possible to combine disparate, dynamic, and distributed datasets and enable everything from predicting the future behavior of complex systems to precise medical treatments, smart energy usage, and focused educational curricula. Government agency research and public-private partnerships, together with the education and training of future data scientists, will enable applications that directly benefit society and the economy of the Nation. To derive the greatest benefits from the many, rich sources of Big Data, the Administration announced a “Big Data Research and Development Initiative” on March 29, 2012.2 Dr. John P. Holdren, Assistant to the President for Science and Technology and Director of the Office of Science and Technology Policy, stated that the initiative “promises to transform our ability to use Big Data for scientific discovery, environmental and biomedical research, education, and national security.” The Federal Big Data Research and Development Strategic Plan (Plan) builds upon the promise and excitement of the myriad applications enabled by Big Data with the objective of guiding Federal agencies as they develop and expand their individual mission-driven programs and investments related to Big Data. The Plan is based on inputs from a series of Federal agency and public activities, and a shared vision: We envision a Big Data innovation ecosystem in which the ability to analyze, extract information from, and make decisions and discoveries based upon large, diverse, and real-time datasets enables new capabilities for Federal agencies and the Nation at large; accelerates the process of scientific discovery and innovation; leads to new fields of research and new areas of inquiry that would otherwise be impossible; educates the next generation of 21st century scientists and engineers; and promotes new economic growth. The Plan is built around seven strategies that represent key areas of importance for Big Data research and development (R&D). Priorities listed within each strategy highlight the intended outcomes that can be addressed by the missions and research funding of NITRD agencies. These include advancing human understanding in all branches of science, medicine, and security; ensuring the Nation’s continued leadership in research and development; and enhancing the Nation’s ability to address pressing societal and environmental issues facing the Nation and the world through research and development

The utilisation of health research in policy-making: Concepts, examples and methods of assessment

The importance of health research utilisation in policy-making, and of understanding the mechanisms involved, is increasingly recognised. Recent reports calling for more resources to improve health in developing countries, and global pressures for accountability, draw greater attention to research-informed policy-making. Key utilisation issues have been described for at least twenty years, but the growing focus on health research systems creates additional dimensions. The utilisation of health research in policy-making should contribute to policies that may eventually lead to desired outcomes, including health gains. In this article, exploration of these issues is combined with a review of various forms of policy-making. When this is linked to analysis of different types of health research, it assists in building a comprehensive account of the diverse meanings of research utilisation. Previous studies report methods and conceptual frameworks that have been applied, if with varying degrees of success, to record utilisation in policy-making. These studies reveal various examples of research impact within a general picture of underutilisation. Factors potentially enhancing utilisation can be identified by exploration of: priority setting; activities of the health research system at the interface between research and policy-making; and the role of the recipients, or 'receptors', of health research. An interfaces and receptors model provides a framework for analysis. Recommendations about possible methods for assessing health research utilisation follow identification of the purposes of such assessments. Our conclusion is that research utilisation can be better understood, and enhanced, by developing assessment methods informed by conceptual analysis and review of previous studies